2016

2016

Artificial Intelligence in Marketing

  • Episode: 209
  • |
  • Topic: Digital Business
Sameer Patel, CEO, Kahuna
Sameer Patel
Chief Executive Officer
Kahuna
Andrew Eichenbaum, Lead Data Scientist, Kahuna
Andrew Eichenbaum
Lead Data Scientist
Kahuna
Michael Krigsman, Founder, CXOTalk
Michael Krigsman
Industry Analyst
CXOTALK

Marketing technology is undergoing dramatic transformation as companies seek greater personalization to engage buyers across the customer lifecycle. This episode examines how AI is changing marketing. Our guest are Sameer Patel, CEO, and Andrew Eichenbaum, Lead Data Scientist, at Kahuna software. 

Sameer joined Kahuna in August, 2016 as CEO and board member. Prior to Kahuna, Sameer was GM/SVP at SAP/SuccessFactors where he led the team that was responsible for making SAP a leading provider of Collaboration and Customer Engagement solutions with 35 million subscribers. Prior to SAP, Sameer worked consulting and systems integrator business. Sameer has a BS in Finance and Economics from Babson College and a Masters in MIS from Boston University.

Dr. Andrew Eichenbaum is a leading Data Scientist specializing in artificial intelligence and machine learning. Andrew has been analyzing large scale data sets for over 15 years and leading data-centric projects and teams for more than 8 years.

In industry, Andrew has worked with a range of large organization including Orange, Intel, and Intuit. He has also worked in early to mid-stage start-ups including Shopping.com, MyBuys (now Magnetic), and was on the founding team of Yummly. He has particular expertise in creating, leading, and scaling high-performing Data Science and Advanced Analytics teams. He is a sought-after speaker around the topics of Data Science, team dynamics, and performance management.

Transcript

Michael Krigsman: Welcome to Episode #209 of CXOTalk, and on this CXOTalk, we are celebrating the holiday season. And how are we celebrating the holiday season? We’re going to have a great conversation. That’s our way of celebrating. I’m Michael Krigsman, I am an industry analyst and the host of CXOTalk, and CXOTalk brings together people who are shaping the future; the most innovative people in the world, for in-depth conversation. And you are part of that conversation, so as we’re talking right now, there’s a tweet chat taking place on Twitter, with the hashtag #cxotalk. And I’m so thrilled, because today, we’re speaking on the topic of artificial intelligence - AI - in marketing. We’re here with Sameer Patel, who is an old friend - I’ve known Sameer for years - who is CEO of Kahuna Software, and his colleague Andrew Eichenbaum, who is Kahuna’s lead data scientist. Gentlemen, how are you?

Sameer Patel: Fantastic! How are you, Michael?

Andrew Eichenbaum: Doing great.

Michael Krigsman: I am excellent. And you know, I was thinking we should have brought, I should have worn a Santa hat.

Andrew Eichenbaum: Yeah. The Starbucks-branded Christmas cup here…

Michael Krigsman: Alright, well that’s good. So we have some Christmas cheer happening here.

Sameer Patel: Mhmm.

Michael Krigsman: So Sameer and Andrew, please. Sameer, why don’t you tell us about Kahuna Software.

Sameer Patel: Sure. So, thanks for having us. So, Kahuna software is a B2C marketing automation provider. We have built a real-time platform that allows brands to be able to understand what the interests and preferences of their consumers literally within seconds, be able to make sense of it, add it to the profile, and put meaningful offers in front of them, be that for a commerce vendor or if you’re a media company and you need to engage your prospects, this is the new way of using artificial intelligence to engage with your consumers on the right device at the right time.

It’s in California, we’re a four year old company, we’re privileged to be funded by Sequoia Capital, and SoftTech Ventures, and Tenaya is our lead investor, and a whole bunch of other amazing people supporting us. And, we’re about 60 people, mostly in California, some in New York and the others in Vancouver. Andrew?

Michael Krigsman: Hey Andrew, you’re Lead Data Scientist, so what is it that you actually do? What does a Lead Data Scientist do?

Andrew Eichenbaum: So, that actually is an interesting question, because when I was looking around at places, I joined at the Kahuna just about a quarter ago. I actually had not looked at marketing places. I had actually done consulting work with large companies; Intel, Intuit; with their marketing groups, and suggested things like recommendations, personalization, and they said, “This is great,” well, everybody had sort of left it at that point. When I was contacted, this was the first company that really thought of marketing as data, and then what can we do with this data? How can it better help us understand people and better mail to them; better send to them; know “when,” “where,” “how,” and pretty much not spam them? So, the data scientist sort of stuck in the middle of making sure the data’s all good, and then being able to figure out all of these things.

Michael Krigsman: Fantastic! So, why don’t we kick this off with a discussion of B2B, B2C marketing; your business to consumer marketing? But you’re selling to … Your end customers are consumers, but you’re selling to businesses. \

Sameer Patel: Yeah, I mean our end-customers are consumer brands who engage with you and me as consumers who buy stuff, right? So one of the great things about taking over this business is that it’s very easy to keep yourself honest and know if you’re getting useful stuff, because all of us are consumers often, or any of the recipients of what Kahuna does, right? So, you know

Michael Krigsman: Welcome to Episode #209 of CXOTalk, and on this CXOTalk, we are celebrating the holiday season. And how are we celebrating the holiday season? We’re going to have a great conversation. That’s our way of celebrating. I’m Michael Krigsman, I am an industry analyst and the host of CXOTalk, and CXOTalk brings together people who are shaping the future; the most innovative people in the world, for in-depth conversation. And you are part of that conversation, so as we’re talking right now, there’s a tweet chat taking place on Twitter, with the hashtag #cxotalk. And I’m so thrilled, because today, we’re speaking on the topic of artificial intelligence - AI - in marketing. We’re here with Sameer Patel, who is an old friend - I’ve known Sameer for years - who is CEO of Kahuna Software, and his colleague Andrew Eichenbaum, who is Kahuna’s lead data scientist. Gentlemen, how are you?

Sameer Patel: Fantastic! How are you, Michael?

Andrew Eichenbaum: Doing great.

Michael Krigsman: I am excellent. And you know, I was thinking we should have brought, I should have worn a Santa hat.

Andrew Eichenbaum: Yeah. The Starbucks-branded Christmas cup here…

Michael Krigsman: Alright, well that’s good. So we have some Christmas cheer happening here.

Sameer Patel: Mhmm.

Michael Krigsman: So Sameer and Andrew, please. Sameer, why don’t you tell us about Kahuna Software.

Sameer Patel: Sure. So, thanks for having us. So, Kahuna software is a B2C marketing automation provider. We have built a real-time platform that allows brands to be able to understand what the interests and preferences of their consumers literally within seconds, be able to make sense of it, add it to the profile, and put meaningful offers in front of them, be that for a commerce vendor or if you’re a media company and you need to engage your prospects, this is the new way of using artificial intelligence to engage with your consumers on the right device at the right time.

It’s in California, we’re a four year old company, we’re privileged to be funded by Sequoia Capital, and SoftTech Ventures, and Tenaya is our lead investor, and a whole bunch of other amazing people supporting us. And, we’re about 60 people, mostly in California, some in New York and the others in Vancouver. Andrew?

Michael Krigsman: Hey Andrew, you’re Lead Data Scientist, so what is it that you actually do? What does a Lead Data Scientist do?

Andrew Eichenbaum: So, that actually is an interesting question, because when I was looking around at places, I joined at the Kahuna just about a quarter ago. I actually had not looked at marketing places. I had actually done consulting work with large companies; Intel, Intuit; with their marketing groups, and suggested things like recommendations, personalization, and they said, “This is great,” well, everybody had sort of left it at that point. When I was contacted, this was the first company that really thought of marketing as data, and then what can we do with this data? How can it better help us understand people and better mail to them; better send to them; know “when,” “where,” “how,” and pretty much not spam them? So, the data scientist sort of stuck in the middle of making sure the data’s all good, and then being able to figure out all of these things.

Michael Krigsman: Fantastic! So, why don’t we kick this off with a discussion of B2B, B2C marketing; your business to consumer marketing? But you’re selling to … Your end customers are consumers, but you’re selling to businesses. \

Sameer Patel: Yeah, I mean our end-customers are consumer brands who engage with you and me as consumers who buy stuff, right? So one of the great things about taking over this business is that it’s very easy to keep yourself honest and know if you’re getting useful stuff, because all of us are consumers often, or any of the recipients of what Kahuna does, right? So, you know and in the B2C of the consumer space, I think in the last four or five years, we’ve seen probably the most tectonic shifts in terms of how you and me as consumers want to engage, and be engaged by brands, right?

And, you know, the specific area where Kahuna plays is the area of retention, right? So you might use ad technology and other ways to drive new customer acquisition. Where Kahuna comes in place is how do you get existing customers to engage more to make that first purchase go from first, to second, to third, and really drive loyalty for [...]? So, that is a very specific place where we end up, where the majority of our folks and all of our folks as a company.

You know, one of the most interesting things that when we look at some of the convergence and a need for consumer brands to begin to rethink how they engage, and transact with the consumers … If you look back at the last four or five years and see the changes that have happened in terms of how we expect brands to work with us, you look at some of the most common - and I apologize because I overuse examples, but I think that should matter. You know, when you look at the notion of how you procure a ride on Uber, for example: You go from this point of them making an offer to you consuming the service, and finishing the service, and at no point during the whole lifecycle did you ever think someone was marketing to you. You thought you won: you needed a taxi, they provided supply at that point and location where you needed it, you used it, you consumed it, you moved on.

You know, when you, and Michael you know I’ve talked about this, I love when you look at Amazon for example, right? And you see a wish list, and you see things that Amazon might recommend to you, for getting to a point where I don’t think - at least I will speak for myself, I almost never find what Amazon is recommending to be annoying. I may not buy, but it super relevant. And we’re getting to the space where if offers can be as relevant and as timely as they seem to be becoming, for some of the more digitally native and proficient brands, you know, we are willing to accept more and more of what might otherwise have looked like spam if it were not well-targeted, right?

So Kahuna is focused on taking that kind of an experience to every single consumer brand out there. How do we get brands to truly be able to engage, just at the right time, with the right offer, on the right device, based on the digital breadcrumbs that you and I today are leaving, every single day, you know? You’re on your mobile phone, you’re browsing stuff; you’re putting stuff in wish lists; you’re almost buying; you’re looking at goods ten times. We never had this kind of information as brands to be able to truly understand what you are interested in; how we put that to use in a way that respects how a consumer wants to work; and really, that is what gets us to work every day. We try to get better, and better, and better at [...].

Michael Krigsman: So Andrew, this notion is very interesting, what Sameer just said, that when you are buying a product, say from Uber, you don’t think that they’re marketing to you, you don’t interpret messages as spam, and so, is relevance the key for consumers to have that kind of open, warmth, and acceptingness of marketing messages so they actually seek it, rather than push it away?

Andrew Eichenbaum: So, let me take a step back to put this in context. To start off with what Sameer is saying, we’re in this sort of new era, where you can market to anybody, probably 14-16 hours a day. People are that connect to their cell phone, it’s always there, there are multiple channels to reach out to them, and that’s all through one device. This is something which has become ubiquitous, at least in the US market over the past sort of five years. Now that being said, it’s easy enough to spam them, and nobody wants to do that because people have become hypersensitive to the whole situation of, “I’ve got one bad message, okay, you’re in the cutting block. Second bad message two days later, you’re gone.” And the reacquisition cost to pull somebody back in is amazingly high.

So, the question is it’s not just not sending them spam, it’s knowing what to send them, when to send to them, how you send to them, because there’s a whole range of things. What message do you want to send to them? And, it just extends out.

One of the most interesting things you could think of is not to think about goals, like I want to sell this person a product, I want them to move the next step down my path. We’re now in an area where we can think about I want to increase my expected long term value of all my customers. I want to increase their overall engagement stake, and this is what marketers can now reach to. This can be what seemed to be a more nebulous goal before, is now something that we can actually move forward and try and act on.

Sameer Patel: You know, Michael, one of the things that’s interesting to just sort of note as we have this discussion is try to understand the baseline first, right? We always will talk about better ways to do stuff, but I always like to spend a little time just talking about where does the market sit today? So, against this backdrop of this very sophisticated consumer and their expectations that I had just described, and that we talk about, it’s really also important to say, “Okay, how does the existing technologies in place stack up to that very increasingly demanding customer,” right? And it’s pretty daunting when you start to think about how marketing automation created a decade ago stacks up to that, right? The market’s over ten billion dollars in size, yet there is over two hundred and eighty billion dollars worth of goods left in abandoned shopping carts every single year. Two hundred eighty billion dollars, right? That’s how much you and I go and we almost buy, and we put it in the shopping cart, and we leave it there, and you’re just effectively nudging the consumer to the finish line, or providing them with a handholding and the information and the research that might be required to persuade them to finish buying. So, you’re left with almost … If you look at some of the research that is out there right now, the conversion rates are 2-3% on all this expense on commerce. That’s how bad it is.

Michael Krigsman: When you say the conversion rates are 2-3%, which conversion rate specifically?

Sameer Patel: E-commerce. So when you look across e-commerce today, all the investment being put into what seemed like the right offers lead to 2-3% of conversion, right? And, you know, we’re now finally at a point where you can begin to bring together both the art and the science of marketing, given the advancements in technology which is what I’m going to talk about on the show later today, to start to say how do I take those meaningful messages; but that’s not enough, I’ve got to find A) as meaningful as they can be, B) how they’re being put out at the right time on the right device that we were saying earlier, because the consumer is telling you, “Look, I’m sharing my location with you on my phone, I’m sharing with you things that I’m interested in, this is not those days of email marketing where you knew nothing about me and you spammed me. You better well be doing much better than you are right now,” right?

And how does the backdrop where you start to truly understand the difference between the technology that 90% of consumers are using today, and increasingly what the brands they’re using today, and increasingly, the new persona of this digitally-connected consumer. Does that make sense?

Michael Krigsman: Okay, so we’re in this situation where if you can more accurately tailor the content, the message, the timing, and the channel to the consumer, to the online consumer, that person will be more receptive, because “Oh yeah, I’m getting something that I care about.” That’s the bottom line here, right?

Sameer Patel: That’s the bottom line! I mean, it doesn’t have to be commerce only, right? This is deeper on all sorts of messages that various online companies want to put in front of you. It could be about engaging for a show like CXOTalk where you’re going after consumers. It’s the same problem [...] too. Seriously, right? The thinking about how to put meaningful content won, but secondly, did they hear you? And this is why I love this business, because we are all consumers when walk out the office in the evening.

Michael Krigsman: Okay. So Andrew Eichenbaum, again, you’re a data scientist, and artificial intelligence comes into play here to solve this problem. Tell us about that.

Andrew Eichenbaum: Artificial intelligence can solve many problems. The question is can you define what you really want? You might ask the system if you tell your data scientist to go off, and I want to increase our revenues by X amount, and the data scientist goes off and increases your revenues, and then three weeks later, everybody goes away, and nobody’s bothering to see your site anymore and they’re asking “What happened, data scientist?” “I increased your revenues. We never talked about lifetime value and things like that, but you were able to increase your revenue by 50%.” [Laughter] It’s a double-edged sword.

Michael Krigsman: “So I spammed everybody, I increased your revenues like you told me, but you didn’t tell me you wanted me to keep these people coming back!”

Andrew Eichenbaum: That’s right. So, it’s a double-edged sword. Data science is sort of half science, half black arts, much like the rest of marketing. You have these fields and understandings of what’s going on and what you think about the consumer, and how you think they work. The only difference with data science, is data science is always asked to prove it with numbers. You know, looking back at data, and looking forward. But, the interesting thing is that all the rest of marketing is following along those lines too. People are being asked to say it’s not just hearts and minds, it’s what numbers … What were the returns? What was our ROI on the spend for these sets of campaigns? So on and so forth.

Michael Krigsman: But how does the AI work? Can you just dig in a little bit and make that AI connection? So, what do you mean by AI in this context? What’s the kind of data that you look at? How does this all …

Andrew Eichenbaum: Sure, yeah. That’s a good question. So, let me give an example: when a baby is born, they don’t understand the idea that something is hot. So, it takes them a while: they’re standing, they can see, say there’s a pot on the stove on the burner, and it’s boiling away. And they don’t know anything so they touch it, and they burn themselves. But, in coming closer and closer, you start getting in those things, “Oh, that could be hot.” Or you start learning, you put your hand a little closer, a little closer, a little closer, and constantly getting warmer and warmer without actually having to touch and hurt yourself. It’s a feedback system.

Most of modern AI is exactly the same thing. It’s what are called “supervised learning systems”. We have large amounts of historical data, where we know the outcome. So, we say we believe to get this outcome, we should look at all of this data beforehand. And so what we do is we have these programs, which we say, “Here’s all of the inputs, here’s what we want,” it’s either good or bad by the definition, or however you want to define your outcome, and then you pass it through the system and it spits out something like, “This is good.” Well you know it was good, so you reinforce and you say, “Oh, and it’s all happy.” And you pass another thing to the system and it says, “This is good,” it’s like, “No, it was bad.” You pretty much slap it and you say, “It should really have been marked bad.” And you do this over and over again. So, it’s learning the exact same way someone would learn that something is hot, or something is cold. You get a better understanding over time from a whole range of input variables.

Sameer Patel: That’s a really important point, right? Because I think there’s so much hype around this topic right now, and one of the things is … And when we talk to customers, this is whether in the sales cycle or the customer success programs, you have to start to have a very open discussion with customers about where the state of AI is today, promise them that you’re kind of at the edge, or the bleeding edge of it, but make no mistake, it’s a constant process of refinement and improvement and improvement, right?

And so, you know, maybe another way to also build on what Andrew said in terms of where the AI come in, there are a couple of places where the AI comes in. And one is, you know, what is the point of all of this? The point of all of this in plain English is how do you begin to move from what I like to call “lazy segmentation and coding,” because the technology just has never been sophisticated, so we kept putting random people into buckets just to make ourselves feel good that these segments actually matter; and starting to move in a direction where you’re starting to really engage and transact with an audience of one.

Now, to do that, you’re going to have to do … There are different places where AI gets injected. Maybe you can talk about it from the standpoint of how do we do it from a [...] standpoint, to understand how you cooperate with the end-user. And maybe the second piece here, Michael, that we’re talking about to where we .... And this is again where … I’ve written a blog post about the things I learned in the first sixty days of coming here, and one of the things I learned, coming from the outside in, was the amount of peanut butter in AI that happens in the industry, right? And you have to also talk about the integrity and the real-time access to data before you apply any AI to it. So one of the things that we do in Kahuna is within five seconds of you making a gesture within a mobile app on your phone, Kahuna will record that [...] a profile; and within thirty seconds we can put out an offer.

If you don’t have that level of immediacy, no amount of peanut buttering … That’s just putting AI on … It’s just making your bad data smarter, in its own way, right? So I don’t know, maybe you just want to talk about those aspects of where in this process you would specifically inject these concepts to actually [...].

Andrew Eichenbaum: So let me touch to both of those points that Sameer brought up. First about the data: Data is good. Data is great. It’s sort of the centerpoint of data science. But, if the data is junk, the data science coming out will be junk as well, so a large piece of any data scientist’s lie for the team is making sure the data’s coming to the system, is properly being stored, planned, verified, so that when we finally get to have fun and play with these advanced systems, we can believe in the results coming out, because if not, why bother doing it?

Michael Krigsman: So, how is this different from traditional marketing? So again, from the techniques that you’re bringing to bear with AI and machine learning, how is it different from the way marketing, digital marketing was handled up until this point?

Andrew Eichenbaum: Yes, so let me give some direct experience. So, I worked at a company called “MyBuys,” it’s now part of Magnetic; this was about eight-ten years ago; and we were providing Amazon-like recommendations of service - various midsize companies. And, one of the things we did there, or I did there, was to figure out what the optimum time to send out to a client base, and that being an entire consumer base, and you can plot it out over time for the entire base [...]. It’s best if we send out the last email at 10AM on Tuesday morning. And so, we backed out, starting a little beforehand until then, and it was all good. And then we were able to see significant lift.

But, now we have the ability to actually do this on an individual basis. We’ve seen an individual come in and respond to messages, or not respond to messages for various channels over the past couple of months. And we know how they respond to what type of message. So, we’re no longer blasting out to the entire group at a single time of the week. We can actually set up our campaigns so that an individual user will be sent out right before the expected time or act, and in a public channel. So this is the real thing. And you say, “Well, that’s a hell of a lot,” when you’re literally giving the orders of magnitude more data to do this. And the other bit is that Moore’s Law has helped us. We have a huge amount more processing power, and it’s not the limiting factor anymore.

Sameer Patel: What is the number? Is that half a billion events today?

Andrew Eichenbaum: Yes, so Kahuna on its own process has half a billion events today. And, it’s literally linear scalable system we can rerun in the cloud and simply add more computerization as we get more data.

Sameer Patel: So I think there’s another way to also look at this. Michael, I know you’ve been a follower of enterprise technology for so long, so if you also start to look at the … If you look at the predecessor to what Kahuna is today, the predecessor to Kahuna were email delivery systems that were built a decade ago. And again, no disrespect to that model, that was state of the art back then. The way to not have to put a flyer in your mailbox, email was a great alternative to do that at scale for much of it, right? So you totally [...].

We’ve now reached a point where the number of engagement and touchpoints for us as consumers has gone from one, which was email, to many. And we haven’t even seen this play out yet, right? So today the dominant ones are email still, and mobile; SMS. We’re going to have beacons tomorrow, we’re going to have IoT after that, we’re going to have chatbots, right? It’s going to go … The places where we engage are going to increase.

The other amazing thing about where we are right now is that every one of those engagement touch points are going to start sending different events to us, that again, email jsut never sends back. So if you do not have a system today that can accept these signals from these different engagement touchpoints, make sense of them, add them to Michael’s profile, but still have the luxury and the [...], if you will, to say, “I may have learned something new by Michael through a gesture on a mobile phone, but the right way to engage with Michael based on machine learning, is 7PM on Thursday nights, via email, because that’s when he seems to be on his laptop and he seems to want to engage and buy stuff.” You have to start as a marketeer, decouple the smarts of the system, and where you want to engage with people. This is where the technology has fundamentally shifted from what were truly nothing more than email delivery machines. You know, batch and blast, batch and blast, batch and blast, right? That allows marketeers to engage in a fundamentally different way.

Michael Krigsman: Andrew, can you drill down a little bit, and give us some concrete examples to kind of maybe walk us through how you look at the data, in order to personalize to that level of the individual that Sameer was just describing, using AI?

Andrew Eichenbaum: Sure. We can … Let me talk about a project we’re working on right now, and it’s a question of whether we should send an email or not. So we set up this batch, you optimize everything, each individual has a send time, but the question is: Should we be interacting with them at all? You can ask yourself the question, do we expect them to interact with this message, or do we even need to send the message because we expect them to interact with the site, the media anyhow, so that the cost of this message isn’t lost because there was no reason to.

I guess the best way to put this is we look at their history. We look at all the ways that they are interacting with the site over the past roughly hundred days. We look at all the different messages that they receive, how they interacted with those messages, or had they not interacted with those messages that we see, but that their site usage has gone up.

There is a bunch of other things going in there, probably a bit too much at this point; it’s trying to understand the expectations of using the site and whether people want to pay the costs of the email, where they say it’s not worth it at this point in time.

MIchael Krigsman: So you have this body of historical data, [on] an individual, about what they’ve done, their open rates on that email, is that correct? And then you’re looking at that historical data and doing analysis on it?

Sameer Patel: So there’s two pieces though, right? There’s the data that Kahuna collects, and then because of how the system is architected, if a customer -  if it’s a commerce example,we can even pull in point of sale data enriching the profile, right? So that’s again the benefit of having built an API first-model of four years ago, and not 20 years ago where the system [...].

Andrew Eichenbaum: So also, remember we’re not looking at just email. We’re looking at email, we’re looking at push notifications, SMS, a whole range. Because when that message was sent out, even before I ask a question - the sort of last-minute question - “Should we send the thing out or not?”, we need to understand what’s the best way to reach out to them. And [after we]look up the message and the time of day, and the requirements from the marketeer, we might want to send out a push notification, which is completely separate.

This comes back to a more interesting question that even the other modern marketers aren’t sort of attacking, in that this is really a derivative problem. It’s not just how many times have you opened your emails and moved forwards? How many push notifications like, “Ok, you that your last two messages were push notifications over this past two and a half weeks, and your interaction for this, and a number of other things, how should we message?” There’s this whole encompassing profile of where you are in the short-term, the mid-term, and the long-term, and how that defines how we should interact with you going forward.

Michael Krigsman: So it’s not just a matter of counting up times. [Laughter]

Andrew Eichenbaum: You can do that, but you don’t get the lists that you do. You’re back to where we were five years ago.

Michael Krigsman: Okay. So now, you’ve got this body of data, you’re making these inferences essentially about individual consumers, the type of content they like, when they like to read it or receive that content, and which channel, and so forth. So we’ve got all of that, and we’re applying these advanced AI and machine learning techniques to it, what do we get as a result? Why are we doing this?

Andrew Eichenbaum: You’re not spamming your consumer, is the easiest result. You’re telling them what they want to know on their timescale. My goal is not to market to people, it’s to make suggestions to people. If they never feel like they’re marketed to, but we’re sending them messages, then I feel that we’ve reached the ultimate goal. We’ve influenced the people without them ever thinking that they were being influenced. They were being passed information that is relevant to them at the point in time that it would be most relevant to them.

Sameer Patel: And that’s a very good point. I think one of the things that, you know, Andrew very astutely said, is being … The rhetoric right now, which is kind of disappointing; and again, because I came from the outside into this world, it’s one of the first things I’ve picked up when I took the role as I tried to understand how the industry was speaking. And we kind of went from this “Let’s drop the email, email’s dead. It’s all about mobile,” and you get to a point where none of us wants to get excessive notifications on our phones. That certainly doesn’t make it correct, because it’s become [...], right?

 So, this notion of being cross-channel at your core, where you can actually engage with people in a way that respects the pace at which they want to go through this journey, we’ve got brands, we’ve got big consumer brands that have massive segments of their customers, who say, “Look, the primary engagement model needs to be email, and mobile once in a while.” That same customer has very lucrative segments of people who want to buy from them that say, “Absolutely not. I need more mobile, some SMS.” We have to let every brand decide what is that right combination for every demographic or user type that you have, and respect the pace at which those consumers want to engage with these brands and transact. Sometimes, it helps the brand figure out, “You know what, it’s going to take four, or five, or six engagement touchpoints before you get to a place where you can get to whatever you define as your goal, be that conversion or what-have-you.”

We can’t assume steep cliffs, nor can you assume gradual rises. You have to start to respect the pace at which you run the most. So these are some of the things we think really hard about, and brands are starting to understand that we can’t switch completely to the other end, and just start hammering people with mobile notifications, right? It’s an interesting problem that I’m not seeing everybody solve, but I feel like we spend an adequate amount of time thinking about it. Do you agree with that?

Andrew Eichenbaum: Yes.

Michael Krigsman: So, when you deliver information that is cued again to the type of content, who it’s being delivered to, tailored to, how they like to receive it, when they like to receive it; in a sense what’s happening is you are bypassing the mental filters that the receiver sets up to block out that we all have, to automatically try to block out the meaningless barrage of marketing noise, that we get all the time.

Sameer Patel: Yeah, and I mean you know, yeah.

Michael Krigsman: Because I care about it. I care about this. I happen to be interested in things like cameras and microphones, and plug-ins for audio, and all that kind of stuff.

Sameer Patel: Of course you are!

Michael Krigsman: And when they … and isn’t everybody? And when I look at websites, and I see these things, I don’t look at it and say, “That’s creepy. I hate that.” I look at it and say, “Oh, that’s interesting.”

Sameer Patel: You know, yeah. I think you nailed it, and I think this is where… You know, unfortunately as consumers, we have normalized in some ways to a world of batch and blast that was created ten and fifteen years ago, where we get an adequate amount of spam and it’s not until I think now, in the last two or three years, where there’s actually enough technology advancement for us to sort of wake up and say, “Why are we dealing with the second grade way of living and getting hit, and getting spammed? And why can’t every commerce retailer be … Why can’t the recommendation engines be as targeted as some of the big brands that have been invented in the last four or five years?” And that to us is success, when we get customers to begin to sort of …

Every e-commerce vendor, every media company, every travel company, all of the industries that we play heavily in; if we can get them to that place, our job’s done.

Andrew Eichenbaum: For me, those banner ads are whatever pushes or emails that you get are great, but I hate them. Like I just purchased this a day ago. I don’t want to be seeing these. These are now the most annoying ads I could ever see. I purchased it, why are you bothering me? And being able to understand that sort of level I think is really the next step for most marketing out there, that even knowing where your best intent is most likely spent.

Sameer Patel: And you know Michael, I think the other interesting thing is: We always talk about, “The world is change and it’s a new world, and it’s a new consumer,” but there are many things that have not changed. Let’s be honest about that, right? There are things that continue, like when we talked about the conversion rates, two or three percent e-commerce conversion rates, this is a problem that every marketeer, and frankly every CEO and consumer brand has been waking up to for decades, right? The amount of money they plow into customer acquisition costs, to drive new customer acquisition, has only gone up. But the amount of focus and available technology, once they’ve acquired that customer, to get from that, from the point where you are now a customer to the first purchase. What is the actual work required to get you from first purchase to second purchase?

We all know, and I think you would attest to this, that as a consumer, forget all the gobbeldygook technology for a second. I would say, in my own buying pattern, if I buy from a given mobile e-commerce app for the third time, my mind starts to get training around certain categories. I associate that brand to certain categories. And I would not go to a search engine. If I’m looking at products within these two or three categories, I will see if this vendor actually has it. And that is something we think really, really deeply about. And I don’t think the retention part of marketing automation technology has advanced ever to a point like it is now, where you can begin to really, really say, “First point of first goal, get the customer to download the app; second goal, get them to make the first purchase; third goal, get them to make the second purchase.” And having that level of discipline, we’re now at a point where you can do that if you use machine learning-based technologies, right? So it’s going to change how we interact in the next decade. We’re just getting started.

Michael Krigsman: Now, what about the flip-side of this, which is the fact that you’re looking so closely at consumer data; and yes, they’re my digital tracks, and they’re not particularly secret, I’m going to these websites; but, when you start aggregating this kind of data, what about the privacy implications?

Andrew Eichenbaum: So, this is a question that comes up in every company that deals with marketing and AI. They say, “Well now that we can draw these correlations between all this data, what does it mean? Are we going to spoof our customers?” I can tell you numerous stories. And what’s really interesting is it’s actually based upon the older the age range, the more worried they are about security and privacy. Say their generic internet traffic. Now there are other places like medical, and banking, where people just don’t want to share. They’re extremely secretive. And, these are where things like personally identifiable information comes in, and making sure that nobody can see these things easily out on the web, or advertised to that specifically. But if you look at …

Heck, just look at social media. How much do people post, and they’re specifically sharing it with the world. Is it that much more than just viewing your … I don’t view my web history trail as any less personal than what I’m putting up there: pictures of my kids, conversations that might be going on… People have become accustomed to a certain amount of sharing, and they understand that that sharing will be used to profile them by multiple people. What the smart companies are doing is they are saying, “Yes, we’re going to do this, and we’re going to make it better for them.” You can see this on Google, on Facebook, it’s like, “Is this ad valid to you? Do you want us to advertise to this?” They are up there saying, “We’re going to profile you based upon your activity. What pieces do you do not, and do want to be marketed to? How do you want us to use this information?”

Michael Krigsman: So basically, opt-in, essentially.

Sameer Patel: I mean, yeah. You’re leaving certain digital breadcrumbs proactively, openly, right? This is no more than, you know, what you have agreed to leave open. Now usually, also understand in our context, because we sit on the retention side, you know. There is an association with a brand already, you have the app, we’re helping you just go through a more meaningful purchase with that particular brand which you’ve always had business with. There’s no denying that this stuff can be used in ways that are not kosher, right? It really boils down to, you know, you having the faith in the brand and the customer success teams, and the people you work with day-in and day-out to … because again, I think every brand knows they’re recovering from brand [...] that’s far more expensive than the initiative use, right? So, stay within the lines of what the consumer has agreed to expose, and you’re okay.

Michael Krigsman: So, maybe this is an important point, that essentially what you’re saying is smart brands will engage in behaviors that will engender trust among consumers. And you started to talk about this, but maybe give us some advice to brands for what are behaviors that will engender trust? How do you engender brand confidence and trust?

Andrew Eichenbaum: So, one of the easiest ways that data science has been viewed as important is explaining why we do what we do. Giving the user, if they ask, the reasons why we’re marketing this to you. And you see this on Netflix, if you go on their streaming. If you go down lower and lower in the recommendations, they say “movies because you watch this-and-that,” films based upon this genre that you seem to like, based upon your viewing history. Just give a brief explanation which seems plausible and at the root of the reason, or the way you were targeting them, and people find it much easier to ingest, and understand and trust those [recommendation].

Sameer Patel: I want to come at this from a different side as well. This is an indirect way, but I truly believe that there is going to be more and more of this over the next coming years. One of the things that is least talked about in this concept of trust between a brand and a consumer. So one is actually the things that we talked about, there’s a level of “Will you screw me over or not?” There is definitely that side. But there’s another discussion too, which is I start to have more trust and faith and respect for a brand, as a consumer, when I see that they have taken the extra effort to understand that. You know, you’re going to … Do you think Amazon breaks your trust when you see five things that they suggest based on your interest? No, I don’t think you - this is again, shrinking that distance between what an offer is, what valuable information is. And I think as we start to do that in a meaningful, respectful way, I’m not going on and telling Michael Krigsman’s friends what Michael’s interests are. I’m sticking to Michael, and only Michael gets to benefit from that. You start to build a mutually respectful relationship with a brand. And I think that implicitly starts to go a long way.

The problem has been the opposite, which is, brands have had to try to get very cute with the consumer because of really crappy, excuse my French, the really, really bad, shitty marketing technology. And that time is done. The consumer’s done, the state of the technology has changed over like “Clap, clap! Wake up! We’re done with all that!” It’s time to move on, right?  And I truly think that better relationship with every single consumer by putting meaningful stuff in front of them, and not screw them over with the data that they give you. That’s important, just to stay there.

Michael Krigsman: So we’ve got about three minutes left. And, how about for our closing, if each one of you just offer your continuing thoughts on what must a brand do to, in the immortal words of Sameer Patel, not screw over their consumers? Andrew, you want to start with that one?

Andrew Eichenbaum: There are so many ways you can screw over your consumer.

Michael Krigsman: … Or to do the right thing. What should brands do, to do the right thing? That’s another way of saying it.

Andrew Eichenbaum: It’s not as much doing the right thing. Marketers want to increase their market share, and it’s inherent in the system. The real piece is not to go above and beyond to the point where people become distrustful of you. It’s really just building up what Sameer said. You can easily go off, given your consumer information, and go to a third party, spend seventy five cents a person, and literally get their full history in there: their employment history, where they’ve lived, so on and so forth. And you can use that and it becomes extremely powerful. But if you start doing that, and people realize you do that, they’re going to go nuts. You’re going to make the front page of the news, and there goes your profits for the next wherever.

Michael Krigsman: And we hear about companies that make the front page of the news because they do that kind of stuff.

Andrew Eichenbaum: But if you keep it at the level that you’re interacting with my site, you’re buying stuff. You are doing this and that, and from that, we are moving you forward, you’re at a much safer space. Now, there are places like Target, which sometimes overreach a little; if somebody gets a congratulations on being pregnant, you might say, “What?” [Laughter] Maybe because they haven’t told anybody yet. But the interesting thing is, you hear more of those stories than the opposite.

Michael Krigsman: So Sameer, you have the last word. We have one minute left.

Sameer Patel: Yeah, look. I think it’s really simple. I think we are at a really critical, and an amazing time in terms of revitalizing and rethinking every piece of the enterprise technology stack and B2C marketing automations, and all different things. Marketers, for the first time, have the ability to start thinking about B2C marketing automation as workflow automation technology, and truly put the consumer in the center of the entire experience process, and figure all the business processes that actually emanate from it. How do I want to engage with an audience of one, Michael verus Andrew versus Sameer, and what are the kinds of campaigns and things I need to be running that have to follow that? This is the opposite of how ten year old technology was designed. That was designed around scaling and batching and blasting stuff out there, consumers are way smarter than that. Unfortunately, or fortunately for you, Netflix and Amazon and AirBnB and all the amazing digital brands have risen.

You know, just the tolerance level of short-e batch-and-blast technology is just not going to cut it anymore. A very simple way to consider this is to say, “Everything I do on a day-to-day basis: Is the consumer at the center of the process, or is the convenience of my marketing automation just at the center of the process, and you will immediately be able to figure out where the gaps are in the technology.”

Michael Krigsman: Okay. What a great summary in the end: Is the consumer at the center of our process, and our life as a seller, as a marketer, or are we doing things because…

Sameer Patel: For our own convenience, right? You know …

Michael Krigsman:

For our convenience.

Sameer Patel: It’s your convenience. It has to be about the consumer, and everything has to surround that.

Michael Krigsman: And on that note, this has been a very fast conversation. We’ve been talking with Sameer Patel, who is the CEO of Kahuna, and Andrew Eichenbaum, who is the lead data scientist at Kahuna Software. I am Michael Krigsman. You have been watching Episode #209 of CXOTalk, talking about the role of AI, artificial intelligence in marketing. Next week, there’s no show because of the New Year’s holiday, and everybody, thank you so much for watching. And Sameer Patel and Andrew Eichenbaum, thank you so much.

Sameer Patel: Thank you for having us.

Andrew Eichenbaum: Thank you.

Michael Krigsman: Everybody, have a great week. Bye-bye.

Advice for Digital Transformation, with SVP of Ziff Davis

  • Episode: 208
  • |
  • Topic: Digital Business
Anurag Harsh, SVP and Founding Executive, Ziff Davis
Anurag Harsh
Chief Marketing Officer
IPsoft
Michael Krigsman, Founder, CXOTalk
Michael Krigsman
Industry Analyst
CXOTALK

Digital transformation involves all parts of a company, from sales and marketing to operations, supply chain, and talent. On this episode, a seasoned leader and author shares practical advice for undertaking a program of digital transformation. Our guest is Anurag Harsh, Senior Vice President and Founding Executive at Ziff Davis.

Anurag Harsh is an entrepreneur, a company executive, a digital and management guru, a blogger, published author of several books, business columnist for leading US publications, an investor, and a classical musician who has performed two sold out solo concerts at New York’s Carnegie Hall. His business blog has attracted hundreds of thousands of readers. His Carnegie Hall concert is one of the fastest growing and most watched world music videos online, with millions of views. Over his 20 year career as a business leader he has led the digital transformation of several companies with programs that have deepened customer engagement, introduced new business models, digitized operational processes, enabled greater employee collaboration, and reimagined the way we work.  His most recent book is Going Digital: Harnessing the Power of Digital Innovation.

Transcript

Michael Krigsman: Welcome to Episode #208 of CXOTalk. CXOTalk brings together the most interesting, innovative executives [and] business leaders in the world, talking about leadership, technology, [and] disruption. I’m Michael Krigsman, industry analyst and host of CXOTalk, and you know, I have a great job doing this, talking with these amazing folks. And today, we are speaking with Anurag Harsh, who is the Senior Vice President and Founding Executive of Ziff Davis. And that hardly scratches the surface on the things that he has done. He has a music video, a performance from Carnegie Hall, that is one of the most viewed music videos online anyplace, with millions of millions of views. He’s written two books, he’s one of the top LinkedIn technology bloggers, so really an extraordinary person. Anurag Harsh, how are you, and thanks for joining us today.

Anurag Harsh: Hi Michael, hello everybody. Thank you for the opportunity! Excited to share my thoughts.

Michael Krigsman: And you were even a radio announcer for the BBC earlier in your career.

Anurag Harsh: Yeah, that was in a past life. I was a newsreader and a broadcast journalist. I produced programs in science and development for the BBC World Service when I was back in college, in the University of Sheffield in England. And I would take a four-hour bus down to London, and then broadcast a six hour shift. And it was fascinating and I did that for many years.

Michael Krigsman: Well, you’ve done amazing things. So, tell us about Ziff Davis, and tell us about your role. What do you do?

Anurag Harsh: Well, Ziff Davis is one of the world’s largest digital media companies. We operate properties in the technology, gaming, entertainment, health, and men’s lifestyle verticals with iconic brands such as PC Mag, IGN, Everyday Health, What to Expect, MedPage Today, AskMen, and Speedtest. The Wall Street Journal describes us as, and I quote, “The epitome of modern innovative digital publishing.” Each month, our Ziff Sites lead to a third of US internet audiences, and 110 million worldwide consumers in over 100 countries, over 50 international editions, in over 24 languages.

I joined Ziff about 7 years ago ─ it’s almost seven years; and as it’s first and founding hire, and the first executive when our CEO, Vivek Shah, took over the company. Being involved in its complete digital transformation all the way from when it was a small, privately-held media company to now, when it’s a thriving nearly $4 billion market cap. It’s an all public digital enterprise with 1,400+ employees. We are part of j2 Global, and we trade under the stock symbol JCOM. I’ve been involved in the last fix of the company, including internal- and external-facing web, digital assets, and focused on harmonizing efforts across all sales channels, social media, internet, intranet. We’ve done over 20 M&A transactions. I’ve been involved in strategy and partnerships, and new business ventures, sales, marketing, revenue generation, and our actual expansion. So it’s really all the way from the beginning to where the company is right now, from sort of technically Employee #1 to, you know, we might be 1,600 people. I don’t know, but the official number is 1,400 employees.

Michael Krigsman: And, you’ve written a couple books, and your most recent book is, and I’ll hold this so you can see. Your most recent book is “Going Digital,” which is all about digital transformation. It’s a really good book, and please share with us some of the key points. Why did you write the book, and what are some of the key themes?

Anurag Harsh: Well look, we live in a crucial period in time. The rate of technological innovation has, you know, outpaced our ability to see into the future with a reliable degree of accuracy. Yes, we’re able to cope with the vagaries of the world, yet no one can precisely say where we’re going to be five or ten years from now. The 21st century and its

Michael Krigsman: Welcome to Episode #208 of CXOTalk. CXOTalk brings together the most interesting, innovative executives [and] business leaders in the world, talking about leadership, technology, [and] disruption. I’m Michael Krigsman, industry analyst and host of CXOTalk, and you know, I have a great job doing this, talking with these amazing folks. And today, we are speaking with Anurag Harsh, who is the Senior Vice President and Founding Executive of Ziff Davis. And that hardly scratches the surface on the things that he has done. He has a music video, a performance from Carnegie Hall, that is one of the most viewed music videos online anyplace, with millions of millions of views. He’s written two books, he’s one of the top LinkedIn technology bloggers, so really an extraordinary person. Anurag Harsh, how are you, and thanks for joining us today.

Anurag Harsh: Hi Michael, hello everybody. Thank you for the opportunity! Excited to share my thoughts.

Michael Krigsman: And you were even a radio announcer for the BBC earlier in your career.

Anurag Harsh: Yeah, that was in a past life. I was a newsreader and a broadcast journalist. I produced programs in science and development for the BBC World Service when I was back in college, in the University of Sheffield in England. And I would take a four-hour bus down to London, and then broadcast a six hour shift. And it was fascinating and I did that for many years.

Michael Krigsman: Well, you’ve done amazing things. So, tell us about Ziff Davis, and tell us about your role. What do you do?

Anurag Harsh: Well, Ziff Davis is one of the world’s largest digital media companies. We operate properties in the technology, gaming, entertainment, health, and men’s lifestyle verticals with iconic brands such as PC Mag, IGN, Everyday Health, What to Expect, MedPage Today, AskMen, and Speedtest. The Wall Street Journal describes us as, and I quote, “The epitome of modern innovative digital publishing.” Each month, our Ziff Sites lead to a third of US internet audiences, and 110 million worldwide consumers in over 100 countries, over 50 international editions, in over 24 languages.

I joined Ziff about 7 years ago ─ it’s almost seven years; and as it’s first and founding hire, and the first executive when our CEO, Vivek Shah, took over the company. Being involved in its complete digital transformation all the way from when it was a small, privately-held media company to now, when it’s a thriving nearly $4 billion market cap. It’s an all public digital enterprise with 1,400+ employees. We are part of j2 Global, and we trade under the stock symbol JCOM. I’ve been involved in the last fix of the company, including internal- and external-facing web, digital assets, and focused on harmonizing efforts across all sales channels, social media, internet, intranet. We’ve done over 20 M&A transactions. I’ve been involved in strategy and partnerships, and new business ventures, sales, marketing, revenue generation, and our actual expansion. So it’s really all the way from the beginning to where the company is right now, from sort of technically Employee #1 to, you know, we might be 1,600 people. I don’t know, but the official number is 1,400 employees.

Michael Krigsman: And, you’ve written a couple books, and your most recent book is, and I’ll hold this so you can see. Your most recent book is “Going Digital,” which is all about digital transformation. It’s a really good book, and please share with us some of the key points. Why did you write the book, and what are some of the key themes?

Anurag Harsh: Well look, we live in a crucial period in time. The rate of technological innovation has, you know, outpaced our ability to see into the future with a reliable degree of accuracy. Yes, we’re able to cope with the vagaries of the world, yet no one can precisely say where we’re going to be five or ten years from now. The 21st century and its people are marked by great change, staggering accomplishment, and unprecedented uncertainty, right? So for all this, we’ve managed to change the course of humanity in ways our ancestors never dreamed. We’ve prolonged human life well beyond what was typical. We’ve engineered machinery and digital technology that reduced the need for human involvement, putting more time and energy at our disposal to pursue happiness inside and outside of work. We’ve deconstructed command and control corporate hierarchy, and created this concept that we now know as “work-life balance” ─ an antidote to the pernicious absorption customary of the workplace.

So, perhaps in equal measure, we’ve opened gaping divides of global proportions, you know? This is a natural fluctuation in human affairs. I don’t think that there’s ever been, and maybe there will never be, a perfect society. We’re flawed in all-too-human ways, and yet, in all those very flaws, when looked at dispassionately and honestly, that can reveal the doorways to a better world for ourselves.

So, when you think about it, the last fifteen or sixteen years, more than half all the Fortune 500 companies have either become insolvent, been acquired by another company, or stopped doing business altogether. And if you just look at last year, 50% of Fortune 500 companies declared a loss. So the stride of transformation has become a revolution. Rivalries have deepened, and business models have been dislocated. So the only constant is the growing severity of digital disruption. That’s why I wrote this book. You know, aggregated many years of experience on the subject of digital, and digitalization, and digitization, and transformation at the corporate, individual, and global level.

So, the topic of digitalization: it’s an incomplete one. To speak on the effects of digitalization will inevitably leave questions [un]answered, and perspectives unrecognized. So, what I did in the book, that you’ve been so kind to show to the audiences here, is to cover these topics from as many perspectives as possible as they relate to the subjects of business, economics - and very important - psychology. My goal with the book was to present the leader with a comprehensive understanding of the myriad ways that digital technology, and the mentality it’s engendered, has changed the course of human history ─ changed the way that people view each other  ─ and has affected business practices. And, you know, provided practical measures for people and business owners alike to create a closer innovation that acknowledges individual differences; and then seeks to harness that, while contextualizing the culture in a broader discourse about the government’s role in digital divides that we see opening with the people today.

So, when you look over the table of contents of this book, and it’s there on Amazon, you can decide where you want to start, based on your interests. You don’t have to read it cover-to-cover. After all, customizability is a hallmark of digitalization, so when a company or a person has truly crafted a digital journey, it matters not where on the path you enter, you will always see repeated, endlessly, every element of the journey; and that really is the guiding spirit of what I think is the next frontier of digital thinking. And that’s what the book is all about.

Michael Krigsman: Anurag, you mentioned two things that I find particularly intriguing. Number one is you spoke about “the growing severity of digital transformation,” and then you talk about the psychological dimension of this. And I find that fascinating because, as I have spoken with many leaders on this show, the issue of culture is a very, maybe the strongest common denominator when people are talking about digital transformation. So when you talk about psychology, maybe you can elaborate on that for us please.

Anurag Harsh: Well, culture is very important. Look, there’s two aspects of culture when it comes to culture: the mindset and the method. And, let me qualify that a little bit. You know, as I was writing my book, reflecting on my years digitally transforming some of the companies I’ve worked for including Ziff, a peculiar allegory occurred to me and some of you may know it. I’m not a Buddhist, but I’m intrigued by world religions, and in Buddhism there is this belief that all of reality is as one. Everything is anything and nothing. Buddhist philosophers will sometimes illustrate this point with the allegory of what they call as “Indra’s net.” As it goes, the universe is a net held together by radiant, bejeweled knots - just follow my thought here. It’s kind of interesting and I think there’s a learning from this. The universe is a net, which is held together by radiant, bejeweled knots. At each knot in Indra’s net, there is a multifaceted reflective gem. You pick any jewel in the net, and then you stare into it; and what you will see is a reflection of all the other jewels in the net. You would see the universe over and over again - it’s sort of like a mirror. So, the edicts of digital transformation are not unlike Indra’s net.

The pervading notion is that no matter where in the business, or in the supply chain you look, you know, you should be able to bring everything about the digital journey - the digital journey being the aggregate of the operational, strategic elements in your digital process. So, that includes your architecture, infrastructure, your management technology, your logistics, your planning, your governance, and everything else. So, the jewels in our net are data. And, the world is all the technology you use to connect. So, you know, at this moment, data is all about information. It’s the blueprint of the physical world, the interactivities, and the lines of causality.

So you know, that’s the culture we’re trying to create, which is the culture that unifies, technologically as well as from a mindset perspective, everything in the network of this invariable communication that can automate, interpret, predict, store, self-adjust, increase the agility, increase innovation and foster collaboration from end-to-end. Right? Now go back to the allegory of Indra’s net. When a company is fully digital, and the culture is fully digital, every element is networked such that a single glimpse at one portion reveals the whole. So, at an abstract level, it’s relatively simple to understand, but in practice, it’s a very different story. And we’ve tried to do that a little bit at Ziff here.

And so, you know, many digital transformation experts I’ve spoken to, they leave a lot to be desired. They don’t provide concrete, implementable solutions from … So for me, digital transformation is really about getting all of those pieces together from a cultural perspective ─ to get the employees and the customers, who are really the building blocks, to digital strategy.

Michael Krigsman: So, the culture and the psychological dimension of connecting all the pieces of the company together, through data, through shared experience … On one level, it’s easy to talk about, but as you said, very difficult to do in practice. And so, what are some of the practical steps that an organization can take, in order to execute a program or initiative of digital transformation?

Anurag Harsh: Well that’s a fantastic question, and let me try to think about this a little bit. Look, companies are spending a lot of money, and why? Because of disruption, there’s despondency, and that’s compelling companies to want these digital initiatives. And they are investing a lot of money, which mostly results in disappointment due to the absence of concrete, components strategy, right? As the markets are shifting downward, many companies try to counter the spiral by initiating these frantic investments and digital initiatives. Some of them are hiring Chief Digital Officers and some of them are looking at their CIOs and CMOs to counter some of these disruptive effects. From my perspective, there are five things, strategically speaking, at the very high level, that companies need to think about, and let me tell you what they are. They’re these buzzwords I’ve created. Well we’ve sort of followed them a little bit here at Ziff, and we seem to be hitting some success with it. The first one is called “the structural swivel.” The second one is “the inverse acquisition.” The third is “the offshoot” and I’ll explain what these are. The fourth is “the coattail rider,” and the fifth is “oiling the hinges.”

So, let me start with the first one, “the structural swivel.” So, when you think about the role of speed, it’s crucial for digital disruption, right? And companies have these legacies. If you talk to any CTO, or CIO, they have all these legacy systems and these techniques that can impede my ability to execute. So, by altering the company’s configuration to spotlight digital initiatives, you know, executives can swiftly escalate the speed of transformation. So that’s a tactic that necessitates earmarking funds, and human resources to digital initiatives, and placing digital executives in command of existing business processes. I’ll give you an example. I can’t give you specific names, for confidentiality reasons, but a lot of these over the course of writing my book, and you know, some of our clients.

This is a bank; it’s a local bank that started to actively swivel. Remember, this is the structural swivel; that’s what we’re talking about here. It swiveled out of a conventional High-Street, branch-driven model by venturing outside by recruiting a CDO (Chief Digital Officer). In fact, the bank empowered this guy with complete corporate supervision, comprising all the High Street branches that were still the lion’s share of the bank’s income. All product, tech, sales outlets, and marketing units started reporting to the new CDO. To push for digital transformation, each regional division also hired a committed CDO at the same level as the local bank president. These changes were then intended to assist the bank in obviously speedening and hastening its conversion to a soup-to-nuts digital enterprise and organizing a pure digital experience across all the business conduits, which echoes everything in consumer and market development. That’s what I call a structural swivel.

The second component of digital transformation is what I call “the inverse acquisition,” when you think about it strategically. Strategically, if you’re not in the right place, tactically you can’t implement it. What is the inverse acquisition? Well, there are a lot of businesses that have unearthed what I call “quick wins” ─ you know, quick triumphs ─ by placing boundaries around the digital products so, they can function autonomously and uninhibited by traditional processes. Just put them in a corner somewhere. It’s like, “Off you guys go!” However, the moment the digital project demonstrates its usefulness, you know, shouldn’t subsequent tasks follow suit? Persevering or preserving the project’s autonomy restricts its influence on other businesses. Furthermore, an individualized gig, as I call it, is not hard for, you know, the traditional business to disregard. So, one possibility is to absorb the traditional businesses into the new digital unit, spreading the transformation business-wide, and then compelling the rest of the company to abandon its archaic approaches. This is what I call “the inverse acquisition. “

This tactic is hard work. It comprises the comprehensive moving and resettlement of technology manifestos, company structures and processes, and ultimately consumers from the traditional business to the new model. Right? Cautious ranking in faith [?] methodology that would guarantee that the company doesn’t collapse into the disorder [while] doing the changeover. I’ll give you an example. You know, this is a British retail store I can name this time; it’s called John Lewis. It acquired a very long time ago buy.com.uk in 2001. And it inherited vital technology and talent that it used to quickly erect its only e-commerce business in the year shortly after. John Lewis commenced a gigantic undertaking a few years later to reconstruct its web and e-commerce framework, which involved assimilating over 30 prevailing tech systems. And then they had the e-commerce site which lands…which launches like in 2013, and it’s connected with the retailer, soup-to-nuts, supply chain, and the delivery conduits, and the physical stores. Here’s the thing. The 10-year long dedicated effort increased its online sales by close to 30%. So, inverse acquisition. That works.

The third is what I call “the offshoot.” And there are five of them. And I’ll try to be as quick as possible to explain these digital mindsets, and the companies. Depending on what kind of companies they are, they can sort of decide.

The offshoot is … It’s unrealistic to always expect to be absorbing a traditional business into a new digital operation, especially if the digital business is not yet sufficiently developed to absorb a larger unit, or if it focuses on too dissimilar a fragment of the value chain. So, in these cases, what the businesses can do is they can discover that an optimal way to grow those ventures is to segment the separate fragments into distinct businesses that can then develop outside the principal trade or business. There’s an example here as well. It’s BBVA Compass, which is a Spanish bank. It’s safe to talk about non-US companies in this context. They had a software development division called “Globalnet” for over a decade, and they used that to fuel their technology initiatives. A couple years back, Globalnet, this little software development division, transformed into a BEEVA, which is an offshoot for creating and marketing business web services.

Now, although BEEVA powered the base technology for BBBA ─ the Spanish bank’s transition into digital banking ─ the bank’s executives realized the software division’s innate potential. So as an independent services business, BEEVA helps other banks do what BBBA has done using BEEVA’s groundbreaking cloud technology platform. So in this instance, a structural swivel or inverse acquisition we just talked about would not have worked. Why? Because the bank was ultimately a financial services company, and its software division BEEVA was a web services unit, with functionality that was different from the bank’s core business. So, that’s what I call “the offshoot.”

Michael Krigsman: Okay.

Anurag Harsh: And finally ….

Michael Krigsman: I don’t want to interrupt, but we actually have a question from Twitter, and this one’s more prosaic but everybody’s asking this question. This is from Arsalan Khan, and he’s wondering where does the CIO fit into all this, because we think about digital transformation as involving technology, but as you’re clearly demonstrating, the technology is … it’s a piece, but it’s not the biggest piece. So, address the technology aspect; but where does the CIO fit?

Anurag Harsh: Well, the CIO fits in the middle of all of this, right? But the CIO is responsible for a lot of the traditional legacy systems and technologies, and to be able to maintain the current, sort of, modus operandi ─ the order of business within the company. A lot companies like Fortune 500 and other companies, and larger companies, are actually going through transformations whilst maintaining their KPIs and their stock price and making sure … because the Street is very unforgiving. So if you actually start to slip your stock price, it’s really going to tank. So, the CIO’s job is to make sure that both sides of the equation are well-balanced. So the CIO sits right in the middle of this, because obviously technology is paramount and it’s sort of at the center of this. But, at the same time, it’s also about thinking strategically outside of the confines of the CIO’s office, or the CMO’s office, or even the CEO’s office. This is about …. That’s why oftentimes you have Chief Digital Officers, which are thinking very strategically about not necessarily technology, or information, or data, but they’re thinking, “Well, how the hell do I just completely change the way that we reach consumers, and change the way that the company is structured so that there is a coherent transformative strategy that the customer sees, and interacts with the company in a coherent and concise manner?” So, the CIO is one aspect of everything, but I think that this is a kind of process ─ transformation in digital ─ that requires skills from a variety of different parts of the organization: operations, information, data, executive strategy as well as of course marketing.

Michael Krigsman: So, the key part of this, then, is the fact that the digital transformation is not just about marketing. We tend to think, or often people talk about digital transformation as essentially a marketing activity, but it’s not at all.

Anurag Harsh: Doesn’t have to be. I mean, I wouldn’t say it’s not at all. Obviously, digital sits within marketing oftentimes, but, you know, digital is way beyond marketing. It’s not just about likes and social media, you know? There’s an old Beatles song, “Money can’t buy you love,” and I would like to add onto that, “It don’t even buy you a Like.” And that’s what marketing has become.

Michael Krigsman: I love that, by the way.

Anurag Harsh: Yeah, money don’t buy you love. You know, it don’t even buy you a Like. That, by the way, is “doesn’t;” it’s incorrect grammar but I’m going by the actual song.

Michael Krigsman: But what about Facebook, you know? You can buy Likes on Facebook.

Anurag Harsh: I’ll give you an example. Customers are not what they used to be, right? The internet has given them wings, and you know, given us the power to express ourselves. Marketing is not … Long gone are the days of … Look, we run one of the largest, you know, we’re one of the largest publishers in technology, and health, and men’s lifestyle. Advertising and licensing are huge, huge aspects of the business, right? We stay away from gimmicks, from clever phrasing and seduction, right? The well of false enchantment can run dry. So, consumers are staring down now at attempts at persuasion and flashy advertising because they expect authenticity from corporations and individuals alike, right? The shift in consumer expectation, it comes on the back of what? It comes on the back of digital revolution, right? And unilateral skepticism towards companies and their products. So as consumer psychology changes, then digital and marketing is entering a new era where human needs, the values, and connections are defining success and failure, right? So, it’s a call to action to marketers and advertising executives, and departments who typically have had digital functions to think about how do they change the perspective towards consumers?

You know, companies cannot see consumers as gullible moneybags, or as conquests, right? They have to see consumers as community members, as human beings who crave trust. You see the theme here? We’re talking about technology and digital, but what I’m getting at is the ability. I call it the “relationship era.”

Michael Krigsman: This is great! This is…

Anurag Harsh: Yeah. This is … When I started out, I must have spoken to over 100 companies in the course of writing this book, and it fundamentally came down to … Consumers crave trust; predictability; transparency; respect. And so, this is the basis [garbled word] of the relationship era. In this era, the company’s corporate value when it comes to digital: “Why do you want to transform digitally?’ Your corporate value must resonate at every level [of] that infrastructure. It has to emanate outwards to the company’s employees, the customers, the suppliers, the stakeholders, you know, neighbors, and your relationship towards Earth! So, merely projecting an image is akin to falsity. The companies have to genuinely and steadfastly practice what they preach. So, the ascendant paradigm in marketing and digital is completely natural. It’s almost expected, you know? You look at the history of marketing. It becomes patently clear why this new era with digital came about, right? And, there’s lots of uber-trends in terms of how marketing has shifted, and why digital doesn’t necessarily have to just fit within marketing, but also spread into operations and supply chain, [and} obviously in technology itself.

So, there’s a reason for that: The first reason is that the unsustainability of mass media, and advertising both economically and socially. Look, the cost of advertising continues to increase. Why? Technology allows marketers to reach highly targeted groups of people, and yet consumers are conspicuously opposed to advertisements. Right? They’re perceived as an encumbrance and in some cases, frankly, they’re perceived as invasive. Look at the ad blocking.

So, the second thing is that the internet has dissipated the curtain of shadows that once hid corporate activity. No longer are corporations impregnable fortresses. What remains of corporations is transparent. And it must be, if companies are to win the confidence of their customer bases. You know, these are the underlying psychology and traits that digital has to harness. Then you have the rise of social media channels, right? These are news outlets. People are sharing current events. Look at our President-Elect; the guy’s tweeting all the time. So, people are sharing current events as they happen as opposed to retrospectively. Daily events are like conversations.

Finally, the uber-trend is about the overturn of the morality of consumerism. What do I mean by that? Well, the public cares not only about the cost and quality of the products and services. Look at the Millennials. I mean, people also care about the values, and the conduct of the providers, right? Trust, reliability, ethics often supersede quality and affordability. And so, you have to take all of these things into account when you devise and place your digital department: Should we sit in the marketing? Should we sit under operations? Or should we think strategically, so that the company has a profoundly altered the status quo ─ the strategy and the very sociology of marketing? So the question, really, before us and everybody out there is this: what can we do to adapt while preserving our bottom line, right? And so, you’ve got to figure out some kind of a middle way, and that’s really where digital comes in and where it really needs to be sitting. You’ve got to think about it as a consumer era, you know? An era where it’s relationships and it’s change and values and how do you build that story ─ you know, do things. And that’s what it’s all about.

I mean, let me give you an example. I’m fascinated by this, okay? I did this last week. Type this in Google. Type “I love Apple” into your search bar and you don’t need to do it right now, but if you type “I love Apple” in your search bar, you’re going to get 400 million hits in about 42 seconds, right? Type “I love Starbucks” in your search bar. You’re going to get like 36-37 million hits, an order of magnitude less. And that’s in about just under a minute.

So, where am I going with this? Some companies spend billions of dollars every year, right. They’re getting the attention from customers and they don’t boast nearly as many hits, likes, or love. Companies like Exxon, right? Rex Tillerson is in the news. Citibank, Dow Chemical, I mean…

Michael Krigsman: So what’s the key?

Anurag Harsh: You do the same thing with these companies, and it’ll tell you exactly what I told you, which is money don’t buy you love. It don’t even buy you Likes. So, type “I love Citibank,” and it’s not a potshot at any of these companies …

Michael Krigsman: How about I love Comcast?

Anurag Harsh: It’s a point I’m trying to make. You’re going to get like 12 million hits in 30 seconds, you know? A lot of these companies don’t fare any better. Where am I going with this? And they’re spending about $1 billion, over $2 billion …

Michael Krigsman: So what’s the key? How does a company that is in business, that has operations, that maybe has had an adversarial relationship with consumers … I mean use the term “gullible moneybags.” How can a traditional company, a traditional mindset make this change?

Anurag Harsh: There’s three realities of today’s market. People talk providence and transparency, alright? If you’re in marketing, and you don’t understand this, then this is something that … this is the digital speak in terms of marketing. There are billions of people online, right? Millions of them are talking about brands, experiences, and posting reviews, and they’re reading consumer feedback. So, when customers like your brand, trust me, they will express affection for it, right? People will care about you. That’s how it works. Look at the Apple Fan Club, or look at the Beyhive, after Beyoncé’s whole marketing empire. Right?

The second is providence, you know? These are relationships. And what people say about you online does, in fact, dictate your success. You might not want to accept it, but that doesn’t make it untrue.

The third is transparency. This is both an edict and an admonishment, you know? Be transparent, and should be. What happens in the boardroom is no longer a secret and any discussions can be had, and they’ll probably find a way to a public forum. So it’s not business as usual, and I would rather call it “business unusual.” So, what can companies do to understand these things? The fact that people talk, the fact that there’s relationships that you might not want to accept for this providence, the fact that this transparency matters, you know? You have to figure out digital strategies that take these into account and stitch them together in a way that can really establish that permanent relationship. The company needs to build with its customers, you know, especially the ones that are detached from it. You’ve got to lubricate the relationship.

Michael Krigsman: But how? Because the reason I ask is because what you’re saying is just so much in tune with what is taking place in the market, but companies very often, they struggle with this, they want to do it, they’ll spend millions and millions of dollars trying to do this, trying to buy these “likes” and this relationship, and it doesn’t work. So how do you do it?

Anurag Harsh: In many ways. Look, relationships are built on social media nowadays, right? I mean, always be connected. It’s a boon. It’s a curse and consumers have perpetual access. And so, there’s no relationship we can take for granted. So, consumers are connected to their friends, their families, coworkers, everyone else. So, what companies need to do is understand how social media works, especially Facebook actually, and use them in a way that can establish these relationships with these customers. Understand the observations, the ideas, their concerns, their hopes, their dreams, their fears, and their opportunities and their failures. And connect with them in a way that can establish the genuine relationship.

You know a consumer complains about a product or a company somewhere on the internet. There are bots available now where you can actually go and harness that conversation and engage with that customer. Companies don’t do that! And if you were to do that, and just channel the customer’s complaint, and address it, you might have the customer for a very long time. I wouldn’t say for life, but for a very long time. And so, you know, you don’t have to spend billions of dollars in marketing in order to do that. So, you have to establish trust. And, it’s important that you have to humanize the institution. Digital is about humanizing your institution. It’s about humanizing the corporation, right? Making it predictable, reliable, you know, honest. Loyal, respect, and shared values and empathy ─ that’s what this is all about. It’s about establishing credibility.

And then you’re asking me, “Well, how do I establish credibility? How do I establish congruency and care?” Well, you know, these are not very hard things to do. It’s just that you need to use social media channels, and you need to use technology to figure out (and marketing) to figure out how to create the credibility. You know, the presumption of reliability and dependence must take primacy. You know, and care, which is about caring for your customer ─ you know, engaging with your customers. Their lives matter! It’s about constructing your business around their needs and addressing them happily, you know?

And then congruence, which is, consumers are consistently reading into the actions of corporations, you know? You’re trying to define true motivations ─ the beliefs, values, and purposes. That’s what this is about.

So, how do you create this? You use technologies and social media, and the tools that are available ─ apps and whatnot ─ in order to create a brand, which is relationship-driven, and which is all-encompassing. That is the only way that Fortune 500 companies, and even smaller companies which are trying to disrupt them, can be around, because you know … Look, Satya Nadella, who was there [with the] President-Elect on Wednesday; he wrote a blog on LinkedIn a couple of months ago that basically said that if you lose 30% of your customers, you’re done. And, 50% of the Fortune 500 companies are done, you know, because they didn’t see it coming. You had a new kid on the block that just came and swept the entire industry away. This is happening more and more.

Back in the day, we had the industrial revolution, which was 20 years, 25 years, and you had the textile revolution. Now you have the digital revolution, which is 5-7 years. So, it’s evolving. It’s changing. It’s fast. It’s in your face. People are there; they’re always connected. How do you actually do it? Well you get in front of them, and you basically, you’re transparent. And, you’ve got to live your life in front of your consumer, and you can’t have the shadow of this veil in the back. And you’ve got to establish this relationship, and once you have that circle of trust, it’s about establishing that. Once you have that circle of trust, that is what digital is about. It’s about establishing a circle of trust, and money will flow. Everything else flows. And so, that’s how you’ve got to look at it.

Michael Krigsman: So it begins with the strong intention to do the right thing. But, we have only about five minutes left, and there’s something else that I wanted to [ask]. This conversation is very important, we could go on for another hour, but we’ve got just a few minutes left, and there’s one other thing that I wanted to talk with you about, which is, and you have to explain this: You are in the star of one of the most highly-viewed music videos of all time. It’s gotten millions and millions of views from a concert you recorded at Carnegie Hall. So, very briefly, tell us about that and are there leadership lessons that can be learned from the musical experience?

Anurag Harsh: Well, I’m going to answer this question using the form of music that I have personally known, and this is Indian classical music, the music of North India ─ the classical music of North India. It’s also called Hindustani music. By the way, this is not the … You’ve been very kind, Michael, this is not the most-watched video of all time. In the genre of world music, this is among the most watched. It’s got about 2.5 million views over the last eight months, so …

Michael Krigsman: I happen to love world music, and I love Indian music, so that’s my frame of reference, and millions of views for that kind of music is pretty darn extraordinary.

Anurag Harsh: Yeah. Normally the template is a few thousand over the course of years. Look, let me start by saying what Indian classical music is, and how my … And then I’ll give you my sense of leadership and management.

Michael Krigsman: Okay, we’ve only got about three minutes. [Laughter]

Anurag Harsh: Okay, okay. I’m going to be very, very quick. Leadership is about the ability to change the central core from which an organization functions, right? Efficient leaders, they redeploy the make up of shared focus. So, you’re altering personal space where individuals and organization center on the ecosystem in themselves. So, there’s three things that leadership comprises: feeling, enthusing, and inventing, right? You’re exposing oneself to the outer ecosystem. You’re embracing the world within, and you’re nurturing and developing potential into existence.

So, you know what’s interesting when I performed at Carnegie Hall is it’s about a shared system of performance that in many ways can be equated with building and playing a musical instrument. Leadership. Three things need to happen for a musical instrument to create its best music: the frame of consonance; the motivation of the music; and lastly, you’ve got to play with the macro voice. So, when I gave my first concert at Carnegie Hall - I did two there (solo concerts). The first one was in 2007. I felt the hall kick me out, for I was young and I tried to perform as I always did. You know, I was just singing. But then I came to realize that at Carnegie, you actually have to use not only your micro-vocals, you’ve got to use use your macro-voice, which is the small voice ─ the instrument that’s inside of your vocal chords. The macro, and this is my point, the macro-voice is the whole Carnegie Hall that surrounds you. The Hall is entirely built according to musical principles, so playing the macro-voice requires you to listen, and to play from another place, which is to think about your audience ─ in other words your customers. You’ve got to move your listening and your playing from within to beyond yourself. Right?

And that is when the music, in other words, the leadership … It’s not about inverted. It’s not about leadership. It’s not command and control. It’s about thinking about your audience, you know? It’s thinking about how do I move from micro to macro, and how do I form this frame of consonance, and play from a macro voice? So when this occurs in an organization ─ and Ben Zander actually, Boston Philharmonic, has done some phenomenal speeches on this, and discussions ─ but when this occurs in an organizational society, concrete changes can be witnessed. There’s a decentralization of societal space. There’s a reduction in societal time to be motionless. And there’s a breaking down of the precincts of ego. Right? The visible results of this practice include an amplified understanding of self, of vigor, of beauty, of continuing authenticity that can be recruited and galvanized in the future, and of course, very long, deep changes - long-term changes. So, that’s the core of leadership.

And so, when I do music, when I perform, that’s how I’m thinking about it from the point of view of onstage, and how do I actually recruit the audience in order to participate with me in a way that it becomes a macro ─ the frame of consonance. And that’s musical leadership.

Michael Krigsman: We’ve had guests on CXOTalk who have spoken about the concept of servant leadership, and it sounds very harmonious with what you just described.

Anurag Harsh: Yes. Thank you.

Michael Krigsman: And with that, I’m afraid this very interesting and engaging conversation … It’s time for this episode, Episode #208 of CXOTalk, to draw to a close. We’ve been speaking with Anurag Harsh, who is Senior Vice President and Founding Executive at Ziff Davis. Anurag, thank you so much for being here today.

Anurag Harsh: Thank you very much. I really appreciate the opportunity.

Michael Krigsman: And I hope you come back, and we’ll have to continue this conversation another time.

Anurag Harsh: Absolutely!

MIchael Krigsman: Everybody, thank you for watching. Next week, we have a show; and we have a show the last Friday of December as well, because CXOTalk never rests! Thanks everybody for watching, thanks for your support, and we look forward to seeing you soon. Bye-bye!

Digital Transformation in the Insurance Industry, with UNIQA Insurance Group

  • Episode: 207
  • |
  • Topic: Digital Business
Dr. Alexander Bockelmann, Group CIO and Chief Digital Officer, UNIQA Insurance Group
Dr. Alexander Bockelmann
Group CIO and Chief Digital Officer
UNIQA Insurance Group
Michael Krigsman, Founder, CXOTalk
Michael Krigsman
Industry Analyst
CXOTALK
Dion Hinchcliffe, Chief Strategy Officer, 7Summits
Dion Hinchcliffe
Chief Strategy Officer
7Summits

The financial services industry, including insurance, is undergoing rapid change in response to new technology, FinTech startups, and shifting customer expectations. On this episode, we talk with the CIO and Chief Digital Officer at a large insurance company to understand digital transformation in this important industry.

Dr. Alexander Bockelmann is the CEO of the UNIQA IT Service GmbH and responsible for the IT at the UNIQA Insurance Group AG Together with his team, Alexander is building a new international IT shared service provider for the UNIQA Group, rolling out innovative new IT services across 19 countries.

Alexander is responsible for improving customer value through digital innovation and solutions at UNIQA Insurance Group as well as responsible for the overall IT services within the UNIQA Insurance Group. He is responsible for the IT strategy and IT service delivery within the UNIQA Insurance Group. In 2015, he completed the build up of an IT Shared Service organization while improving IT stability by 50% and improving the success rate of IT enabled business projects by 20%.

Dr. Alexander is currently working on the digital transformation on UNIQA and its related IT activities.

Transcript

 

Michael Krigsman: Welcome to Episode #207 of CXOTalk. I’m Michael Krigsman, industry analyst and host of CXOTalk. CXOTalk brings together the truly the most interesting, and innovative people in the world, talking about disruption, talking about the leadership challenges, and talking about what’s going on in their company, and they’re industry. And today, I’m so happy because my old colleague and friend Dion Hinchcliffe is here as a guest co-host with me. Hey, Dion, how are you?

Dion Hinchcliffe: Hey, Michael! Good to be on the show again, and looking forward to our conversation today.

Michael Krigsman: Yes, we’ll have a great conversation. We’re going to be talking about digital transformation in the insurance industry, and Dion, if you would, please introduce our wonderful guest!

Dion Hinchcliffe: Absolutely! Well, it’s my great pleasure to introduce a very special guest, I think, based on our conversations, it wouldn’t be too hard to say he is a visionary when it comes to information technology. He is the CIO and now, the Chief Digital Officer of UNIQA Insurance Group in Europe. I’d like to welcome to the show Mr. Alexander Bockelmann! Alexander, welcome. Thank you for coming on CXOTalk.

Alexander Bockelmann: Hi Michael, thank you for having me! It’s a pleasure. I’m looking forward to our discussion.

Michael Krigsman: So Alexander, please tell us about UNIQA, and what does UNIQA do, and what is your role?

Alexander Bockelmann: UNIQA is a mid-tier insurance company in Europe. Our headquarters are located in Austria. We’re doing business in 18 European countries, predominantly to the east of Austria ─ so, Central and Eastern Europe, Southeastern Europe up to Russia. And, we’re a multi-line insurer, meaning we’re insuring life products, health products, and non-life products. And, we have about 6 billion in revenue, 14 thousand employees, and about 10.5 million customers.

Dion Hinchcliffe: Well very good! And so, we talked a little bit before the show about your background, and I was struck by some of the concepts you were telling us about that we’ll explore later on in the show. And I was wondering can you tell us a little bit about your background? How did you become the CIO at UNIQA? What was your mandate? You know, what led you to that role in the first place?

Alexander Bockelmann: Originally, I [was] an environmental scientist. After doing that, I had a stint in strategy consulting. And there, one of my first projects was innovative technology in financial services, which started essentially my IT career in the transformation jobs in the industry. And, after working for another insurer for a couple of years, I got the opportunity to join UNIQA, first as the head of IT to build up a new shared service IT organization. And since the middle of this year, [I’ve been spearheading] the digital transformation as the CDO.

Michael Krigsman: It’s really interesting that you have both roles. So you started as a CIO, and now you’ve taken on the CDO role. And I’m always interested what is the connection? What’s the distinction between the CIO and the CDO?

Alexander Bockelmann: The interesting thing is also the setup that we have chosen, because the CDO is essentially a business function. So, I’m now essentially with one foot in the IT world, and with one foot in the business world. {This] gives me an opportunity essentially to not only be stuck with the traditional CIO role, which is often fighting to get a seat at the table, but with the CDO role. It’s now my responsibility to work with my business partners and develop and bring to life new business models. And, spending essentially both roles is also an opportunity, because you can help in the prioritization and getting things done if you have also the IT operations behind you to actually execute on the digital projects.

Dion Hinchcliffe: Yeah, I can see there would be a lot of advantage in having all

 

Michael Krigsman: Welcome to Episode #207 of CXOTalk. I’m Michael Krigsman, industry analyst and host of CXOTalk. CXOTalk brings together the truly the most interesting, and innovative people in the world, talking about disruption, talking about the leadership challenges, and talking about what’s going on in their company, and they’re industry. And today, I’m so happy because my old colleague and friend Dion Hinchcliffe is here as a guest co-host with me. Hey, Dion, how are you?

Dion Hinchcliffe: Hey, Michael! Good to be on the show again, and looking forward to our conversation today.

Michael Krigsman: Yes, we’ll have a great conversation. We’re going to be talking about digital transformation in the insurance industry, and Dion, if you would, please introduce our wonderful guest!

Dion Hinchcliffe: Absolutely! Well, it’s my great pleasure to introduce a very special guest, I think, based on our conversations, it wouldn’t be too hard to say he is a visionary when it comes to information technology. He is the CIO and now, the Chief Digital Officer of UNIQA Insurance Group in Europe. I’d like to welcome to the show Mr. Alexander Bockelmann! Alexander, welcome. Thank you for coming on CXOTalk.

Alexander Bockelmann: Hi Michael, thank you for having me! It’s a pleasure. I’m looking forward to our discussion.

Michael Krigsman: So Alexander, please tell us about UNIQA, and what does UNIQA do, and what is your role?

Alexander Bockelmann: UNIQA is a mid-tier insurance company in Europe. Our headquarters are located in Austria. We’re doing business in 18 European countries, predominantly to the east of Austria ─ so, Central and Eastern Europe, Southeastern Europe up to Russia. And, we’re a multi-line insurer, meaning we’re insuring life products, health products, and non-life products. And, we have about 6 billion in revenue, 14 thousand employees, and about 10.5 million customers.

Dion Hinchcliffe: Well very good! And so, we talked a little bit before the show about your background, and I was struck by some of the concepts you were telling us about that we’ll explore later on in the show. And I was wondering can you tell us a little bit about your background? How did you become the CIO at UNIQA? What was your mandate? You know, what led you to that role in the first place?

Alexander Bockelmann: Originally, I [was] an environmental scientist. After doing that, I had a stint in strategy consulting. And there, one of my first projects was innovative technology in financial services, which started essentially my IT career in the transformation jobs in the industry. And, after working for another insurer for a couple of years, I got the opportunity to join UNIQA, first as the head of IT to build up a new shared service IT organization. And since the middle of this year, [I’ve been spearheading] the digital transformation as the CDO.

Michael Krigsman: It’s really interesting that you have both roles. So you started as a CIO, and now you’ve taken on the CDO role. And I’m always interested what is the connection? What’s the distinction between the CIO and the CDO?

Alexander Bockelmann: The interesting thing is also the setup that we have chosen, because the CDO is essentially a business function. So, I’m now essentially with one foot in the IT world, and with one foot in the business world. {This] gives me an opportunity essentially to not only be stuck with the traditional CIO role, which is often fighting to get a seat at the table, but with the CDO role. It’s now my responsibility to work with my business partners and develop and bring to life new business models. And, spending essentially both roles is also an opportunity, because you can help in the prioritization and getting things done if you have also the IT operations behind you to actually execute on the digital projects.

Dion Hinchcliffe: Yeah, I can see there would be a lot of advantage in having all of the assets of IT to be able to bring to bear to the CDO role, but we said that the CDO role’s primarily a business role, and makes me think of being a P&L, right? A profit / loss center. Whereas IT is traditionally viewed as a cost center. How do you balance those two views there? Are you going to wear both hats? You’ve got to be everything to everybody.

Alexander Bockelmann: It is an interesting situation to play both roles ─ essentially the P&L impact and the cost center part. But the interesting thing is to be in the position to be a credible partner for the C-Suite to work on the transformation that I think is responsible or is needed in the industry. And, I think the CDO role in a company is now very popular. I think last year, or up to last year, 2.5 thousand CDO roles were created. And I think a CDO is crucial at the beginning of a transformational journey as the catalyst and the driver for some of that change. But, it’s a little bit a “role of goal” situation for the enterprise ─ meaning either the digital realities kick in, and the organization is adopting those. And then the CDO becomes a temporary role, because the business is itself taking over that responsibility. Or, you will always have a CDO which is screaming and fighting [on] the sidelines trying to call the plays, but the organization is still moving in the traditional way. And then, actually, the transformation or the digital revolution has failed.

So I think the digital part and the CDO part is important, but I think at some point, you should not need it anymore. And then roles should either go away, or maybe transition to something like a Chief Customer role, bringing in the customer value operation at the board level into the strategic thinking.

Michael Krigsman: So, why is this notion of “customer value” so central to digital transformation?

Alexander Bockelmann: I think the game at the end of the day is lost on one with the interface and the relationship with the customer. If you can create customer value, you will basically not be able to provide your services and products. At the end of the day, nowadays, the digitization is creating different ecosystems and platform businesses, which are topics we can discuss further on. And, if you can then decide to either become a product provider for a service ecosystem, or be the orchestrator of the service ecosystem. If you lose the customer value creation part ─ if you are not relevant for your customers on your own, then you will be absorbed by somebody else’s service environment and ecosystem. So, therefore, the ability to be relevant for your customer ─ to have useful, enjoyable, transparent, and relevant services ─ becomes the win-or-break point in a business strategy.

Dion Hinchcliffe: Yeah, so that’s a very interesting topic, given that you’re in the insurance business, which, you know, it may be different in Europe, but here in the US is a highly regulated industry, not known for its superior digital experiences, I’d say. And so, it sounds like you’re doing some very innovative things, like you know that research from Deloitte that says it’s the platform orchestrators that will bring the most value overall, right? Those individuals in Amazon and so-on. And it sounds like your positioning UNIQA to be in [that] role. Is that [how] you get around the regulation, that you’re enabling other products and services? Or, you know, how are you going to be able to deliver a superior customer experience, given the constraints of your industry?

Alexander Bockelmann: Lately, the constraints are not necessarily limiting you to create great customer value.  Banking is also a regulated industry. Healthcare is a regulated industry. I think you need to transform yourself from a pure product provider and try to develop more holistic services that solve the need for a customer, so that you become relevant on a high frequency basis. The traditional insurance business has the disadvantage that you have literally no touch requirements for your business, or with your customer.

Dion Hinchcliffe: And customer value.

Alexander Bockelmann: Yeah. Imagine you have a life insurance [policy]. You buy it. It goes on for thirty years. And you only have one negative touchpoint each year, which is when you have to pay the premium, right? So, insurance companies are now under pressure to provide the same customer relevancy like retail companies, or other companies, because that is what the customers experience in their daily lives. And when they then approach their insurance company, you don’t want to be seen as going to the dentist, right? It needs to be something enjoyable and useful, and that is where insurance companies need to, well, definitely change their business model and the way they serve customers.

Michael Krigsman: So, how do you manage? It seems to me you’re managing two different hats. Number one is as the Chief Digital Officer, you’re always thinking about the customer as a reference point, and how does our business model incorporate that? And yet, at the same time as the CIO, and correct me if I’m wrong, I’m assuming you’re thinking about our systems - our technology systems; and so, one is a very customer value role, and the other is a kind of inward-looking tech role. How do you reconcile those?

Alexander Bockelmann: When we talk about digital, then we are talking about five different dimensions. And that’s maybe explaining your valid question. If you imagine a simple diagram with a horizontal and a vertical axis, the way we illustrate our digital approach is on the horizontal axis. We have basically all the internal digital activities, which we did for a couple of years before all the buzzwords, basically in here. That’s everything that has to do with automation, with process and product standardization, with legacy modernization ─ all those activities; and that’s the traditional home-turf of the CIO.

The second dimension ─ the vertical dimension ─ is the external role, which is one of the key pillars basically of digitization, which is “How are you approaching your customer?” And from an IT perspective, you have the internal employee as a customer, you’re business partners as a customer, and your ultimate business customer. So, for each of those, we are basically in our digital endeavor. We want to change how they experience the world on a daily basis ─ make it more value-driven. And not only do that for our customers, but also our employees. Otherwise, we will not have the momentum that we need. So those are the framing two conditions.

Within that little graph, you then have the dimension of data and analytics, which is very important for digital business models. And the crown jewel is essentially the development of new business models. And, underlying all of that, the key enabler to do any of that work is essentially a cultural change in the company. If you don’t do that, your digital journey will essentially not work very well. So, those are essentially the five dimensions.

And, with the CDO role, it’s all about external data, [and] new business models. With the CIO role, it’s all about culture, internal processes and procedures. And that’s how it’s balanced.

Dion Hinchcliffe: That’s very interesting. So, this brings us to the hot topic of the day that we read in all of the trade journals, and that is the process of digital transformation that all organizations really have to undergo. Now, we see that the technology role is changing faster than our organizations, and you say we have to roll out these new products and build these ecosystems, and layer in these new business models. Can you tell us about your journey at UNIQA, and how you’re going about it?

Alexander Bockelmann: Yeah, we’re trying to manage three different phases. Essentially, you have to take care of your business of today ─ your customers of today. You have to deliver on your promise. So, you need to develop and optimize today’s business, which is the automation, standardization, improvement part of the journey. Then you have the second phase, which is the transition phase moving from your existing business model; and augmenting that, strengthening that, with new business models. So, there’s a big change management component in there.

What I always say is that this part is where I use the phrase, “You have to provide digital leadership.” What that is, is you landed on an island, which is your current state where you work today. Unfortunately, your boats are beginning to smolder and to catch fire. So, your old model starts to burn, and you have no idea yet what new boats you’re building ─ what the new business models will be ─ because nobody knows today what the silver bullet of tomorrow is. And as a digital leader, one of your key requirements is to manage that transition phase, and keep your employers and peers engaged in that journey.

And the third phase is then actually building the new business models. And there, it’s all about learning with the experience, not trying to reinvent the wheel, and being the world dominator in the first step. Think big, start small, and learn from your customer feedback.

Michael Krigsman: What are some of the difficult challenges? You know, it’s interesting as you describe it, it’s nice and neat. But, in practice, I’m sure that it’s not quite as simple and as easy as it sounds when one talks about it.

Alexander Bockelmann: No, of course, there are tons of pitfalls, and we learn something new every day. The one challenge is, as Dion already said, “Insurance is not well-known for innovation.” It’s a 400 year old industry, or maybe older. Our company is very proud to have over 200 years of company history. So, you have very established and organically grown products, processes, and procedures. You also have, as a bank or as an insurance company that has always dealt with a lot of data, everything that was commercially available at one time in your data center. Right? At one point, I was basically jokingly saying that I can improve my budget by going to the local IT university, and selling tickets for people to look at very old-fashioned technology! And, it’s still working. It’s working fine. But, most of these systems that you deal with are predating the Internet. So, they have no concept of microservices. They have no concept of connectivity. They’re not designed for flexibility and for supporting ecosystems, so obviously you have to deal with that.

And, the the third topic is something that I call the “expert dilemma.” The expert dilemma is if you are in a very successful company, you tend to project your past success to the future. And, in the new world (in the digital world), the rules of the game have changed. And what made you strong in the past will not make you strong in the future, and therefore, there is this mindset shift that needs to happen to gain momentum on a digital journey. So you have technical opportunities for improvement; you have cultural ─ mindset-wise. And as insurance, you don’t have an industry with much experience for need for action, where something dramatic needs to happen as the business model was so stable for such a long time. So you don’t have a lot of change agents that are ready to go the next change program, because they have done it so often. Insurance has not reinvented itself in the past, and that’s a major transformation challenge.

Michael Krigsman: It’s pretty extraordinary. So, in a sense, there’s really no choice. So, what kind of sense of urgency is there within the organization to embrace the kind of changes that you’re talking about? And it’s difficult for any organization to change the way you’re describing.

Alexander Bockelmann: I am very fortunate to work in a company where the board of management and our supervisory board basically have that sense of urgency. And we can talk about our transformation program maybe later on. But, if you look at the insurance business, and I mentioned the three parts of it: life, health, and non-life; think about what’s happening in the industry. We have a very low interest regime right now. In the past, the business model in life insurance for an insurer was very simple. Get the premium. Put it into an asset management account. Get 10% returns, and promise your customer let’s say 4-5%. You have 2% admin expenses and 3% of that asset-under-management income. The investment income is your profit. So that business model was very simple. If you have an interest rate that is zero or negative, that model doesn’t work anymore. But, you have promised your customers an annuity. If it’s a fixed annuity, you have promised them a certain return. So, the life insurance business right now is not profitable for most of the life insurance companies, so there is a sense of urgency.

If you take health insurance. Health insurance is taking some of your premium, [and] putting it in an asset account. And this [assumes] that you get a certain interest rate to pay for higher medical expenses when you get older. If you don’t get that interest rate, then you have to either ask for more money or reduce your level of service. As you don’t want to do the latter, you have to do the former, which the customer’s not appreciating. So two of your three business models are currently under pressure.

The third one [is] non-life. For many insurance companies, 50% of their non-life business is motor insurance. So, you know what’s happening with motor insurance with the Teslas and other innovations coming our way. So that business model, where you insure a driver of a vehicle is evaporating.

So, three out of three business models are under pressure in insurance. So, if somebody has not received the sense of urgency to do something, then maybe insurance is not the right place to be right now.

Michael Krigsman: We have a question from Twitter. Wayne Anderson is asking, “How do you balance the privacy requirements in this shift to digital?”

Alexander Bockelmann: Privacy requirements are extremely important for us, because insurance companies are living off their reputation. If there would ever be a breach or a misuse of personal data, that is a code of conduct that all insurance companies are basically following. We don’t want that. So, we take extreme care, and that is actually limiting some of the activities that we can do. For example, in Austria, it took us 2.5 years of negotiation with the local regulator to get a video identification process in place that is accepted by the regulator. And, we also are not only in a situation where it’s very tricky which data we want to use, we are so far advanced in technology that it becomes an ethical question, not only a legal data usage question. What I mean by that is we all know privacy laws and all the challenges we have with that, but technology nowadays allows us, when a baby is born, to get a test (usually on the third day) for certain diseases that they could have. Nowadays, it would be economically feasible to get a DNA imprint of that newborn child, and then identify the likelihood for diseases, how well the medicines will work, etc. And, you could profile a lot size of one ─ meaning a very personalized health insurance product for this person. But, that would completely destroy the underlying idea of insurance where you spread that basically across a bigger audience and a bigger group. And therefore, data usage ─ the information that is available ─ especially in healthcare and digital health, which for us is very important, becomes an ethical question. And there’s information and data that we would not use even if we legally were allowed to do it.

Dion Hinchcliffe: Yes, so the picture you just painted reminds me of something you told us when we were speaking earlier that I thought was really amazing to hear from a C-level leader of a large organization, and that is: given all the things you just relayed about each one of your business models, your existing business models is under pressure, even the insurability of people is changing because of DNA imprints; what you said was you believe in the five to ten years, the classical insurance company will disappear. And so, how does that affect your role? It sounds like you are the one - you are on the hotseat for building that bridge into the future to something that’s hopefully on the other side. Is that right?

Alexander Bockelmann: Well, it’s always a team sport. Right? If you would depend on only one person, you’re not working in cross-functional teams, which I think are most effective. If we build now a silo where there is only one single person driving innovation and change, then it will probably not succeed. But having said that, as part of our journey, we created two new roles midyear in 2016. One was my role, the CDO role on top of the CIO role, to tackle all of the topics that we just discussed. I have a partner in crime, which is a colleague of mine with the title of Chief Innovation Officer. And what we are doing there is that he is looking specifically at the idea of what could be new business models; what could be new partnerships; what could be new ecosystems to join to create, to strengthen our overall business approach. And to be ready for the third phase that I’ve mentioned ─ the start of at least the testing of new business models.

Michael Krigsman: Again, it’s another very interesting point. So, if the Chief Digital Officer is responsible, or let’s say very heavily involved with searching out new business models, and new business models of course are a key form of innovation; and, the Chief Innovation Officer is obviously responsible for innovation; how are these two roles different?

Alexander Bockelmann: They are part of the same puzzle. I think you (in some sort of fashion), in whatever organization you are, you need to tackle the challenges that those two roles are addressing. If you think about it, in traditional innovation management, you have at the beginning a lot of ideas that go into a funnel, and then they go into execution or piloting or something similar. So, now imagine you do that with a topic of business models. So the Chief Innovation Officer is essentially screening the fintech and insurtech world of where could there be ideas for partnerships, for investing into new models, for observing what others are doing, and also for designing ideas for additional models for UNIQA. And, at some point, those topics become more concrete and prioritized, and then the Chief Digital Officer comes into play to think about the aspects associated with that role: what’s the customer value; what’s the customer journey; touchpoint analysis; etc. And then it goes further into the execution, either in our new digital team, if it’s an external-facing activity, or in the basic traditional core IT unit, which is still essentially the central nervous system of our UNIQA business models. So that’s how two roles play together.

Dion Hinchcliffe: Yeah, that makes a lot of sense. And so, when we talked before, you were saying some very interesting things about how the importance of data had shifted. I think you mentioned it before, but what’s the role of data in your digital transformation? I think you talked about that it should support customer experience, but I think there’s more to it than that.

Alexander Bockelmann: Yeah, I think all digital models at the end of the day by definition are data-driven business models. But, outside of that, as an insurance company, you have a lot of information available and most insurance companies are quite good at analyzing those for whatever opportunities and insights you can gain out of those. But, those have not changed a lot over the last decades. There are the same type of information that is linked to underwriting, risk underwriting, assessing a risk, and invoicing, billing, claims handling ─ that kind of thing. Nowadays, however, with the internet, with mobile devices, within the internet of things, with telemetic technologies, you have in theory a much, much bigger universe of data points, which allow you the opportunity to improve the risk-based products that you have with new service offerings.

For example, I said the motor business is under pressure, right? And, we all know that the self-driving cars are around the corner sooner or later. Most projections say by 2021, all the major players will have those on the road. Add another 5-10 years for the exchange cycle, and then you will have a meaningful number of self-driving cars on the road.

At some point, and also with the sharing economy where people are not owning stuff anymore, there will be a tipping point where you’re essentially developing a new need, which is a mobility need. The person wants to get from point A to point B, but they don’t want to own a car to get there. Depending on the weather, they might use a bicycle, or a car, or take public transportation. So is there an opportunity for insurance companies, similar to the car OEMs, to develop ideas and exchange the old business model of insuring a driver, and just link, for example, a mobility service with your home insurance. If you live at Location A, and you work at Location B, why couldn’t an insurance company not offer you with your home, and life, and health insurance, a mobility package that could bring you from A to B, in whatever fashion you fancy?

Michael Krigsman: We have a question from Twitter, and I just want to remind everybody that you’re watching CXOTalk. Right now, there is a tweet chat going on using the hashtag #cxotalk. And, we are speaking with Dr. Alexander Bockelmann, who is the Global CIO and Chief Digital Officer for a major European insurance company, UNIQA Group. And we have a question, Alexander, from Arsalan Khan on Twitter, who says, “What kind of labs do you have?” Essentially it’s the innovation question, and how do you manage experiments, and how do you manager failure? And along the same lines, I’m going to throw in and ask if you can touch on your view of fintech, and startups, and competition coming from those directions.

Alexander Bockelmann: Ok, thank you for the question, first of all. And, what kind of labs did we have? Let me take a step back before I answer that. I think disruptive innovation is very hard, if at all achievable within a given organization. So if you want to do something that is really new, you most of the time do not have the resources in the existing organization, which is streamlined for efficiency to manage your existing business, to do all that disruptive stuff on top of everything else. So, I think that is the main driver why people have certain labs.

What we have is, we have a digital team that is centered around a customer experience group. As I mentioned, that customer value creation and customer experience is for me one of the key winning ingredients in digital solutions. And surrounding that, we are building teams for the web and portal space, for the mobile space, and for the data analytics space. Why is that important? The first two [are] web and mobile. I think we are obviously in a mobile-first world. And you always need to be there where the customer wants to engage you, and always when the customer wants to do this. So, you have an “anytime, anywhere, 24/7” obligation for good customer service, at some point depending on your services. And, the third pillar, the data pillar, is very important to manage all the additional data volumes. And I believe that insurers need to transform from pure risk product providers to be more predictive and preventive life solution providers. And, that’s where you need a new competency in data and analytics to make that happen.

Dion Hinchcliffe: So, we’d be remiss in not bringing up another subject of industry conversation lately, and that is something that our mutual friend Martin Lanford has been talking about which is just, “CIOs are shackled to Legacy Mountain,” as it were, that 70-90% of our budgets are required to just keep what we already have going, and that leaves very little left over to maneuver to innovate, to move your organization across that bridge into the future. How do you cope with that? I mean, this is the best-kept secret in our industry, that people don’t understand what holds back so many organizations. How do you cope with that?

Alexander Bockelmann: That’s true. That’s a major challenge, especially when you have regulated industries. On top of that, you also have the change projects driven by new regulations. And that is obviously more often than not eating away all your change capacity that you have in a given year. So, due to the sense of urgency that is for us needed in the industry, our board made a very bold decision, and started on the next stage in our UNIQA 2.0 strategy. We started a transformation program that is founded above and beyond the regular outlets for those change activities in the three phases mentioned: the existing business, the transition period, and the development of new business models. And, we started a ten year program that is funded with 500 million Euros, and that gives us additional capacity and budget to tackle the challenges that we discussed today.

Michael Krigsman: We have another question from Twitter. And, Shelley Lucas is asking about the use of virtual reality, augmented reality, mixed reality in risk and in your models, and how is that going to affect the insurance industry?

Alexander Bockelmann: Very good question. Personally, I think augmented reality will have a bigger and faster impact than virtual reality. Doesn’t mean that virtual reality is not coming, but I think that’s a little bit further down the road. With augmented reality, a lot of things are in theory possible in the insurance phase from risk assessment over solution design for certain things. So, I’m very big on the idea that augmented reality will become available quite soon. You already see some innovative companies that use it more in the machine industry for maintenance tasks, on turbines, and things like that. So I think that is coming.

For us right now, the more short-term usage is not the virtual or augmented reality piece, but the machine learning piece. So, I think that machine learning and artificial intelligence are extremely impactful for business models. I believe that a lot of the customer interaction in the future in many service environments will be at least optimized by artificial intelligence , if not conducted by artificial intelligence. And, we also have a pilot running right now to use machine learning for the optimization of certain processes and procedures in our health insurance segment. So, I believe that there is a lot going on in that space.

And you asked earlier: Fintech, startups, etc. If you think about the money that is being poured into those fintechs and startups over the last couple of years, it enabled an immense amount of innovation. And I think that’s very helpful to bring that amount of new ideas into a lot of industries, and the one thing everybody should not do is ignore that. I always have a sign in my mind that says, “Ignore at your own peril,” so … like a danger sign. For me at least, at least insurtech companies are very useful in our transformation journey, because often, they have an opportunity to develop or find a solution to a problem where we neither have the resources or have the idea how to do that. I think Cisco is a model of buy, partner, observe and so, forth is the right one. So you have to think about fintech and insuretech as a partnership model. I think 85% of those companies don’t want to disrupt incumbents, they want to work with them. And the combination can be very powerful.

Michael Krigsman: And we have another question from Twitter. Sohail Sarwar, and I hope I’m pronouncing his name correctly, if not I apologize, is asking about the impact of blockchain.

Alexander Bockermann: Blockchain for me is a very interesting technology because it has the potential to solve a lot of efficiency problems. So it has the potential to solve things in the space of fraud detection in the area of identity management. It can be a very cheap transactional documentation ledger technology. For me, however, blockchain is still missing a couple of key ingredients for making really a big impact. The key ingredients are scalability, standardization, and adoption. Because for me, blockchain has the biggest impact. The bigger the network that is using a certain blockchain solution. I could easily imagine now having an in-house blockchain use case, but then the impact would be very marginal. If we, on the country level, suddenly would have a blockchain network across multiple providers, service providers, including customers or so-forth, then blockchain could really be powerful. And I think it will come, but I think it will come in a couple of years. And now I’m falling probably in the same dilemma that I mentioned before, that we always think linearly in the development of certain technologies, but they develop exponentially. So, if I say it will take three to five years, maybe it’s only one or two. Take it with a grain of salt.

Dion Hinchcliffe: Absolutely. So, as you wrap up the show, I was wondering if you could share some practical advice about digital transformation. You’ve been down the road at least part of the way, right? And you would be able to have lessons learned and presumably battle scars…What would you tell other CIOs in terms of advice? How should they go about digital transformation?

Alexander Bockelmann: I would say take ownership, and leverage the sense of urgency to get into a driver’s seat for the journey. Kim Stevenson from Intel once had a famous quote saying there are no IT projects, only business projects. And today, there are no IT roles; there are only business leaders. So therefore, every new digital business model is an IT-enabled and empowered business model. So, CIOs should basically feel empowered to have a voice in that.

The second one: provide the digital leadership. Your C-suite is often probably not as well-educated on the new technologies. You have an opportunity to have a coaching and educational aspect there. And, whatever you do, do not build the strategy for … Do not build the digital strategy, but build a strategy for a digital world. That is a play with words, but it basically has a totally different perspective if you design your strategy in that way.

And then, start now. There is no right way of doing it. You have to think big ─ that your idea can scale. You have to start small, and learn from your customers. So, engage customer feedback as early in the process as possible, and then figuratively improve the outcome. And, if possible, engage your employees. And find change agents at all levels ─ from the C-level down to the individual expert at the desk ─ to carry the torch with you, because there’s potentially a lot of good energy and ideas in your team already that just needs a way to express that. And that’s the experience that we did. Once we created the environment, there were a lot of people that stepped up and helped us essentially in our first steps of the journey.

Michael Krigsman: And as we finish the show in the last couple of minutes, what advice do you have for Chief Information Officers? You came into this role as a business leader, not as a technologist. And so, you have a broad perspective. So, what is your advice to CIOs to manage this very difficult and challenging transition period, where it’s not even clear where we’re transitioning to?

Alexander Bockelmann: I think it doesn’t sound pretty, but the first thing is get your ship in order. If your day-to-day business is not working, then you’re so much in firefighting mode that you have no chance to get out of that, and you will not have the credibility to build something new. So, first of all, take care of your business today. The second one is Show & Tell, meaning try to find some resources to build the mock-up ─ to do something that doesn’t take a lot of effort. But, get away from any powerpoint strategy presentations, and show an idea as a click dummy. What we once did is we wanted to get the point across that customer journeys are important, and you have to look at things from a customer perspective. And we very quickly found out that giving powerpoint presentations is not the best way of doing that. And what I’m sharing now is not the silver bullet thing, it’s just an illustration. Think differently. So what we did is we did a very short Playmobil stop motion movie, and we played the life of customers in a certain situation before and after a project that we proposed. And suddenly, people understood on a totally different level what we want to achieve with this project, and how it can influence the life of our customers in a much different way than if we would just have used powerpoint. So, just find creative ways to show how a digital project can be different, and then find one or two lighthouse projects to build momentum. And don’t pick the most difficult ones. So, these ones should really be …. not as a first. These ones should be ones with a relatively high likelihood of success.

Michael Krigsman: Okay, wow! Dion, this has really been quite a conversation, hasn’t it?

 

Dion Hinchcliffe: Yeah, no it’s amazing to see how things are changing, how industries really are going right up to the brink and how Alexander probably has his role at the most interesting possible moment in the evolution of moving from the industrial age to the new modern world. So yeah, that was a great conversation, really appreciated that.

Michael Krigsman: And you know Dion, one of the things that I found most fascinating is the fact that Alexander has this perspective as a Global CIO, but at the same time has equally his feet on the business side, and thinking about the customer impact, and the business model impact as well.

Dion Hinchcliffe: Yeah, and you really would think that’s a recipe for success. You know, we always had this talk about the IT business divided, and Alexander seems to have found a way to bridge that by having that CDO role and that CIO role, so it’s great to see.

Michael Krigsman: Well, we have been talking with Dr. Alexander Bockelmann, who is the Global CIO and Chief Digital Officer at UNIQA Insurance Group. Alexander, thank you again for taking time to speak with us today.

Alexander Bockelmann: Michael, Dion, it has been a pleasure, and I’m honored to be a part of your show. Thank you very much.

Michael Krigsman: And I hope you’ll come back again! [Laughter]

Alexander Bockelmann: Any time, any time! Thank you for having me!

Michael Krigsman: And Dion Hinchcliffe, thank you for being the guest co-host today!

Dion Hinchcliffe: Yeah, thank you so much, Michael! I really enjoyed being here!

Michael Krigsman: Everybody, there will be another show next week, and please come back and watch. Have a great day! Bye-bye.

AI: Legal, Ethical, and Policy Challenges

  • Episode: 203
  • |
  • Topic: Leadership
Dr. David A. Bray, Visiting Executive In-Residence, Harvard University
Dr. David Bray
Visiting Executive In-Residence
Harvard University
Kay Firth-Butterfield, Executive Director, AL-Austin
Kay Firth-Butterfield
Co-Founder, Consortium for Law and Ethics of Artificial Intelligence and Robotics
University of Texas, Austin
Michael Krigsman, Founder, CXOTalk
Michael Krigsman
Industry Analyst
CXOTALK

Artificial intelligence is fraught with legal, ethical, and public policy challenges. This episode brings two esteemed experts to discuss these issues and present guidance for both commercial companies and the public sector policymakers.

Dr. David A. Bray began work in public service at age 15, later serving in the private sector before returning as IT Chief for the CDC’s Bioterrorism Preparedness and Response Program during 9/11; volunteering to deploy to Afghanistan to “think differently” on military and humanitarian issues; and serving as a Senior Executive advocating for increased information interoperability, cybersecurity, and civil liberty protections. He serves as a Visiting Executive In-Residence at Harvard University, a member of the Council on Foreign Relations, and a Visiting Associate at the University of Oxford. He has received both the Arthur S, Flemming Award and Roger W. Jones Award for Executive Leadership. In 2015, he was chosen to be an Eisenhower Fellow to Taiwan and Australia and in 2016, Business Insider named him one of the top “24 Americans Who Are Changing the World”. 

Kay Firth-Butterfield is a Barrister and part-time Judge and has worked as a mediator, arbitrator, business owner and professor in the United Kingdom. In the United States, she is Chief Officer, and member, of the Lucid.ai Ethics Advisory Panel (EAP) and an adjunct Professor of Law. Kay is a humanitarian with a strong sense of social justice and has advanced degrees in Law and International Relations. Kay co-founded the Consortium for Law and Policy of Artificial Intelligence and Robotics at the University of Texas and taught its first course: Artificial Intelligence and Emerging Technologies: Law and Policy. She is Vice Chair of the IEEE Industry Connections Committee “Global Initiative for Ethical Considerations in the Design of Autonomous Systems”. 

Transcript

Michael Krigsman: Welcome to Episode #203 of CXOTalk. I’m Michael Krigsman, and CXOTalk brings together the most innovate, most original, most interesting business thinkers to have an in-depth conversation about important and very often disruptive issues. And these are people who are genuinely shaping some important part of our world. Today, on Episode #203 of CXOTalk, we’re going to be discussing artificial intelligence, and particularly the ethical and the public policy, and the legal challenges and implications associated with that. We have two amazing guests. Our first guest is Kay Firth-Butterfield, who is a legal scholar and one of the world’s top experts in the ethical issues and legal issues associated with artificial intelligence and robotics. And our other guest is David Bray, who is the CIO for the Federal Communications Commission. So, let’s begin with Kay. Kay Firth-Butterfield, how are you and thanks so much for taking the time!

Kay Firth-Butterfield: Thank you for giving me the opportunity!

Michael Krigsman: So Kay, tell us about your background.

Kay Firth-Butterfield: Well, my background, as you say, I’m a lawyer. I was a barrister and judge in England before I moved to the United States about eight years ago. And here I’ve been teaching law, and thinking about artificial intelligence. I recently was the chief officer of an AI company and ran the ethics advisory panel. We were the first AI company that actually allowed its CO to go out and give talks, and talk about what we were doing. I’d say that was a great privilege for me to be there at the founding edge of that work and to be able to talk about what we were doing. In the last month, I moved to be the executive director of Austin…  AI-Austin and that’s a brand new collaboration between academia, industry, government, medical school, and others. And although we’re based in Austin, we’re actually having a very global outreach program. So, I’m really looking forward to taking that forward with my co-founding advocates. I still do have an academic background: I’m Distinguished Scholar at the [Robert E.] Strauss Center at the University of Texas; and I teach a course on artificial intelligence and the law for the law school there. I am founder of an organization that is a consortium at the University of Texas, which, we call it “CLEAR” because it’s actual title is quite long. It’s the Consortium on Law and Ethics of Artificial Intelligence and Robotics. And, then, I am Vice Chair of the IEEE’s project (another snappy title): The Global Initiative for Ethical Considerations in the Design of Autonomous Systems.

Michael Krigsman: Ok. So, if we want to talk about law and AI, you’re the person to talk to. [Laughter]

Kay Firth-Butterfield: Well, I’ll try to be! [Laughter]

Michael Krigsman: Ok. And, our other guest is my good friend and colleague David Bray, who has been on CXOTalk several other times, and David is the CIO for the Federal Communications Commission. Dr. David Bray, welcome to CXOTalk again!

David Bray: Thanks for having me, Michael. It’s great to be here and I look forward to discussing how we can both deal with the basic fundamentals of artificial intelligence; and how we can begin to use it in organizations both public and private; as well as how we can actually make sense of the ethical issues involved in AI use.

Michael Krigsman: Ok. So let’s dive in. When we talk about AI, what do we mean? David, tell us, what are we actually talking about here? I think we need to get that out of the way first.

David Bray: I think that’s absolutely true. So, artificial intelligence probably includes many different things to different people. And I can only talk about it as machine learning; it’s neural networks… It really is using technology to try and emulate, basically something that appears to be intelligent. And I want to be very careful about using the word, “appears to be intelligent”

Michael Krigsman: Welcome to Episode #203 of CXOTalk. I’m Michael Krigsman, and CXOTalk brings together the most innovate, most original, most interesting business thinkers to have an in-depth conversation about important and very often disruptive issues. And these are people who are genuinely shaping some important part of our world. Today, on Episode #203 of CXOTalk, we’re going to be discussing artificial intelligence, and particularly the ethical and the public policy, and the legal challenges and implications associated with that. We have two amazing guests. Our first guest is Kay Firth-Butterfield, who is a legal scholar and one of the world’s top experts in the ethical issues and legal issues associated with artificial intelligence and robotics. And our other guest is David Bray, who is the CIO for the Federal Communications Commission. So, let’s begin with Kay. Kay Firth-Butterfield, how are you and thanks so much for taking the time!

Kay Firth-Butterfield: Thank you for giving me the opportunity!

Michael Krigsman: So Kay, tell us about your background.

Kay Firth-Butterfield: Well, my background, as you say, I’m a lawyer. I was a barrister and judge in England before I moved to the United States about eight years ago. And here I’ve been teaching law, and thinking about artificial intelligence. I recently was the chief officer of an AI company and ran the ethics advisory panel. We were the first AI company that actually allowed its CO to go out and give talks, and talk about what we were doing. I’d say that was a great privilege for me to be there at the founding edge of that work and to be able to talk about what we were doing. In the last month, I moved to be the executive director of Austin…  AI-Austin and that’s a brand new collaboration between academia, industry, government, medical school, and others. And although we’re based in Austin, we’re actually having a very global outreach program. So, I’m really looking forward to taking that forward with my co-founding advocates. I still do have an academic background: I’m Distinguished Scholar at the [Robert E.] Strauss Center at the University of Texas; and I teach a course on artificial intelligence and the law for the law school there. I am founder of an organization that is a consortium at the University of Texas, which, we call it “CLEAR” because it’s actual title is quite long. It’s the Consortium on Law and Ethics of Artificial Intelligence and Robotics. And, then, I am Vice Chair of the IEEE’s project (another snappy title): The Global Initiative for Ethical Considerations in the Design of Autonomous Systems.

Michael Krigsman: Ok. So, if we want to talk about law and AI, you’re the person to talk to. [Laughter]

Kay Firth-Butterfield: Well, I’ll try to be! [Laughter]

Michael Krigsman: Ok. And, our other guest is my good friend and colleague David Bray, who has been on CXOTalk several other times, and David is the CIO for the Federal Communications Commission. Dr. David Bray, welcome to CXOTalk again!

David Bray: Thanks for having me, Michael. It’s great to be here and I look forward to discussing how we can both deal with the basic fundamentals of artificial intelligence; and how we can begin to use it in organizations both public and private; as well as how we can actually make sense of the ethical issues involved in AI use.

Michael Krigsman: Ok. So let’s dive in. When we talk about AI, what do we mean? David, tell us, what are we actually talking about here? I think we need to get that out of the way first.

David Bray: I think that’s absolutely true. So, artificial intelligence probably includes many different things to different people. And I can only talk about it as machine learning; it’s neural networks… It really is using technology to try and emulate, basically something that appears to be intelligent. And I want to be very careful about using the word, “appears to be intelligent” because we have to answer the question of what’s intelligent behavior in the first place. We can be very human-centric and say, “Well, humans are inteligent because we are able to make sense of challenges put before us. We can be goal-oriented.”

I think when it comes to talking about AI, what we’re really talking about is using technology to solve problems or achieve goals in ways that appear to mirror intelligence beyond just something that someone has programmed the machine explicitly to do.

Michael Krigsman: And Kay, as an attorney, how do you think about the definition of AI?

Kay Firth-Butterfield: Well, I will piggy-back on what David said, in terms of AI. But, I think that basically we’re talking about a scholarship that has been going on now for a long time and a number of different ways of achieving what we call “artificial intelligence.” But again, I’m going to piggy-back on David as to what might be intelligence. I think that we need to perhaps lift from the UK government’s recent report that “artificial intelligence” can be adequately used as an umbrella for all the different things going on ─ all the different scholarship in this space.

Michael Krigsman: When we talk about AI, it seems like it has become the explosive growth in the jargon value of AI. And, in commercial companies wanting to piggy-back on top of the terminology. And so, clearly AI is very important, but can either of you shed a little bit of light more specifically on why it’s so important, why this explosive growth, and why we should actually care about the legal, policy, ethical issues of AI?

David Bray: So … Go ahead, you can go first, Kay.

Michael Krigsman: Please, Kay, go ahead.

Kay Firth-Butterfield: Ok. [Laughter] I think that one of the things that sticks out in my mind is some research that McKinsey [&Co.] did recently, where they describe AI as a contributing factor to the transformation of society. And I just want to quote what they’re saying about the transformation of our society: that it’s happening ten times faster, and at three hundred times the scale, or roughly three thousand times faster than the impact of the industrial revolution. And you know, a lot of people compare this revolution to the industrial revolution. But, I think it’s the speed and the real, core underpinning that AI is contributing to that transformation of our society, that makes these discussions so important.

David Bray: So, I would build on what Kay was saying, and really say that I think AI has had three waves. We’re kind of in wave three in my opinion. The first wave: you can actually go back to a Nobel Prize winner Herb [A.] Simon. Herbert Simon, interestingly enough, actually started off actually with New York government and public service, and he observed what he called administrative behavior. And what he saw in terms of how people did administrative behavior was, generally, people didn’t go beyond sort of the landscape of what they already knew to be true. And he had this conclusion that the challenge is “How can you help people in organizations go beyond the landscape of what people knew to be true.” And interestingly enough it led him to do behavioral economics, behavioral psychology, and eventually to artificial intelligence. So, in some respects, observing how people make decisions in public service gave rise to artificial intelligence. That was a first wave.

The later waves tried to look at what was called decision support systems, expert systems and that would be the late 80’s and the 90’s. And I think what we’re now is, I think the third wave is really occurring, quite frankly as Kay said, because computers have gotten fast enough; memory has gotten cheap enough; the internet is now connecting things that we can actually now do distributed problem-solving at a scale that frankly was not possible in the 80’s or 90’s, or when Herb Simon was trying to do his work in the 70’s.

So, why AI has become the buzzword is, in some respects, and I would say it’s replaced “cloud” as the new buzzword. In some respects, cloud was the buzzword four or five years ago. That said, and interesting enough, even though it’s replaced that buzzword, in some respects AI is only possible now because we do have cloud computing. So, you have elasticity of CPU cycles, of memory, and quite frankly, just the sheer scope of being able to collect data and trying to make sense of it. That’s why I think artificial intelligence has reached the crescendo that we’re hearing about right now.

Kay Firth-Butterfield: And I think also that we’re actually beginning to see artificial intelligence so the general public can see it so much more. And they’ve interestingly, the Future of Advocacy did a YouGov poll in the United Kingdom just recently, which showed how little the general public understand about AI. But, when they go out their door, and they can see for example an autonomous vehicle or truck, then that’s really leading to the way that we’ve had much more reporting in the press about AI. And so, I think it’s not just the technology, but it’s also the fruits of the technology that are being seen that contribute to the conversation I think is so important at the moment.

Michael Krigsman: So we see, as you said, we see technology such as autonomous vehicles coming out, and if you’re in San Francisco you can often see these driverless cars, or autonomous cars driving around the streets, and things like Chatbots that are visceral reminders to people, or make people aware of the personal impact of these technologies. So, it’s not just hidden behind the surface. But all of this creates a set of dynamics with profound implications for ethics, for the legal system and for policymakers. And, Kay, why? Why is that the case?

Kay Firth-Butterfield: Because, we are, as lawyers, always catching up. And so, for example, in a common law system, unless you have legislation, you have to wait for something to happen before you can have case law decisions be made about it. So, we’re sort of in this holding pattern at the moment where we’re either waiting for governments to create legislation or for self-regulation to spin out, and I think that’s vitally important, or the case law piece. And so, you know, if you look at Europe for example, they have gone with regulation of a lot of these things, and more and more so. Whereas of course, in the United States, we have seen a very slow progress just through the NHTSA trying to work out how to govern or regulate safety on those vehicles.

Michael Krigsman: And David, what about … Why is this such a potential quagmire? Why is this so fraught with difficulty and challenge from a policy perspective?

David Bray: So, that is where I’ll put on my Eisenhower Fellow hat, where I was in Taiwan and Australia and had a chance last February and March talk to them, both about their strategies for the Intenet of Everything, but also the expected impacts of artificial intelligence. And I think, first is there is the need for educating the people in a way that is accessible to everyone, not just computer scientists, as to what artificial intelligence can and cannot do. I think we may have the challenge of people who have been educated in those respects through the movies and the movies, of course, show a very non-realistic situation in terms of artificial intelligence deciding to change its ultimate goal, and somehow taking over the world or something that… You know, we actually do not currently have a programming language that allows you to have the program itself change its ultimate goal. It may be able to change sub-goals, but we don’t have the ability to have a machine change its ultimate goal yet. And people will say, “Yeah,” but then unlikely again.

It’s trying to have a conversation that involves everyone, not just the experts on artificial intelligence, that is going to make tackling these issues, both in the public sector and in the private sector, challenging. And I think as Kay said too, I think we need to have a little bit more demonstration projects before there is any rush to try and do any policy. You don’t even begin to show what’s possible, both from a good sense, and also what maybe you want to try and avoid, if you don’t show what’s possible. It’s really hard to have an informed conversation. So hopefully over the next year or two, we can try to show what artificial intelligence beyond these autonomous cars, maybe can make local communities healthier or safer, maybe address things at the national level.

One of the things I’m tracking with interest is in California. They actually are using machine learning to actually help set bail decisions. So you feed in the facts of the case, and it actually makes a bail recommendation. The interesting thing about that is [it] actually helps weed out things that shouldn’t relate to your bail decision, and shouldn’t be related to your height, or your weight, or your gender, or your race. So, in some respects, artificial intelligence in that sense could actually make things more ethical, because we know what the algorithm is, and we know it’s not taking in extraneous information that should not be important.

Kay Firth-Butterfield: Except, looking at that on a different footing of helping the sentencing, you know there was the recent research done around bias ─ in-built bias ─  in sentencing so that people of color were still getting heavier sentences than white people using the models. So I think we have to be very careful around how we build these systems.

David Bray: Oh I agree 100% and that’s where one of the things I really want to see happen is making the algorithm open-source in terms of what weight and what factors it’s considering. So I agree. If you’re only going to base it on past decisions, and past decisions were made by human bias, then don’t be surprised the machine itself is going to be biased, too. I think that’s where there needs to be a conversation about where do you want to get your data. Because if your data is biased, it will result in biased decisions. However, that’s also where the machine itself can probably pick up, and actually begin to identify weight. These past human decisions were biased. I mean, we know it’s a sad reality. Your height should not relate to the amount of money you earn as, say, a Chief Financial Officer, but we know that there’s a very strong correlation between your height. The taller you are, the more you earn as a Chief Financial Officer even though there’s no relation to the job with height. And so, we know that humans, we all have inherent biases even if we try not to. That’s actually why I’m a big fan of the phrase, “collective intelligence” and what collective intelligence is. How do you arrange both human and technology nodes so they make smarter, more intelligent decisions without, I mean, you can never remove bias, but as less biased as possible? So, I think it’s worth talking about not only doing pioneering projects on artificial intelligence and learning what works and doesn’t work, but also doing experiments on collective intelligence that is a combination of humans, as well as technology nodes, to ideally actually begin to remove bias from both groups.

Michael Krigsman: So is this issue here the fact that we’re now asking machines to make decisions that people otherwise would have made regarding judgement? Is that the issue that’s kind of driving the ethics? What’s driving [it]?

Kay Firth-Butterfield: Certainly, that’s one of the issues. And if you think about what Europe is doing with the general directive that will come into force next year, so very soon, they’re saying, “Well, we want transparency, we want openness.” So, if a machine is making decisions that adversely affect citizens of the EU, we want that machine to be able to explain itself, because the human would have been able to, and so therefore the machine would be able to. So, I think it’s very much around that human-in-the-loop notion. That previously human beings were doing this, and now we are increasingly giving over these decisions to our artificial intelligences.

Michael Krigsman: But David …

David Bray: Just a bit on there real quick. I was going to say, and I think, I would even go one step further. That it’s not just about handing over judgement and decisions to a machine that a human would do otherwise. It really is about the loss of a locus of control, either a loss of a locus of control for the individual. So, when you’re in an autonomous car, you know, you are not driving; the car is driving, unless you have the ability to stop in the next … [garbled text], but again, within milliseconds that might not be possible. It’s really about are we handing over control to an entity that we are willing to trust that will be as fair, if not more fair than a human. And that’s where it gets to what Kay said with Europe. The interesting thing with the Europe question is it applies not just to artificial intelligence but to what they call “autonomous systems”. So, the question is, “Will this require companies like Google and Facebook to be able to explain why certain results showed up at the top of the page as opposed to the bottom, and are they actually going to be willing or able to do that?” Because, that gives them their search algorithm, their ranking, in some respects intellectual property. And it’s going to create some interesting challenges of how much are companies actually going to be able to explain why the system is doing things a certain way, and at the same time protecting intellectual property. And I think it’s going to be the interesting experiment for the next two or three years is, “How can you do that and at the same time, preserve possibly your unique advantages in the organization?”

Michael Krigsman: But David Bray … Please, let me … So David, let me just interject here. So how is this different from what currently is happening with existing technology, because Google and many other companies do personalize the data that is presented to us, and so these challenges are there. So, why is AI any different?

David Bray: So, I think it’s just the scale at which it may be used, and the scale and the impacts of the decisions. I think we’ve always had, well, there’s always been the ability to tailor your experience even before the Internet in terms of what services were provided to you. People were making sense by hand what things you should receive in the mail in terms of ads, or what was called “automated data processing in the 1970’s. And it’s interesting to note that as Kay mentioned about the law, obscenity laws came before privacy laws, and that obscenity laws came about in the late 1900’s because people started moving in the cities. When people were living closer together, now they realize they might look out a window and see something they don’t want to see. So, that led to obscenity laws. And then privacy laws came back in the 1970’s when you started doing automated data processing. And again, these machines were nowhere near as fast as what we have today, but that somehow there could be a correlation of “This person lives at this address; they’re getting this type of heart medication; they also are on this type of insurance.” At what point do you need to say, “Well, those are correlations you shouldn’t draw unless that person is giving consent?” So I think artificial intelligence, much like those things that came before, it’s just the scale and the impact of what this machine might be able to make decisions that will impact your life will be. So you’re right it’s the same trend. But, I think it’s the sheer scope and impact that I think we need to take into consideration.

Kay Firth-Butterfield: And I think it’s coupled with things that are going on in our society, which gives it more, a bigger reach. Say for example our aging population. You know, if we decide that we might go the same route as Japan, and introduce more artificial intelligence devices in the form of robots for example into our elder care, then that’s going to make the technology so ubiquitous that the scope is so much broader. The other way that we might go would be obviously immigration, too, so some of the care needs that we have for our elder population. And again, there’s going to be different choices around the world.

Michael Krigsman: So the issue then, is one of scale and then one of pervasiveness. Is that why the issue of, the challenge of AI ethics has received such a high profile in recent days?

David Bray: I would agree… Go ahead, Kay.

Kay Firth-Butterfield: I was going to say “Yes!” in a nutshell, yes. But I think that actually the AI ethics point really came to the general lips of media, and those people who weren’t really thinking about this, through perhaps DeepMind’s original creation of its ethics board. And obviously, you know the seminal quote from Stephen Hawking on the first of May, 2014, when he said that this could be the best thing that we’ve ever done, or our last. And I think that really captured the attention of the media. And where there were lots of us thinking about these things before, it’s become so much part of a more public conversation now.

David Bray: And I would build on that and say that I do think it’s the winning of Jeopardy by Watson, the winning of a Go championship; there’s been a series of events that are making this much more real to people. If you think about it, how many of us in the last ten years have been on a plane where at some point in time, and probably for a majority of the flight, the plane was on autopilot? And none of us were running around saying, “Oh dear, this plane is being flown by itself!” You know, it was always there in the background. It’s just now becoming increasingly visible to people. Sure, it’s actually raising interesting questions of: Will this impact employment? Will this impact jobs ─ the nature of work? And so, it’s raising a lot of interesting questions. I mean, the good news is we’re talking about it in some respects before the technology’s even able to do some of the things that people are claiming it might be able to do in the future.

Michael Krigsman: Kay Firth-Butterfield, you are one of the top legal scholars in the world and ethicist, and thinking about these issues. And so, when it comes to AI ethics, is there kind of a framework, or an approach that we can use to break it down and look at the problem?

Kay Firth-Butterfield: I think that the way that I have always seen it is that we need to be thinking about responsible design, and also, companies that create AI taking responsibility. Either we’re a nascent industry, or at least a young one, but we need to have a level of maturity around the product. And so, what I was doing when I was at Lucid.ai, was really sort of talking about the fact that we need to be thinking about responsible design from the moment that we have the idea of a product, through to the way that it’s sold and used. And so, I think it’s a continuum, and it’s something certainly that in my new role at AI-Austin, we’re going to be looking at, and working with companies who not only producers of AI, but users of AI.

Michael Krigsman: David Bray, and you have been in public service for much of your career, and have had quite a number of roles looking at these kinds of issues. So Kay talked about responsible design, really from building it in from the ground up, looking at the technology through the development, through the point of release as a product. What is your thought on that?

David Bray: So, I think I’d say i’m very supportive. I would say from my perspective, having served in public service as well as in the private sector, you can plan for something to be used a certain way, or designed a certain way and the reality is humans will find things that you never intended, both good, bad, and mundane. Unfortunately when the Mumbai terrorist attacks happened, the attackers actually used the things that you and I use on a daily basis for web searches. They used GPS. They used social media unfortunately both to plan the attacks and to execute. And, I don’t know of any engineer [who] could have changed the design of web searches or GPS or social media to prevent that from happening. And so, if we recognize that yes, design is a good part, but there’s still going to be the human agency that is going to possibly use it in ways that you never intended it and it may even be good ways that you never intended.

I really want to make sure that when we’re thinking about how we design, and actually how we begin to incorporate these things into society, how we can give people the ability to actually indicate their preferences for what they want done, either with them, to them, with their data associated with artificial intelligence. So there may be some people like, “I’m all in! I would like to have an autonomous car. I’d like to, when I retire, have AI providing care, and that’s something that I have now given my consent to.” There may be other people wanting to live off the grid and that’s also perfectly fine, too.

So, how can we continue to recognize … It’s almost an inversion of the Golden Rule, which is, you know, “Do unto others as you would have [done] unto you.” It’s almost sort of the interesting tweak to say, “Do unto others as they will permit you to do unto them.” And then, that’s again recognizing that what artificial intelligence is, is giving up some control. It’s recognizing that something else is making a decision, and in some respects it could be the same thing for a human, but it’s letting the human that is having those actions occur, so it has the ability to indicate their preferences as to what they’re comfortable with. And ultimately when you do do those things when it’s in the public space ─ having openness and transparency ─ so, as Kay mentioned, it’s not just being able to explain why the machine made a decision, but also be able to indicate: What was its range of possibilities? What is it actually considering? What is it not considering when it makes these decisions? So, we can again have some informed understanding about the scope and sheer impact of artificial intelligence.

Kay Firth-Butterfield: Well, I’ll just echo some of those things. I think that everything that David just said is great, and really important, and leads to the need for us to have a much more open conversation about some of the things that we’re doing. One of the great things about having this great conversation with you, Michael, is that we’re reaching people who will be using AI and we’re able to have this interdisciplinary conversation, which is so important, that we have at this level and at a wider level.

Michael Krigsman: So, Kay, this issue of the unintended consequences of AI, of the use of AI, really any other kind of technology. We don’t know in advance how people will apply these technologies. How does that inform the shaping of laws, policy, and the ethical thinking as well?

Kay Firth-Butterfield: Well, yes of course, you know, with every technology that we’ve ever built as humans, there have been bad actors. And so, my raison d’être when I’m thinking about this, is thinking about things that we can do to be as safe as possible, and to educate people correctly in the use of the technology. But, I agree with David that there are going to be bad actors who are going to use technology in bad ways. The best thing we can do is try and stay ahead of those people doing those things. It sounds like a cop-out answer, but it’s, you know, since someone invented your rock, or picked up a rock and hit somebody else on the head with it, we’ve been having this trouble as human beings.

David Bray: Yeah, and I would actually reinforce what Kay’s saying. I mean, when the car came out, that allowed interstate crime, which was something that had never been possible before. I mean, you could not potentially drive to a state that you weren’t living in, commit that crime, and drive out and the local law enforcement wouldn’t know who you were because you were not a resident of that city. Does that mean we shouldn’t have cars? No, but I think that’s again, we should recognize that again, it’s how we humans choose how to use things, whether it’s good or bad, that will have impacts. What can we do as Kay mentioned, to educate the public, to ideally make it available to as many people as possible. And I think it gets to another ethical dimension that’s worth talking about, which is I personally would like to see artificial intelligence be available to as many people as possible. So, it’s not just a niche only available to a few. And so, I applaud efforts like OpenAI and other endeavors that are really rolling it out so it can be used used by everyone and it’s not limited to a few niche actors, because I think that’s going to be so key to making sure we can have these informed conversations. I would not be surprised, I hope, in the future, you have students as early as elementary school and middle school beginning to do experiments with artificial intelligence so that as they grow up , they are much more aware of what it can or cannot do, and how it can enhance their lives.

Kay Firth-Butterfield: And I think that’s really an important thing because, you know, one of the things we have been talking about is taking some control for ourselves as individuals. And unless we empower people to do that through education, then people are not going to be able to take back that power. And so, and also I think that there’s an issue around what we’re seeing in social media at the moment. I have seen a lot it of Twitter in the last two days that people are saying, “Oh well move. We have to defend our privacy.” And there’s a lot of fear of surveillance ─ switching to Tor, and more secure uses of email and things like that. That is not a positive sign for the way that some people in our society are thinking about artificial intelligence.

Michael Krigsman: Well of course, there’s also great concern that the robots are going to be taking over our jobs, and especially in light of the political climate today, that’s particularly so, particularly pronounced, those concerns. And so, what about that? That must intersect the ethical perspectives in one way or another as well. How do we think about that?

Kay Firth-Butterfield: Well, I think that we do have to be very worried about it, because AI, in my view, is a technology that will benefit mankind or humankind enormously. And, there are some great challenges that we have as humans and for our planet that we really can’t solve without AI. And so, we certainly don’t want to see a groundswell of opinion against AI by people who are losing their jobs to it. We’ve all read for the Oxford Martin study, and the Bank of America [Merrill Lynch] study that says that 47% and I think 52% of jobs in America currently done will go to automation in the next 15 or 20 years. But we have to think about the complexity of job loss, because we don’t know what the future jobs are going to be. But what we do know is that as people lose their jobs, and some think that hasn’t been done in the past, we need, and can use AI to retool and re-skill those that work that workforce to create the jobs of the future.

David Bray: So, I would build on that, too. I mean, if we go back to the analogy of when the car came out, I’m sure there was a large portion of the world’s population that were involved in raising horses and taking care of horses and things like that. But, that didn’t mean we shouldn’t not recognize the car as an advantage, and because people were worried about losing their jobs taking care of horses. And so, I think this raises a question about as jobs are lost because they can be automated, what do we as society owe those people whose jobs have been displaced, to help them re-tool, retrain as best as possible for something else. And the jury is out as to whether more jobs will be created vs. destroyed as a result of artificial intelligence. So, we need to monitor them and be aware of it. We must also be aware of there is what’s called the “unemployment effect” on people’s health, which is we humans need to have a purpose. And so, a future in which we don’t need to work because artificial intelligence is doing everything may actually not be a nirvana as it sounds like because we won’t find purposes. Or we may find purposes in advocations as opposed to vocations. But that’s a collective conversation we need to have, which is, “Where are we going together as a society? How can we make sure we bring as many people along?” As Kay said, ideally make it so they’re not as fearful of artificial intelligence.

I personally think the future is really going to be about pairing humans with AIs. Right now, artificial intelligence is a lot like a five year old. So, for example, if you have a five year old, none of us teach a five year old specifically to speak, sing, subject, verb, and object. We just expose the four- and five-year old to enough language before they actually begin to construct sentences on their own and eventually they might say something like, “I walked to the school today.” And when you ask them why they say it that way, as opposed to, say, “To school today I walked,” the five-year old is just going to say, “Well, I never heard it said that way before.” They’re not going to have a deeper reason why. And so, I think right now, where there’s going to be plenty of automation that’s possible by machines and by artificial intelligence, when you ask the deeper question of “Why right now?” It’s just going to be because that’s what I have seen in the data, or that’s what I’ve never seen before. It’s not going to be telling you the deeper reason. That’s going to require humans at the moment to be able to dive deeper. And so, I think it’s really going to be about pairing humans and artificial intelligence, at least for the next 20 years in my opinion.

Kay Firth-Butterfield: I certainly agree with that and I think that it’s a great, great thing for us to have the augmentation of AI as humans. We’ll be able to do our jobs better, and as I say, perhaps solve some of these intractable, currently intractable problems. I think two points I wanted to just come back to on David’s comment: One is that it was easier for people who had been looking after horses to perhaps move to looking after cars. You know, grooming a horse, and polishing the car. They’re manual labor. If we are looking at a change which actually requires a change from manual labor to coding, or any of those sort of things, then that’s a much bigger gap to bridge and we need to think about how that might be managed. And also, as a historian by background, I really worry about the analogies with the industrial revolution because the industrial revolution hurt a great deal of people over a long period. And yes, we came through it and we developed something better. But, it looks as if this industrial revolution will be much faster, and we need to prepare not to hurt as many people very quickly.

David Bray: And, I think that’s very true actually because it’s worth noting that when the industrial revolution happened, and people moved from working on farms basically 24/7 to factories, and doing basically rote, repetitive actions, aside from the fact they’re doing rote, repetitive actions for twelve hours at a time is not healthy for anyone, so what was also very painful was the way society collectively dealt with that transition from agriculture to industry was actually through alcohol and gin. And so, similarly when we made a transition from the industrial revolution to the post-WWII era, in which people didn’t need to work as much, and actually worked 9-5 jobs, the interesting thing that happened with that, was there are some that actually argue the way we dealt with that was through TV dinners and sitcoms, which, while not as bad as alcohol, we still needed an outlet. So Kay’s absolutely right. It’s going to happen in a much shorter time period. It may be as big, if not bigger change. And so, having again that conversation about what do we, as society, owe each other is really key to have now, because we don’t know! And none of us know if the job we’re currently doing today in two or three years will be done better by machines.

Michael Krigsman: You know, one of the big difference I think between this change that’s taking place, in terms of the fears around job displacement vs. during the period of factory automation is when factories were being automated, they brought in robots, and people could walk into the factory and you could see, “This machine is doing this task, and it’s a physical thing and you can see how this task is now being done that I used to do, and so I understand how my job is being displaced.” However, with AI, I think part of the fear is there’s this unseen hand, there’s the computer that’s a black box and we have no visibility or transparency into it, and it’s changing things, it’s making my job, or I have the fear it’s making my job go away. But it’s not tangible. And that changes the psychology of how people relate to the technology.

David Bray: Yeah, I would agree. My experience is, again, I previously worked in the Bioterrorism Preparedness Response Program, so we dealt with bioterrorism. And what makes bioterrorism such a challenging subject is that it is not seeable. That if you say something bad has happened, even if you haven’t done anything, the fact that it’s not seeable makes people worried, makes people fearful, and makes people worry something’s occurred. And so, we humans don’t do well with things that are invisible. And right now, most artificial intelligences are not written in a way in which you can easily show what they’re doing. Like you said with the factory example. So I think part of the interesting ethics of design going forward is, how easily can you elucidate both what the machine is designed to consider - recognizing again that it’s not going to be like A+B+C+D. That’s not what artificial intelligence does. It’s goal-bound. It’s often exploring a space much larger than you can express in a diagram. But, something that can help people understand what it is possibly doing, what it is not possibly doing in order to help people overcome that possible fear factor.

Kay Firth-Butterfield: And I think that that’s interesting because actually you have two sides of the equation here. When we have the AI that can’t be seen because it’s locked away in our computers, or in the “black box” as it’s often talked about. But, when we actually do put AI into robots, it’s very interesting because we then see them as being created in our own image. And I think that that’s really interesting. You see robots being called, and the people relating to robots almost as if they’re humans.

David Bray: Right, yeah. And well even with computers, how many of us have wanted to hit a computer because it did something we didn’t want it to do, thinking it would somehow respond to the fact that we hit it. But, you’re right, there are these cases of young children being educated through a robot, and then they become their friends and they hug them. So, we do anthropomorphize machines if we can see them.

Kay Firth-Butterfield: And, just I was reading today that Google’s looking at cybersecurity, and had named the three algorithms with human names, that they were using. [Laughter]

Michael Krigsman: So we want to have warm, fuzzy AI algorithms that make us feel good. We have, really, just a couple of minutes left, and so let’s just finish. Kay first, and then I’ll ask David just in a minute: what advice and suggestions do you have for people who are thinking about the law in, and the evolving law in regard to AI?

Kay Firth-Butterfield: Well I think the advice to lawyers is that very soon, you will be receiving… You will see those cases coming across your desk, and you need to get up to speed around artificial intelligence. And, what’s going on in artificial intelligence now, I think just going back to that job creation thing, actually there are going to be a lot of jobs around, so we’re not going to kill all the lawyers by automating them just yet, because we are going to see experts needed in court. For example, instead of cross-examining a driver, we might have to cross-examine an algorithm, a.k.a. an expert on the system. If you are in any business, you need to be looking at what AI can do for you, and what the impact of AI will be on your business. So there are two pieces of that, because I genuinely believe that AI will change everything. And if you don’t start looking now, you will be too far behind.

Michael Krigsman: And David Bray, your thoughts on guidance for policymakers who are looking at the policy, the public sector policy, and regulatory side of this. Any thoughts or guidance for us, very quickly.

David Bray: So again, I’m wearing my Eisenhower Fellow hat, not my FCC hat. What the conversation I had in Australia and Taiwan is, cloud computing in some respects is the appetizer, artificial intelligence and the Internet of Everything is really going to be the main course that we’re going to be consuming over the next five years. And, I don’t know if I can necessarily give advice necessarily to policymakers, but I’ll say what Kay said. Any organization and any entity should recognize that this will disrupt how you operate and it’s a question of whether or not you are very intentional about it. Or, someone else is going to do it to you. So, start on that journey now. Start having conversations. And if there’s one thing I really call out, it’s look at the OpenAI effort and other efforts like it that are trying to make this open and available to people as a place to try to either begin experimenting, or if you don’t have the time to experiment, maybe have some of your employees begin to experiment what’s possible. Because, we’re only going to get the expertise we need to know in this era through the experiments that we need to do with artificial intelligence.

Kay Firth-Butterfield: And I think just to quickly add to that, we need to have more networking. We need to talk about this more. So, thank you very much for this opportunity.

David Bray: Yes, thank you Michael for the great service!

Michael Krigsman: Well, thank you two! This has been an amazing conversation, and in about a week, we’ll have the transcript up on the CXOTalk site, and you can dig in and watch the replay. Just a tremendous amount of information. You have been watching Episode #203 of CXOTalk. Our guests today have been David Bray, who is here in his Eisenhower Fellowship… “wearing his Eisenhower Fellowship hat,” is the right way to say it, although he’s also the CIO of the FCC. And, we have been talking as well with kay Firth-Butterfield, who is truly one of the world’s leading experts on the law and ethics of AI. And, a clear message has been that AI is going to be changing a lot of parts of our lives, and for all of us regardless of the job that we do, the time to start learning about this, thinking about this, and understanding more of it, that time is now. So, thank you so much, and we have another CXOTalk tomorrow, actually. So join us! Thanks so much everybody, have a great day. Bye-bye!

Workday in Focus: HCM and Financials

  • Episode: 201
  • |
  • Topic: Digital Business
Brian Sommer, Founder, Vital Analysis
Brian Sommer
Founder
Vital Analysis
Bill Kutik, Host and Managing Editor, Firing Line
Bill Kutik
Host and Managing Editor
Firing Line
Jason Averbook, CEO, LeapGen
Jason Averbook
Chief Executive Officer
LeapGen
Michael Krigsman, Founder, CXOTalk
Michael Krigsman
Industry Analyst
CXOTALK

Workday is one of the leading software-as-a-service (SaaS) companies in the world. On this episode, three respected industry analysts examine Workday, its products, and competitive position in the market. It's a rare opportunity to see inside the mind of top industry analysts as they examine this important enterprise software company.

Brian Sommer founded Vital Analysis in 2007 based on the market success that accompanied his TechVentive, Inc. launch several years earlier. Brian closely follows what C-level executives think, feel and need. He is also in a unique position to diagnosis the winners and the losers in technology as he was the longest running (10 years) and most senior director of Andersen Consulting’s (now Accenture’s) global Software Intelligence unit. This position required him to pick the best possible software solutions for hundreds of clients globally.

Jason Averbook is currently a leading analyst, thought leader, consultant and keynote speaker in the area of human resources, the future of work and the impact technology has on that future. Jason co-founded Knowledge Infusion LLC in 2005 until 2012 when the company was sold to Appirio and served as its Chief Executive Officer. He was responsible for the groundbreaking vision and strategy. He served as the Chief Business Innovation Officer at Appirio Inc where led Appirio’s human capital management business. He held the position of CEO of The Marcus Buckingham Company (TMBC) from 2014 through 2016 until recently leaving to focus on his thought leadership and analyst career.

Bill Kutik is considered one of the top four influencers in the HR technology marketplace. In 2015, he started Firing Line with Bill Kutik®, a new independent broadcast-quality video interview program about HR technology. Since 1990, he has been Technology Columnist for Human Resource Executive®, also serving as founding co-chair of the magazine's famous annual conference, HR Technology® Conference & Exhibition, since it began in 1998 until 2013.

Transcript

Michael Krigsman: Welcome to Episode 201 of CXOTalk. I’m Michael Krigsman, you host, our host; and CXOTalk brings together truly the most interesting, the most innovative, the most forward-thinking experts on technology in business for in-depth and really meaningful conversation. And today, we have a really interesting show. We’re going to be focused on Workday, which is one of the most well-known of the software as a service enterprise software vendors. And we have a truly all-star panel of industry analysts, who are going to explore this topic for the next 45 minutes. And, in no particular order, to start introducing our panel, let’s begin with Bill Kutick. How are you?

Bill Kutik: I’m well, thanks for having me, Michael. My interest in HCM is 27 years old, when a short-lived magazine that I ran had the first review of PeopleSoft 1.0. And for the 27 years since, I’ve written a column about the subject for Trade Magazine and Resource Executive, started now-famous show called the HR Technology Conference, which I ran until three years ago, and now I have a broadcast-quality TV show called “Firing Line with Bill Kutick” that’s never as up to the second as your CXOTalk, Michael.

Michael Krigsman: Well Bill, your show “Firing Line” is just great. And what’s the URL for that so people can find you?

Bill Kutik: Well, they just go to YouTube and they search for “Firing Line with Bill Kutik,” you know, the whole name and they’ll get it. I mean, it’s a bit lame but that’s the easiest way to get there.

Michael Krigsman: Fantastic. And now our next guest, a star industry analyst, is Brian Sommer. I’ve known Brian as with all of these gentlemen for years, and Brian Sommer, how are you? You’re in a hotel room here in Boston, in fact.

Brian Sommer: Yes I am, and taking a break from another conference from another vendor, who shall remain nameless. My short little quick bio bit: I’m an ERP analyst, and I think I’m the token finance guy on today’s group, since I know Jason and Bill will overwhelm us all, I’m sure, with HR kind of commentary. I’ve been doing the game for a number of years. I don’t want to say how many decades, but a bunch. And I do a lot of client work with folks on things like software selections, shared service projects, and the odd ERP litigation or any true steal. So that’s my kind of story.

Michael Krigsman: What Brian did not mention, because he’s a pretty humble guy, is that in the world of enterprise software and finance, he is truly one of the top analysts and observers in the world, and that is absolutely the case.

Brian Sommer: Thanks.

Michael Krigsman: And last but not least, Jason Averbook, and Jason, hi, welcome.

Jason Averbook: Hey, Michael. Hi, thanks for having me. So, really excited about the topic today, and the workplace human capital management and financial applications, their entire platform is one that we see on fire across all of our customer base. My background is I spent 15 years in the vendor space between two different organizations; spent ten years in the consulting space helping CHROs and CEOs and CFOs really think about platforms and think about applications. And now, I’m [in] Next Venture, which is a new enterprise consulting organization as well. So today, well, I’m going to talk about human capital management and the whole workday space. Brian, I do have a dollar with me, so we’ll see how many times I can bring up finance. I do know something, do know something about finance, and the fact that I’ve got the dollar with me.

Brian Sommer: Well, you’ve sold a few more software companies than I ever consulting firms I have, so I know you know something about money.

Jason Averbook: And maybe it’s not as much of a Workday financials, but let’s go at it a bit.

Brian Sommer: Ok.

Michael Krigsman: Ok. So, Workday. Let’s begin with an overview: why is Workday important in the market? Why are we spending

Michael Krigsman: Welcome to Episode 201 of CXOTalk. I’m Michael Krigsman, you host, our host; and CXOTalk brings together truly the most interesting, the most innovative, the most forward-thinking experts on technology in business for in-depth and really meaningful conversation. And today, we have a really interesting show. We’re going to be focused on Workday, which is one of the most well-known of the software as a service enterprise software vendors. And we have a truly all-star panel of industry analysts, who are going to explore this topic for the next 45 minutes. And, in no particular order, to start introducing our panel, let’s begin with Bill Kutick. How are you?

Bill Kutik: I’m well, thanks for having me, Michael. My interest in HCM is 27 years old, when a short-lived magazine that I ran had the first review of PeopleSoft 1.0. And for the 27 years since, I’ve written a column about the subject for Trade Magazine and Resource Executive, started now-famous show called the HR Technology Conference, which I ran until three years ago, and now I have a broadcast-quality TV show called “Firing Line with Bill Kutick” that’s never as up to the second as your CXOTalk, Michael.

Michael Krigsman: Well Bill, your show “Firing Line” is just great. And what’s the URL for that so people can find you?

Bill Kutik: Well, they just go to YouTube and they search for “Firing Line with Bill Kutik,” you know, the whole name and they’ll get it. I mean, it’s a bit lame but that’s the easiest way to get there.

Michael Krigsman: Fantastic. And now our next guest, a star industry analyst, is Brian Sommer. I’ve known Brian as with all of these gentlemen for years, and Brian Sommer, how are you? You’re in a hotel room here in Boston, in fact.

Brian Sommer: Yes I am, and taking a break from another conference from another vendor, who shall remain nameless. My short little quick bio bit: I’m an ERP analyst, and I think I’m the token finance guy on today’s group, since I know Jason and Bill will overwhelm us all, I’m sure, with HR kind of commentary. I’ve been doing the game for a number of years. I don’t want to say how many decades, but a bunch. And I do a lot of client work with folks on things like software selections, shared service projects, and the odd ERP litigation or any true steal. So that’s my kind of story.

Michael Krigsman: What Brian did not mention, because he’s a pretty humble guy, is that in the world of enterprise software and finance, he is truly one of the top analysts and observers in the world, and that is absolutely the case.

Brian Sommer: Thanks.

Michael Krigsman: And last but not least, Jason Averbook, and Jason, hi, welcome.

Jason Averbook: Hey, Michael. Hi, thanks for having me. So, really excited about the topic today, and the workplace human capital management and financial applications, their entire platform is one that we see on fire across all of our customer base. My background is I spent 15 years in the vendor space between two different organizations; spent ten years in the consulting space helping CHROs and CEOs and CFOs really think about platforms and think about applications. And now, I’m [in] Next Venture, which is a new enterprise consulting organization as well. So today, well, I’m going to talk about human capital management and the whole workday space. Brian, I do have a dollar with me, so we’ll see how many times I can bring up finance. I do know something, do know something about finance, and the fact that I’ve got the dollar with me.

Brian Sommer: Well, you’ve sold a few more software companies than I ever consulting firms I have, so I know you know something about money.

Jason Averbook: And maybe it’s not as much of a Workday financials, but let’s go at it a bit.

Brian Sommer: Ok.

Michael Krigsman: Ok. So, Workday. Let’s begin with an overview: why is Workday important in the market? Why are we spending our time? Workday has gone public their revenue guidance is about 1.6 billion or so, this year. Why is Workday important in the market? Who wants to start?

Bill Kutik: I’ll start. Workday’s important in the market because it was the first true SaaS vendor in HCM. Little-known to people outside, we in face had hosted applications in the late 90’s, mostly recruiting applications from companies like Taleo and Brassring, which always drove me crazy when Marc Benioff proclaimed his software to be the first hosted SaaS software. Not true! We have for a while. But Workday was the first one to be really rigorous about it, and caused their competition, SAP, Successfactors, and Oracle, to line up behind them and into the cloud. I remember vividly, as I’m sure Brian does, hearing Larry talk about how the cloud sucks, and Oracle’s never going there, and they’re certainly there now.

Brian Sommer: I also remember them, how Brian’s talking about how multitenancy was a bad idea, and we go on and on. As far as their relevance in the marketplace, I would argue they were formed in 2005, and what was also really interesting is unlike so many of their competitors, they have the luxury of not worrying about bringing along an install base of customers who are on some very old, antiquated products and trying to help them step-by-step, through a thousand of incremental marches, modernize their applications. That’s really tough and expensive for customers to do, and it’s also tough for a software company to do it, because they’ve got so many other customers out there running on so many different versions. If workday becomes a multitenancy, essentially, probably 99.9% of all their customers are running on the current release within probably 60-90 days of the new release coming out the door. That’s the value and the beauty of it.

The other thing I think is really important for people to realize, is that Workday was actually built using a memory database technology. They have subsequently added additional capabilities for Hadoop, and they even used the traditional relational database storage mechanisms for persistent storage. But this was a product that was designed for a much more modern era. It was not designed backward-looking when technology was so constrained, and there was no, you know, you have this ability to process vast amounts of information, in very different ways than what you did before with the old legacy products.

Bill Kutik: Brian, how did God manage to create the universe in seven days?

Brian Sommer: They started that in 2005.

Bill Kutik: No, it’s a joke Brian. And it’s because he had no install base.

Brian Sommer: Yeah.

Bill Kutik: So, a clean sheet of paper is a luxury that companies occasionally have, and it’s pretty great!

Jason Averbook: And Michael, if I could just get a word in, which I know will be hard for me. I’m going to be like, which debate camp will be hard for me. I think it will be hard for me. So, I’m going to need your help with that. I think the biggest thing about Workday that’s most relevant, and the technology stuff aside because the technology is really important, is Workday is the first organization, the first vendor, that actually brought the work to the worker. We tried with little things like self-service, we tried with little things like pushing things out, but the cloud and the concept of the cloud, where I didn’t have to install software on devices, I didn’t have to think about it, and I actually designed the software for the worker: not for the HR function, not for the design function but only for the worker. Workday said, and the have that realization, that the only way I’m going to get good data from an HR and finance standpoint, is if I design the applications from the worker into the HR and finance function, instead of the HR and finance function out to the worker. To me, that’s a hallmark of what Workday brought to us. The whole market has followed the law, in its own unique ways, but to me, that was the hallmark of the Workday solution.

Michael Krigsman: But Jason, Workday was not the first SaaS company, so maybe put a finer point onto what they did.

Jason Averbook: Well I think what’s very interesting, and it’s a great, great point. Thank you. Workday wasn’t the first SaaS company, but Workday was the first SaaS company that actually designed their solution. Once again, like I said, for the worker not thinking about the HR department and the finance department first. So the first SaaS company took old software and put it online; put it online in the SaaS world; took old processes and put them online in the SaaS world. What Workday did is Workday actually reimagined those processes, put them online with the worker being the center of it, and then having HR and finance be there to consume that data and to use that data in a way that drives business decisions.

Brian Sommer: Michael, if I could go back on one. You asked the history, the historical perspective on why it’s important. I think anytime Dave Duffield decides he’s going to get into the software business, it’s going to send some shockwaves to the market from their competition, because Dave, this is his fourth HR software company; Information Associates, then you get Integral, then you get PeopleSoft, then he has Workday, and …

Bill Kutik: There’s actually a fifth, Brian, but not worth talking about.

Brian Sommer: Ok. But the point being that the guy’s always been successful with these things, and every time he did it, it would then cause a loss of market share, or whatever, for some of the established vendors in the market. And it was also interesting because when he would do these things, it usually coincided with signal changes in the way that technology in this space is moving their offering. And you know, PeopleSoft really made its hay during the client server age, Workday in the cloud age, you could go backwards in support. I think, I don’t want to under-appreciate the importance of what the original founding team behind Workday did, and that it basically created a whole new kind of business, even using some of the talent and brains that had successfully built some of the other companies before.

Jason Averbook: And Brian, as someone who was there from a PeopleSoft standpoint, I think one of the things that Dave, and Neil, and that team is they learn brilliantly, from I’m not going to call them the mistakes, but from the technology that they were dealt with at the time when we built PeopleSoft to where Workday is now and the technology that it has available. They haven’t just taken it and said, “Hey, let’s move it over to the new technology.” They actually did it in my mind a great job of learning from the mistakes, and those mistakes being, “Let’s not customize everything so I can’t upgrade it. Let’s actually not build point-to-point interfaces but let’s truly think about integration in a unique and different way, and let’s truly think about how we design a solution that focuses on, like I said, the worker, not on the function.” And I think if you think about those three things that Workday’s done a great job of saying, “What can we learn from where the ERP space was, to now where the ERP space is today?” And what that’s done, is it’s brought the rest of the market up in a tremendous way. That whole Workday play has made us all better from a tech and consulting standpoint.

Bill Kutik: Jason you were there at PeopleSoft and you’re probably aware of the fact that PeopleSoft did commit the mistake you just described. They took basic functionality from integral and slapped it into client server without really redesigning it or making it special or different, because of the technology. This is not a mistake that Workday has made. Workday has really used the new capabilities of the technology that it has to do what you just described doing. Although, I’m not sure they were doing that from day one, I mean you’re very eloquent as you are on Firing Line with Bill Kutik about this issue of the work being brought to the workers. Was that true at Workday early, early on? I mean it’s certainly true now.

Jason Averbook: I believe it was a core design principle. I think that PeopleSoft and employee management self-service wasn’t going to work the way it was being pushed out; the adoption wasn’t there. We have to think about the experience; the experience of the worker at the core, and I think that’s just a different design principle that was from day one at Workday. And it still holds true today. And like I said, let’s not just talk about Workday, but now the rest of the industry has followed a lot. I give them credit for truly ushering that into the enterprise space.

Bill Kutik: I wouldn’t deny them that credit either, but I would point out to Brian, which he already knows, but to the audience, that though Dave started it, and Dave is the first one to tell you that he’s a technologist, and he’s now a functional person, and that new technologies get him excited, which is what happened at PeopleSoft, what happened at Workday. He’s pretty much been not terribly involved in the company for a good five years, and while he was once co-CEO with Aneel Bhusri, he’s no longer that, and I don’t know, is he still chairman of the board? But, it is Aneel’s company now.

Michael Krigsman: Right. But guys, let me ask you a question. So, you were talking about placing the customer at the center of the world, and I’m really interested in the corporate cultural dimensions of that. Why didn’t earlier software companies take that step? Is it a function of technology? Is it a function of the corporate culture? So maybe just your thoughts on that point, please.

Bill Kutik: I don’t know why other companies didn’t do it, but Workday truly does have a unique culture, similar to the PeopleSoft culture, which Dave will say, puts employees first. Every other company will talk about how they put customers first. Workday says “Employees first, because if employees are happy, they will make our customers happy.” And the fact is, at the last rising, Aneel announced that they got a 98% customer satisfaction rating from some outside agency…

Michael Krigsman: I’m sorry, that’s Aneel, for the people who don’t know …

Bill Kutik: That’s Aneel Bhusri, the current CEO of Workday.

Michael Krigsman: The current CEO of Workday, yes.

Bill Kutik: They got a 98% customer sat., and I would challenge any software company in the world to meet that! I mean, software, particularly enterprise software is usually something you’re pissed off about, not something that you’re happy with. And so, I think that comes from the culture and other things.

Brian Sommer: You know, let me pile on a little there. Customer satisfaction, or net promoter scores and the ERP space are notoriously terrible. And they’re terrible because either the products were a whole lot more expensive and more difficult to implement than anybody actually believed coming in, or more importantly, the vendors have such a notorious culture going for after their own customers doing what an attorney friend of mine calls “shale fracking,” they try to go in there and break up the wallet of the customer and get every little drop of money they can out of them. You’ve got a lot of Workplace customers who’ve been exposed to relentless numbers of software audits in the past by some of the older vendors, and they hate those vendors for that reason. They don’t like them during the depths of the recession in 2008, of 2009, of 2010, when companies may have lost half or two thirds of their revenues, and/or their employees, and they still couldn’t get a break from the old, established vendors on increases in maintenance costs and everything else.

There’s a reason why the customer sat. scores are so low in the competition. Workday, because of the way it’s subscription-based technologies are priced, is based on the consumption. Yes, they do have some long-term contracts they’ve cut with some customers and so forth, but as long as they don’t get greedy, they probably have a really good chance of keeping a really happy, satisfied customer. Now related to that, they continue to keep pumping out releases at a relentless pace, even though they now bundle them down to, like, three good ones every year. The fact that people get a lot of good, new functionality quite frequently and that the vendor is maintaining that version of the code for them, instead of their IT department, you’ve got customers that are very happy because they never have to wait on their own internal IT department to implement this backed up technical data. So it’s great!

Jason Averbook: Michael, if I could, I mean I think the thing that’s really important here, and Workday was one of the first, and you’ve seen vendors follow along with this. In the SaaS space, what I have to do is I have to drive customer satisfaction, and not customer satisfaction at the level where, “Hey, I’m mediocre, I’m okay with the software.” I have to drive customer satisfaction in a “customer love” kind of way. “I love” is a soft, touchy word for your show, that may not be used a lot, but in this case, I have to get my customers to love me. Dave Duffield and Aneel Bhusri and what Bill says Dave hasn’t been involved for the last five years. Dave still lives and breathes in many of the people that every single day wake up to make their customers love.

Bill Kutik: They’re absolutely right. You go to Rising, and you feel like you’re at a hippy love-in.

Jason Averbook: And by the way, a lot of other vendors in the space have gotten a lot better at this. So, I don’t think this is a … I mean, workday is great. As a former PeopleSofter, I feel the same way, but now we’re starting to see other vendors learn from it that in a SaaS world, I don’t drop of the software and leave. In a fast world, I have to make sure that I am keeping the customer happy. And if I am not keeping the customer happy, and in lots of different ways, that customer’s going to fall back to mediocre, and there are too many choices in the market today.

Michael Krigsman: Okay, but guys, wait a second! Wait, wait, wait…Wait a second. Hold on, hold on. As the moderator, I’m going to take my privilege and jump in here. So, yeah Workday is great, but was Workday built by God? I mean, nothing in life is perfect. So what are the challenges that …

Jason Averbook: Yeah, Michael so if I can get started, I mean, this was turning into a little bit of a Workday lovefest, which is not good for anyone. Because while Workday has done a lot of these things, anytime you’re rolling out enterprise tools, I always say it’s like an organ transplant. You’re basically taking out an organ and putting in a new organ. You’re doing a heart transplant. And if you think about all the things that are connected to the heart, it’s crazy! Absolutely crazy. So, when we think about Workday, what Workday is, you have to think about Workday as a core solution for HR and finance that serves as a master data tool. Now, it has so many other things that it touches, that where Workday itself doesn’t fall down, but where it falls down in the customer’s eyes, is when the customer starts to implement it without a given strategy, without the skills to sustain it, without the concept of being able to run and optimize it, and innovate it consistently. And when you have systems integrators that jam it in to go live an X period of time, without thinking about what the bigger, longer outputs are, that gives Workday a black eye. And I always say this to my clients, that the easiest person to blame in all this stuff is the vendor. Why? Because they’re not sitting in the table, they don’t have feelings.

So, there’s lots of things that Workday needs to do to make sure that it’s ecosystem gets stronger. There’s lots of things that Workday needs to do to make sure that customers adopt more. But, I think that’s something every single SaaS provider needs to do. So no, Workday is not perfect. Not all their capabilities are strong, let’s say global payroll is not as strong as X and Y and Z, you have to think about fit for your organization. But that’s something you have to do with every enterprise tool, every heart transplant you’re doing today.

Bill Kutik: Michael, I’ll tell you something else that’s wrong, and it’s so oddly a repeat of a bad development at PeopleSoft. There was a moment at PeopleSoft when the salesmen got so arrogant that when a selection committee cut them out, they would go over the committees head and say, “Hey! Your committee doesn’t know what they’re doing! I’m PeopleSoft! They just got rid of me!” Well at Workday now, there’s the feeling of foot that everything we do there is perfect, and everything we do there is first, and nobody else is doing it, and nobody else could possibly compete with us. And, I fear for them, that that may lead to the similar kind of arrogance, which there’s a lot of strong DNA passed from PeopleSoft to Workday. Incredibly strong, not to mention the number of people there who’ve worked at PeopleSoft. And you know, they should be on their guard against the bad things they know happened.

Michael Krigsman: That is always a risk for success. For anybody that is successful. Workday emphasizes its platform. It’s not the only software company to do that, but it really presents the platform in a central way. So, what is the importance of platform? Why is it important to Workday? Why does this matter to customers?

Brian Sommer: I’ll weigh in on this. On the platform: theirs is an interesting one, in that it predominantly uses a number of open-source technologies, which gives them an incredible cost advantage over competitors. They can scale and add customer, after customer, after customer and they owe no additional fees to some third-party systems software company. So that’s a good thing. Number two is the platform only really has to support one technology stack and one set of code. So, many of their competitors have multiple different product lines that they’re supporting. In some cases, one vendor has promised to support old applications on the old platforms in perpetuity. That just adds cost to the vendor. Cost, you’ll have to get eventually passed down to the consumer or the customer, or whatever you want to call the vendor. They don’t have that. They’ve got one stack, one set of technologies. And the architecture of this stuff, to run predominantly in memory. So now, they’ve run all these additional extensions so that the product line can support other types of data, not just structured, heavy order kind of database transaction and information.

With that, there’s been a big push from customers and integrators. They wanted Workday to open up their platform for years, so that third parties could start building extensions or wholly surround-sound kind of applications around the Workday suite. And based on what we heard at Rising a couple weeks ago, it looks like they’re finally coming around to opening up a platform for third parties, which I think will usher in an interesting new generation of new, additional add-ons that will drive sales for the company even further.

Bill Kutik: The other thing that’s impressive is with their object-oriented programming, it makes them very nimble in creating new applications as for instance, they just created a video function which will be used in learning. You know, the five minute video’s considered the sine-qua-non right now of learning objects. And then they immediately said, “Well, after we’ve used it in learning, we’re going to put it in recruiting.” And I haven’t seen other vendors be that nimble when they create new functionality. And Workday does that all the time with reusable pieces.

Jason Averbook: And Michael, could I just add one thing real quick? On the platform? Real, real, real, real quick? The concept to me of platform really ties into the fact that the worlds of HR, finance, and IT have shifted, And what the platform allows is it allows that shift to happen. So in my old world of applications, and this happened across the board, where 10% of the deployment responsibility was from the function, 90% was from IT, what the “platform” to me has done, is it allowed 70-80% of responsibility to go to the function. The people that are truly establishing business rules, the people that need that agility, and then 10-20% tying back into IT being able to support it. It allows HR finance to have much more control over how its processes and tools work, and allows IT to be much more strategic in how it supports the enterprise. I think that right there is the holy grail of the platform.

Michael Krigsman: And we have a question from Twitter, and this is actually from the hacked CXOTalk account, which is being managed by my friend Elizabeth Shaw. And Elizabeth is asking, “What is the role of technology in driving your supporting workforce stability and improving the workforce? And are there other factors that are really more important than technology?” So the relationship between technology … So, in other words, why should we really even care about all this?

Jason Averbrook: So Michael, if I can just jump in real quick, 90% of a deployment of a solution has nothing to do with technology. It has to do with process, it has to do with change, it has to do with culture, it has to do with marketing, it has to do with what my processes around HR and finance stand for? But at the end of the day, the way to get stuff done is through technology. The way I touch the people is through the technology. So, complete … her comment is so spot-on. You have to have that process-people aspect in everything you do. And you have to have it formed up-front. And the technology is just there to support that and deploy that. So, it’s totally important. It’s totally important to create that experience that you’re trying to create from a people and process standpoint. But know that technology does not create that.

Brian Sommer: Yeah, but what will happen with all this new technology, just putting the microscope on the HR functional: if you look at all of what’s in the stack that Workday has with all their in-memory and other capabilities, they have the ability to incorporate huge amounts of outside, non-transactional data. And they have this technology stack that could be exploited by HR groups that have more skills than just filling job slots that the recruiting function is responsible for. If they have more data scientists they can do more algorithms, more analytic tools, they can do a better job of identifying and coordinating talent that they want to bring into the company. And, in fact, they’ll be managing things that require knowledge of algorithms, artificial intelligence, machine learning, and on, and on, and on. You know, the point of this is not to do a recitation of three-letter acronyms, but it’s to point out that the HR function, the people within HR, are fundamentally going to be changed. Either they’re going to have to acquire new skills themselves, or they’re going to have to bring different kinds of people into HR to use some of these new technologies. And if you only look at products like Workday, or any of the newer solutions in the HCM space, or finance space …

Finance is actually more intriguing in that regard. You tend to lose sight of the fact that … We’re not here to automate just the old accounting transactions anymore, for example. We’re actually here to stop major fraud in a company, and the way you do that is by analyzing a whole bunch of other data that never made it into a general ledger in the first place. And that’s where the future’s going to go, and that’s the interesting people impact of these new technologies, is around the new uses of the new capabilities that these newer platforms can deliver.

Michael Krigsman: And what about the fact that you have… So Workday has got HCM, it has financials, it now has learning as well. And, Workday Student. But, focusing particularly on HCM and financials for the moment, what are the advantages of having them integrated into a single platform?

Bill Kutik: Well, they … The newest application from Workday is called simply Planning. And it for the first time for them, incorporates elements of HCM and finance into one application. And, it makes perfect sense, I mean, how can you be deciding to hire X number of people without knowing the financial repercussions of that? How can you know whether or not you can afford to hire Y number of people without having the finance behind that? The fact is that HCM finance has been sold as a bundle since mainframe days, I mean, last 40 years, and that continued during client server, and then there was a pause, a little pause, during the cloud because HCM got to the cloud first, and finance didn’t get there for another three, or four, or five years. But, those two that have now been rejoined in the cloud, and Oracle’s suddenly selling them together, and Workday’s working very hard to sell them together. I’d say these success factors have some elements of complexity with its SAP install base, but it now has the multitenant version of finance that it’s selling with its cloud HCM. So, it’s sort of the most natural order of things in back-office software for the last 40 years.

Jason Averbook: Yeah, and Michael, I think what’s really important about this topic is we’re onto the next generation of what this means. So, before, in the ERP space, this meant interfacing data from solutions to solutions, or maybe if we’re really sexy, integrating data from solutions to solutions.

Michael Krigsman: I like that. Interfacing vs. integrating. I won’t even ask what that actually means, and I’m sorry …

Bill Kutick: [unintelligible] … mainframe distinction.

Jason Averbook: But Michael, hold on! We live in a world today where employees don’t work in modules. The workforce doesn’t work in modules, the workforce works in processes, and the only way to integrate processes together truly, is if they’re in a single platform. We can interface data all day long, but to integrate processes to create a seamless experience, that is hard, hard stuff. And it’s something that people shouldn’t discount. Whether it’s Workday or any of these tools, when they think about platforms, why should things be in one platform? An integrated experience is key.

Brian Sommer: I’m thinking… Okay. You know… But I think my learned colleagues here are maybe giving you the quick textbook or elementary school version of the problem.

Jason Averbook: Well that’s all we can speak, Brian, compared to you.

Brian Sommer: Well …

Michael Krigsman: And I know …

Bill Kutik: I’ve been in this for 34 years, Brian, tell us the revealed truth!

Jason Averbook: You’re the one that’s in the tie, my friend. You’re the one that’s in the tie.

Michael Krigsman: But he’s not wearing a jacket, and Brian, you should not let your learned colleagues fall back on jargon and intellectual cliches. You should never let that stand.

Brian Sommer: What’s really going on here, guys, is businesses today should never be buying a bunch of little best degree stuff in the finance and HR area, unless it’s for some peripheral, small add-on piece, and here’s why: Moving forward, what businesses want out of a toolset is they want a single place to find operational, financial, human capital, as well as big data and a whole bunch of other external stuff. Unfortunately, in a lot of companies, they’ve got 20-30 years of experience building what I would, if I could use the British term, a “dog’s breakfast,” lightly, loosely integrated, spreadsheet-ridden junk.

Michael Krigsman: Ok, hold on! I just need [you] to repeat that back, just to make sure we got that, and I quote: “A dog’s breakfast” of speadsheet-ridden junk.

Brian Sommer: Right. And so, you’ve got blatant piles or islands of data, stuff that’s being pumped into spreadsheets, and manipulated, and re-pumped back into something else, and that’s in the existing finance and HR world. And then when they try and go shop for new software, God help them if they recreate that same, loosely-interfaced kind of world together, when what they really need is they need to get as much integration as they possibly can from a core provider of all the ERP stuff they can get, because they’re going to have to now connect those technologies to weather data, to geopositional data, to smartphone data, and to a million cloud solutions that are powering their employees’ mobile devices among other things. So there’s social sentiment data. I can show you guys, line-by-line on a PNL, just about how to use big data to do a better job of planning and forecasting and doing your budget than what companies do today, which is rely on, “Let’s take last year’s number, add 6% to it, and tweak it a little bit.” That’s terrible. So, we need to get out of this thinking about having a bunch of disconnected finance and HR kind of products. Yeah, go buy all that you can from a single vendor, because your world is going to get changed by all the other sources of data that you’re going to need to integrate in there.

Jason Averbook: And Brian, what’s the opposite of a dog’s breakfast?

Brian Sommer: Nirvana.

Jason Averbook: Okay. So, in this world of Nirvana that Brian speaks of, the future is all about, and Brian and I, you and I tweeted about this a little bit yesterday, is all about using these AI tools, this box. And in order to use these tools, and once again, not to say HR is turning into AI or Box, but what’s really important is these tools rely on data. And what Brian is saying is if we’re going to use these sexy new tools, some of the shiny objects, or like I said on Kutick’s show, frosting on top of a cake, I have to have data in a single place so those tools can consume it. And I think that’s what we’re going to see more and more, as people look at a platform like a Workday or another one of these SaaS tools, so they can make sure that this data is right and then take it to the next level of service in Workforce.

Michael Krigsman: So Bill, we’ve got less than ten minutes left. And, what advice do you have for people in the enterprise who are looking at these products, who are looking at Workday, looking at others who are being told on the one hand, by some vendors, best of breed is the only thing that is going to save you! And other vendors, like Workday and there are others saying, “The platform is the only thing that’s going to save you!” What should we do?

Bill Kutik: Well, it’s not as crucial a question as you might think, Michael, because Workday has 100% mindshare in HCM, and any large company that thinks that it’s time for a change, Workday is on their list. In finance, things are slightly different.

Jason Averbook: Bill? I don’t want to interrupt you, but wouldn’t you say SAP and Oracle are also on the list?

Bill Kutik: Oh yeah! Of course SAP and Oracle are on the list, and they will be considered, but I think Workday just gets on there first simply because it’s sexier, it’s newer, it’s made a bigger splash.

Michael Krigsman: They’re all platforms, though.

Bill Kutik: I’ll include that. I think the big problem in finance, and Brian will back this up I’m sure, is that the finance guys have had the budget for years, so they got no pain points with their software because they’ve been getting exactly what they want, because they have the money to pay for it. And, I understand, Brian can probably tell me…

Michael Krigsman: But they’re also completely risk-averse, I mean, finance… talk to a payroll person and say, “Hey! Would you like to change over payroll systems?”

Bill Kutik: No way! And, I understand also that they’re still not sold on the cloud being the next generation computing, right? How are they?

Brian Sommer: Well, funny you bring that up, Bill, because in some of the selection work I’ve done lately, I have a … I rented a lot of aging boomers who were about to retire, and their CFOs and controllers. And one of them sat me down the other day and said that he wants to retire, but he will not retire until the finance technologies have been modernized. And, his view, that he would not have been a good steward of the company because, or the finance function, because they actually have more spreadsheets, more old junk than everything else than they had when he got the job, and he needed to change that. Their company, in fact, had failed to complete two big acquisitions in that last year because their old technology, while it felt like a comfortable, broken pair of shoes, just wasn’t up to the task of twice the volume of transactions they would have going forward. So, I think there’s a lot of introspective work going on with a lot of aging out boomers, who are looking at some of their finance operations and asking themselves, “Have I been a good steward of the company?” And if they haven’t they’re going to be looking at new technology, because they cannot keep continuing with all of the stuff that may have got them through the recession, but isn’t going to get them going any further going forward.

Michael Krigsman: Jason, your advice for people who are looking at the enterprise… Your advice for the enterprise buyers: What should they do? How should they make sense of all of this?

Jason Averbook: Well, Michael, I think that what’s really important is that organizations look at right fit versus future function. I think we spend way too much time on future function, and we spend way too much time on RPs, I think we spend way too much time on saying is this vendor, is this vendor, is this vendor ready? I think if we look at the top three vendors in the space, they’re all ready, and they can all do this. I think what’s most important is how am I … I’m basically renting someone to move into my house. That’s a weird way to say it, but I’m renting someone to move into my house. And as I do so I’m going to be like, “What’s it going to be like to live with them? Do I have the ability to sustain them? Do I have the staff to sustain them? Every vendor talks about analytics, do I have anyone who even knows what an analytic is and how to read it?” I mean, there’s so many different things to me that tie into the solution other than future function. Do I have an IT staff than can support what I’m trying to do? Do I want HR and finance staff to do more configuration than the average IT staff? All of those things are important, and then, we haven’t even talked about price until cost of ownership, I mean, we’re not even going to have time to get there, but that’s another component. Where am I coming from? Where am I going? How am I going to think about TCO, because each one of the big three are completely different from a TCO standpoint.

The last thing I’m going to say, Michael, is about best-of-breed. I don’t think you rule out best-of-breed completely. I think that there is a space for best-of-breed, and I think you have to look at best-of-breed and say, “If best-of-breed drives a competitive edge, or a competitive advantage for me, that I can’t get today, I can’t get today from my platform, I’m going to put in a place, until I get the platform to where I need it.” So, you don’t say “No best-of-breed,” you say “When best-of-breed” and “How long best-of-breed,” and I always call it a “bridge to somewhere,” which is where am I going in the future.

Michael Krigsman: Bill Kutik? Thoughts on the bridge to the future for buyers?

Bill Kutik: Well, I’m not as sanguine about best-of-breed as Jason is, because the fact is that any small benefit best-of-breed may give you is going to be copied by the integrated guys in a reasonably short period of time.

Jason Averbook: But what if I need it today?

Bill Kutik: You need it today? Then if you can rent it for six months, sure.

Jason Averbook: If I’m going through a talent crisis, do I say, “Oh, sorry! I have to wait for my vendor!”

Bill Kutik: Right!

Jason Averbook: Do I want to take care of that talent crisis?

Bill Kutik: No, obviously get it today. But, how many best-of-breed vendors are there left out there, that really do it significantly better than the guys who are offering suites? There aren’t that many. And I was recently at…

Michael Krigsman: Touché, Bill; touché, Bill.

Bill Kutik: Sorry?

Michael Krigsman: I said “Touché for you!” That’s right.

Bill Kutik: I was recently at a recruiting vendor’s analyst day, and they had one of the customers there talking, who happened to be a Workday customer. And she said, “Oh, it was clear to me that they didn’t care about learning. And it was clear to me that they didn’t care about recruiting.” And I wanted to grab her by the shoulders and shake her and say, “You’ve got to do something last. Just because they did recruiting and learning last doesn’t mean they don’t care about it.”

Jason Averbook: Bill, I mean, I want to hear Brian talk about this also but these are names of modules. You’re talking about recruiting and learning as a name of a module. I’m talking about deep capability. Am I really developing the stuff today that recruiting and learning needs? These people get there. They’ll all get there. But today, what they need? Brian, like the finance space like expenses, huge area. I mean procurement, huge area. I mean, where do you tell Brian where people say, “Go with best-of-breed versus platform.”?

Brian Sommer: The counsel to those companies is always try and get as much as you can through the core vendor, and then you’ll have to probably round out for some of the other stuff that’s best-of-breed. And that’s different than what we probably espoused for strategy for years. And, someone was making, well it probably was Bill, you know, people buy software as kind of a discrete, point-in-time event that may come up only every ten years or so. And, they can only choose what is available at that point in time. If it happens to be that a software vendor is in the middle of remodeling or retooling its product line, well, that vendor probably won’t get the business during that changeover. It is what it is. It’s a point-in-time decision.

Michael Krigsman: So guys, we are just about out of time. Would you like to each take ten seconds and just add your final, final thought? Bill, why don’t we start with you? Literally just a tweet. A tweet-like statement!

Bill Kutik: Sure. I’m never again talking to my good friend Jason Averbook, after what you said.

Jason Averbook: Wrong! [laughter]

Michael, I think that because this topic was Workday, I think Workday has changed the enterprise software space forever. I think there were a lot of doubters at first. I think it changed the space, and it’s made the space a whole lot better, as far as how it’s working with customers.

Michael Krigsman: Alright. And Brian, you’re going to get the tippy-tippy last word.

Brian Sommer: I think the fun thing to watch in the next few weeks, months, and years to come will be the changes around the ecosystem around Workday, and we should expect to see a whole new list of characters who will come in to help customers implement this stuff, given that so many of the initial ones have already been acquired. So I think we’re going to see something cool happen there as well.

Michael Krigsman: Fantastic. What a great show! You have been watching Episode #201 of CXOTalk, and our focus has been an industry analyst perspective on the software company Workday. We’ve been speaking with three, and this is literally true, three of the top, most well-respected industry analysts covering Workday, covering this field in the world. We’ve been talking with Bill Kutick, we have been talking with Brian Sommer, and we have been speaking with Jason Averbook. Gentlemen, I just want to say a hearty thank you. Thank you all for taking the time.

Jason Averbook: Thank you for having us, Michael!

Brian Sommer: Take care, guys!

Michael Krigsman: And, with that hour episode, tune in tomorrow when we will be speaking with Oliver Bussmann, who is the former head CIO for the huge UBS bank, and now is a major expert in fintech and blockchain, and new technologies relating to financial services, so that is tomorrow, at 1 o’clock Eastern Time for Episode #202. Thanks so much, everybody! And especially I want to thank Livestream, because Livestream provides our video infrastructure and man, those guys are great. And so, if you need anything to do with livestreaming video, conferences or internally, you should talk to Livestream. Thanks a lot. Bye-bye!

Artificial Intelligence in Business, with Anthony Scriffignano (Dun and Bradstreet)

  • Episode: 204
  • |
  • Topic: Digital Business
Anthony Scriffignano, Chief Data Scientist, Dun & Bradstreet
Anthony Scriffignano
Chief Data Scientist
Dun & Bradstreet
Michael Krigsman, Founder, CXOTalk
Michael Krigsman
Industry Analyst
CXOTALK

Hype around artificial intelligence and machine learning continues to explode. In this episode, a prominent data scientist explains AI, explores how the technology works, and discusses the ethical implications. Our guest is Anthony Scriffignano, Chief Data Scientist of Dun & Bradstreet.

Scriffignano has over 35 years experience in information technologies, Big-4 management consulting, and international business. Sciffignano leverages deep data expertise and global relationships to position Dun & Bradstreet with strategic customers, partners, and governments. A key thought leader in D&B’s worldwide efforts to discover, curate, and synthesize business information in multiple languages, geographies, and contexts, he has also held leadership positions in D&B’s Technology and Operations organizations. Dr. Scriffignano has extensive background in linguistics and advanced computer algorithms, leveraging that background as primary inventor on multiple patents and patents pending for D&B.

Scriffignano regularly presents at various business and academic venues in the U.S., Europe, Latin America, and Asia as a keynote speaker, guest instructor, and forum panelist. Topics have included emerging trends in data and information stewardship relating to the “Big Data” explosion of data available to organizations, multilingual challenges in business identity, and strategies for change leadership in organizational settings.

Transcript

 

Michael Krigsman: Welcome to Episode #204 of CXOTalk. I’m Michael Krigsman, and CXOTalk brings the most innovative, interesting, really great people for a live, spontaneous video conversation, and what an incredible way for me, and for all of us to interact with the guests. And, you can follow us on @cxotalk, and use the hashtag #cxotalk to ask questions and to make comments directly to the guest. So today, on Episode 204, I’m speaking today with Anthony Scriffignano, who is the Chief Data Scientist at Dun & Bradstreet. Anthony is …  This is his second time on CXOTalk. He is such an articulate and clear communicator, and we’re going to talk about the foundations of artificial intelligence, and the implications for business, and in a very practical way. Anthony Scriffignano, how are you today?

Anthony Scriffignano: Michael, thank you very much. It’s great to be with you again.

Michael Krigsman: Well it’s awesome that you’re here! Please, share with us your background, and tell us about Dun & Bradstreet.

Anthony Scriffignano: Sure. So, Dun & Bradstreet, first of all, is arguably the world’s largest commercial data environment that you can encounter for information about businesses globally. And we maintain a database over 250, closing in on 260 million entities right now. We never forget a business, even after it’s out of business. This information is collected from hundreds of countries all over the world. It’s collected in different languages and writing systems. It’s updated millions of times a day. So, it’s a pretty big environment. [The information is] very, very dynamic ─ lots and lots of change in that environment. Those countries have different laws. We have to be very careful about how we curate the data, what we discover, permissible use, the whole nine yards. And, we certainly have to worry about implications of things like changing environments and changing behaviors, Some of the things that we’ll get into today that touch on the space of AI and machine learning in some of the underlying things.

As far as my role as Chief Data Scientist, one of the mandates that I have is sort of looking over the horizon. Looking at technologies and capabilities that will enable us going out into the future ─ so, not two days from now. But, before they become problematic, we have to be able to be very much aware, very well informed. So I spend a lot of time in the data science community of practice working with some of the top data scientists in the world, to basically say what we think out loud and be called crazy if we are; and to share ideas and thoughts; and to understand some of the new capabilities that are becoming possible. And then making sure we understand how these might be applied to this environment that we maintain.

Michael Krigsman: So we’re going to be talking about artificial intelligence and machine learning, and autonomous systems, but before we do that, just briefly share with us the kinds of things that you’re using AI or machine learning for inside Dun & Bradstreet.

Anthony Scriffignano: Sure, so we’re looking at a number of different processes that touch on this space. The most obvious one is in computational linguistics, natural language processing, things of that nature. We need to be able to look at large amounts of data. Some of it is unstructured. Actually, a lot of it is unstructured and we need to be able to understand things that are very difficult to understand because they’re proper nouns. See, you can look up the words in the dictionary, but you can’t look up your name in the dictionary, and by the time you can, it’s old news. So, we have to be able to deal with discussion about places, discussion about people. So, that’s a very big part of what we do.

Another thing that we do is something called recursive discovery, which is the ability to essentially adjudicate the truth. You have to be very careful with information that you pull

 

Michael Krigsman: Welcome to Episode #204 of CXOTalk. I’m Michael Krigsman, and CXOTalk brings the most innovative, interesting, really great people for a live, spontaneous video conversation, and what an incredible way for me, and for all of us to interact with the guests. And, you can follow us on @cxotalk, and use the hashtag #cxotalk to ask questions and to make comments directly to the guest. So today, on Episode 204, I’m speaking today with Anthony Scriffignano, who is the Chief Data Scientist at Dun & Bradstreet. Anthony is …  This is his second time on CXOTalk. He is such an articulate and clear communicator, and we’re going to talk about the foundations of artificial intelligence, and the implications for business, and in a very practical way. Anthony Scriffignano, how are you today?

Anthony Scriffignano: Michael, thank you very much. It’s great to be with you again.

Michael Krigsman: Well it’s awesome that you’re here! Please, share with us your background, and tell us about Dun & Bradstreet.

Anthony Scriffignano: Sure. So, Dun & Bradstreet, first of all, is arguably the world’s largest commercial data environment that you can encounter for information about businesses globally. And we maintain a database over 250, closing in on 260 million entities right now. We never forget a business, even after it’s out of business. This information is collected from hundreds of countries all over the world. It’s collected in different languages and writing systems. It’s updated millions of times a day. So, it’s a pretty big environment. [The information is] very, very dynamic ─ lots and lots of change in that environment. Those countries have different laws. We have to be very careful about how we curate the data, what we discover, permissible use, the whole nine yards. And, we certainly have to worry about implications of things like changing environments and changing behaviors, Some of the things that we’ll get into today that touch on the space of AI and machine learning in some of the underlying things.

As far as my role as Chief Data Scientist, one of the mandates that I have is sort of looking over the horizon. Looking at technologies and capabilities that will enable us going out into the future ─ so, not two days from now. But, before they become problematic, we have to be able to be very much aware, very well informed. So I spend a lot of time in the data science community of practice working with some of the top data scientists in the world, to basically say what we think out loud and be called crazy if we are; and to share ideas and thoughts; and to understand some of the new capabilities that are becoming possible. And then making sure we understand how these might be applied to this environment that we maintain.

Michael Krigsman: So we’re going to be talking about artificial intelligence and machine learning, and autonomous systems, but before we do that, just briefly share with us the kinds of things that you’re using AI or machine learning for inside Dun & Bradstreet.

Anthony Scriffignano: Sure, so we’re looking at a number of different processes that touch on this space. The most obvious one is in computational linguistics, natural language processing, things of that nature. We need to be able to look at large amounts of data. Some of it is unstructured. Actually, a lot of it is unstructured and we need to be able to understand things that are very difficult to understand because they’re proper nouns. See, you can look up the words in the dictionary, but you can’t look up your name in the dictionary, and by the time you can, it’s old news. So, we have to be able to deal with discussion about places, discussion about people. So, that’s a very big part of what we do.

Another thing that we do is something called recursive discovery, which is the ability to essentially adjudicate the truth. You have to be very careful with information that you pull in, even information that you know to be true, because not all true information is true at the same time, and truth is somewhat fungible - it’s not really a black and white kind of thing in many cases. And then the big Magilla [Gorilla], if you will, is malfeasant behavior, if you will. Fraud is another word for it. Sometimes when people commit actions, to us they haven’t actually committed fraud yet because they haven’t gained financially. So, watching people behave in bad ways, is certainly something where these types of techniques are very much part of what we think about in terms of how can we inform our thinking, and how can we do what we’re trying to do to inform our customers.

Michael Krigsman: Ok, so these are areas that you’re focused on inside D&B. But now, let’s take a step back and so when you, as a data scientist, think about the term “AI”, what do you think of? What does it actually mean? And let’s try to go beyond the hype, because AI has become the latest jargon, you know, it’s even better now. It’s exploding faster than digital transformation, which has exploded into meaninglessness.

Anthony Scriffignano: Yeah.

Michael Krigsman: Yeah. [Laughter]

Anthony Scriffignano: If there’s nothing else that our industry is good for, it’s creating terms that people can use that have ambiguous meaning, and can be taken to mean almost anything in any situation. And this is certainly one of them. So, it’s one of those things that you understand, but then when you try to define it, scholars will disagree on the exact definition. But, artificial intelligence collectively is a bunch of technologies that we run into. So, you’ll hear “AI.” You’ll hear “machine learning.” You’ll hear “deep learning,” [or] sometimes “deep belief.” “Neuromorphic computing” is something that you might run into, or “neural networks;” “natural language processing;” “inference algorithms;” “recommendation engines.” All of these fall into that category. And some of the things that you might touch upon are autonomous systems ─ bots. Sometimes, we will hear talk of… Well, Siri is probably the most obvious example that anybody runs into (or any of the other ─ I won’t try to name them all because I’ll forget one), but things of that nature where you have these assistants that try to sort of mimic the behavior of a person. When you’re on a website, and it says, “Click here to talk to Shelly!” or “Click here to talk to Doug!” You’re not really talking to a person; you’re talking to a bot. So, those are examples of this.

Generally speaking, that’s the broad brush. And then if you think about it as a computer scientist, you would say that these are systems processes that are designed to do any one of several things. One of them is to mimic human behavior. Another one is to mimic human thought process. Another is to “behave intelligently” ─ you know, put that in quotes. Another is to “behave rationally,” and that’s a subject of a huge debate. Another one is to “behave ethically,” and that’s an even bigger debate. Those are some of the categories that these systems and processes fall into.

And then there’s ways to categorize the actual algorithms. So, there are deterministic approaches; there are non-deterministic approaches; there are rules-based approaches. So, there’s different ways you can look at this: you can look at it from the bottom up; the way it just ended; or in terms of what you see and touch and experience.

Michael Krigsman: So, from a business perspective, when we hear terms like “machine learning,” “AI,” “cognitive computing,” is there some type of framework in which we can think of these things? How do they relate to one another? Are they synonymous?

Anthony Scriffignano: They’re not synonymous. So, cognitive computing is very different than machine learning, and I will call both of them a type of AI. Just to try and describe those three. So, I would say artificial intelligence is all of that stuff I just described. It’s a collection of things designed to either mimic behavior, mimic thinking, behave intelligently, behave rationally, behave empathetically. Those are sort of the systems and processes that are in the collection of soup that we call artificial intelligence.

Cognitive computing is primarily an IBM term. It’s a phenomenal approach to curating massive amounts of information that can be ingested into what’s called the cognitive stack. And then to basically be able to create connections among all of the ingested material, so that a particular problem can be discovered by the user, or a particular question can be explored that hasn’t been anticipated.

Machine learning is almost the opposite of that. Where you have a goal function, you have something very specific that you try and define in the data. And, the machine learning will look at lots of disparate data, and try to create proximity to this goal function ─ basically try to find what you told it to look for. Typically, you do that by either training the system, or by watching it behave, and sort of turning knobs and buttons so there’s unsupervised, supervised learning. And that’s very, very different than cognitive computing.

Michael Krigsman: And, what about autonomous systems? We’re kind of like, this is truly an alphabet soup.

Anthony Scriffignano: Yeah.

Michael Krigsman: Ok. [Laughter]

Anthony Scriffignano: So we [covered] all the colors in the palette here, a little bit, to be able to speak this language. So, autonomous systems are systems that behave without human interaction, essentially. They go off on their own, and do what they’ve been told to do. And you can think of a drone that’s not being flown by somebody as an example of an autonomous systems. Lately, there’s been a lot of talk of autonomous vehicles, which is an interesting sort of oxymoron, because they’re not really “autonomous.” There’s somebody in the car, but that person in the car isn’t driving the car. And that will be an example of that. And then, there are semi-supervised, [which is] somewhere in between autonomous and not-autonomous, for lack of a better word. That means that you might have systems where you can intervene if necessary. So think of the autopilot on an airplane ─ they like to call it the flight control system or the flight… there are other words for it on airplanes. They’re basically designed to help the airplane maintain a course: maintain an altitude ─ mainly do something like change altitude, or change the direction with some input. But, at a certain point, you know, if there’s a lot of turbulence, or something unusual happens ─ the plane’s in an unusual altitude, the thing breaks ─ the autopilot system or the autoflight system basically turns off and says, “It’s your airplane, have a nice day!” So, they’re not completely autonomous. There’s an “If all else fails, give it to the human” kind of function in many of these.

Michael Krigsman: Well certainly, we should talk at some point during this conversation about human functions that are augmented by AI. But there’s a few things we need to get to first, and we have a question from Twitter. It’s a really good question, let me tell you what it is, but let’s again address it a little bit later. And this is from Arsalan Khan, who’s asking, “When an AI system makes a decision that is based on bad data, or bad algorithms, in business, who is responsible for that?” Which is a fundamentally important question, but let’s come back to that because there’s still some basics I think we need to get out of the way, and we’ll definitely want to talk about the ethical aspects.

Anthony Scriffignano: Yeah, we’re going to have to parse through them too, but you’re going to have to define “bad.” I’ll let us get there.

Michael Krigsman: Yeah, we’ll get there in a couple minutes. Ok. So, autonomous systems, machine learning, what does all of this, first off, have to do with AI?

Anthony Scriffignano: Well, basically, we need AI for autonomous systems to behave autonomously. That would be the simple way to put it: for an autonomous system to work properly. Imagine you had a train, and you wanted the train to be able to come up to speed, travel down the tracks, slow down when necessary, don’t go through any signals, and stop at the next stop. I’m not a train engineer, but I’m guessing I could probably build an analogue system to do most of that. And I’d still probably want someone sitting there with their hand on the break just in case it doesn’t work. But, I think I could probably build a system that did not require a lot of intelligence to do that.

But, now you think about what happens when there are no railroad tracks ─ when the road might have lines in it that might get fuzzy; or might be covered with rain; or a kid runs out with a ball; or there’s a police car and you need to pull over; or a plane lands in front of you, or an elephant walks out in the road. And pretty soon, you get into this system where the number of things that can happen starts to overwhelm discrete description, and a basic set of rules. Now we start to need AI to be able to deal with the problem like that ─ to be able to effectively learn. And I have to say we tend to anthropomorphize these systems or these algorithms. We talk about “machine learning,” and “systems learning.” Well, they’re not “learning.” They are adjusting information and they’re organizing it in ways that they’ve been designed to organize it. I actually use the term “symbiotic intelligence” instead of “artificial intelligence”. These are systems that have been taught to learn in ways that we’ve described for them with primary goals that we’ve given to them. But, without having to say all that, we can say “learning”.

Michael Krigsman: Ok. So again, in our quest to demystify the basics, you explained that the systems quote-on-quote “learn”. And we hear the term “modeling,” right? We hear the term we have to train… When you talk to data scientists and they’re talking about machine learning, they say we have to “train the model”, create the model and then train it. What does that mean?

Anthony Scriffignano: So, I’m not sure if we’re demystifying this or mystifying this because unfortunately, this is a field that every time you talk about something, there’s new terms that come in. So, let’s just talk about what a model is mathematically first, and then we’ll talk about how it applies to machine learning and training the model.

So, a model is basically a method of looking at a set of data in the past, or a set of data that’s already been collected, and describing it in a mathematical way. And we have techniques based on regression, where we continue to refine that model until it behaves within a certain performance. It basically predicts the outcome that we intend it to predict, in retrospect. And then, assuming that we can extrapolate from the frame we’re in to the future, which is a big assumption, we can use that model to try to predict what happens going forward mathematically. The most obvious example of this that we have right now is the elections, right? So we look at the polling data. We look at the phase of the moon. We look at the shoe sizes. Whatever we decide to look at, we say, “This is what’s going to happen.” And then, something happens that maybe the model didn’t predict.

And, I saw some great articles over the last few days blaming the data. “Stupid data!” The data doesn’t have stupidity. And I’m not saying the people that interpret the data are stupid either. I’m saying that things can always happen within random variation, or they can always happen according to attributes that weren’t anticipated. So, modeling is a good thing. It’s an important thing. We all live and die by certain models in our lives. That’s how interest rates happen. That’s how all kinds of … that’s how certain warnings come up in your car. There’s all kinds of reasons why we want models to work. But, we also have to be very humble that the human brain doesn’t work that way; doesn’t work that way at all.

So, now we get into AI. The way some systems work, not all, is they say: “Show me something that looks like what you’re looking for, and then I’ll go find lots of other things that look just like it. So train me. Give me a webpage, and tell me on that webpage which things you find to be interesting. I’ll go find a whole bunch of other web pages that looks like that. Give me a set of signals that you consider to be danger, and then when I see those signals, I’ll tell you that something dangerous is happening.” That’s what we call “training.”

Michael Krigsman: Ok Anthony, I don’t mean to interrupt, but please, drill down a little bit more on this. So we hear, just for example, companies coming up with image search.

Anthony Scriffignano: Yes.

Michael Krigsman: So, train us in terms of images, mountains, or seashores. When you say “Find something interesting on the page,” can you drill into that?

Anthony Scriffignano: Sure. So imagine that I gave a whole bunch of people, and the gold standard here is that they have to be similarly incented and similarly instructed, so I can’t get, you know, five computer scientists and four interns … You try to get people that more or less have either they’re completely randomly dispersed, or they’re all kind of trying to do the same thing. There’s two different ways to do it, right? And you show them lots and lots of pictures, right? You show them pictures of mountains, mixed in with pictures of camels, and pictures of things that are maybe almost mountains, like ice cream cones; and you let them tell you which ones are mountains. And then, the machine is watching and learning from people’s behavior when they pick out mountains, to pick out mountains like people do. That’s called a heuristic approach. When we look at people, and we model their behavior by watching it, and then doing the same thing they did. That’s a type of learning. That heuristic modeling is one of the ways that machine learning can work, not the only way.

There’s a lot of easy ways to trick this. So, people’s faces are a great example. When you look at people’s faces, and we probably all know that there are techniques for modeling with certain points on a face, you know, the corners of the eyes. I don’t want to get into any IP here, but there’s certain places where you build angles between these certain places, and then those angles don’t typically change much. And then you see mugshots with people with their eyes wide open, or with crazy expressions in their mouth. And those are people trying to confound those algorithms by distorting their face. It’s why you’re not supposed to smile in your passport picture. But, machine learning has gotten much better than that now. We have things like the Eigenface, and other techniques for modeling the rotation and distortion of the face and determining that it’s the same thing.

So these things get better and better and better over time. And sometimes, as people try to confound the training, we learn from that behavior as well. So this thing all feeds into itself and these things get better, and better, and better. And eventually, they approach the goal, if you will, of yes, it only finds mountains. It never misses a mountain and it never gets confused by an ice cream cone.

Michael Krigsman: And how is this different from traditional programming, right? Because with traditional programming, we can put up pictures, you can do a Google search, or a few years ago maybe, before there was big machine learning, and pick out pictures of mountains or whatever. So how is this different?

Anthony Scriffignano: So, without getting into a whole debate on how it used to work versus now (because I’m sure there’s a bunch of people on the internet that will take us to task), this has been done in a lot of different ways. The original way that this was done was through gamification or just image tagging. So, they either had people play a game, or they had people trying to help, saying, “This is a mountain,” “This is not a mountain,” “This is Mount Fuji,” “This is Mount Kilimanjaro.” So, they got a bunch of words. They got a bunch of people that use words to describe pictures …

Michael Krigsman: Amazon Turk, for example.

Anthony Scriffignano: There you go. Mechanical Turk. Right. And then, using those techniques, they just basically curated a bunch of words and said, “Alright, the word ‘mountain’ is very often associated with there’s a high correlation statistically between the use of the word ‘mountain’ and this image. Therefore, when people are looking for a mountain, give them this image. When they’re looking for Mount Fuji, give them this image and not this image.” And that was basically a trick of using human brains and using words. That’s not the only way it works today. There’s many more sophisticated ways today.

Michael Krigsman: Ok, this is good.

Anthony Scriffignano: I have a good example for you. After the earthquake and the tidal wave happened in Japan a number of years back, we needed to try to help the people in Japan. And one of the things we had to do was look at satellite images and find roads and infrastructure that were impacted by all of these horrible things that happened. So, we taught a series of algorithms to find previously unbroken straight and curved lines that were now interrupted, and then we had an algorithm that inferred the degree of impact to the infrastructure around a business. So, that was learning about something that just happened using data we never used before, that in this case was graphical, that we could reduce to something mathematical and observe it quote-on-quote “Thousands, and thousands, and thousands of times” really quickly. That’s an example of a real impact.

Michael Krigsman: And, what about autonomous cars? If you live in someplace like San Francisco, you see these autonomous cars driving in the streets. What is the role of AI and machine learning, other technologies, in making that possible?

Anthony Scriffignano: So, a whole industry in the process of exploding right now, right? So we started out very much like the autoflight systems in airplanes. We wanted the car to stay in the lane, and stay at a certain speed, and remain a certain distance away from the car in front, right? So, if a car pulled in in front of you, the car that you’re driving in let’s call it “autoflight mode,” or “autodrive mode” would slow down enough to keep a certain distance, and override the intention to drive at a certain speed, but not change lanes. So this is, “Stay in the lane; stay at the speed unless you’re going to hit somebody,” basically.

Now, the autonomous cars are way beyond that, right? So they know something about the road in front of them. They know that it’s essentially what a GPS system would know, in terms of what are the roads ahead of us, what does the traffic look like… So the overall goal might still be, “Get from Point A to Point B, stay in the lane, try to drive at the speed,” but they’re much, much, much more sophisticated in terms of the information that they can bring in and the type of decisioning. So they don’t have to just say, “Well what do you want to do?” They can do it for you, to a certain extent.

There are still some very real concerns. You know, we all read the news, right? An autonomous car isn’t going to speed, because there’s a speed limit. And well, people speed! People drive with traffic, right? And you try going on a highway, and driving the speed limit, and see what happens! In certain cases, that might be very dangerous, and I’m not suggesting we speed. But, I’m just observing as a scientist that people do, right? So, you know, what do you do in a situation where “common sense”, in quotes, or at least common practice dictates that you do something that’s against a rule that’s built into a system? What do you do when a kid runs out in front of you with a ball, and a dog runs out in front of you chasing the kid and you’ve got to hit the kid or the dog? And this is horrible, but these things happen. It’s never happened to me; I hope it never does, but I’m pretty sure that I wouldn’t just throw my hands up and let the car do whatever it wants. I would have the car do something. Sometimes jamming on the breaks is the most dangerous thing you can do. So, you know, autonomous systems are able to approach the behavior of a safe driver driving in predictable environments right now, within reasonable limits, as long as there’s a person in the car to take over. Our goal is to get better than that, but think about the number of things you have to believe for that to be fully functional? I think we’d still want the human being there. I don’t think I want the autonomous car going out and delivering pizza all by itself, although probably before I get a chance to eat these words, that will be happening anyway.

Michael Krigsman: [Laughter] We have another question from Twitter, and this is a well-timed question, because we’re talking about the applications, the practical applications of AI and techniques like machine learning. And this is from Frank McGee, who’s wondering: “How are companies using AI to predict the behavior of customers and prospects?” So of course, this is the sales question.

Anthony Scriffignano: Yeah, and of course, in my case, we’re trying to use it to predict the behavior of the bad guy, as well. So it goes either way. So, you know, obviously, the billion-dollar idea is if I could predict, by people’s behavior, what they’re about to do and approach them in their time of need before that need arises, or just as that need arises. Then, I have more of an opportunity to serve that customer and maybe I can take some business away from people who aren’t so agile, and so smart. That’s basically the underlying idea. And AI is certainly being used. You know, we’ve all seen the movie (or many of us) [called] “Minority Report”, where the guy walks into the shopping mall, and all of the digital advertising on the walls is recognizing his eye implant and trying to sell him things, and tell him that he needs things. And I think we’ve all had experience with maybe going onto a, I don’t want to name a site (but something like Amazon for example), where you might search for something and not buy anything, and later on you get an email ─ you know, trying to offer you something. Those are really primitive examples of this kind of technology but it’s getting way, way, way better.

So, by watching enough people behave in a well-understood environment, with well-understood context, we can start to anticipate clusters of behavior and take action on it. An example, a great example would be if we watch people’s behavior in supermarkets. So, people go into a supermarket; and we can easily put technology on the cart that says, “Where are they going? How long did they stop?” and then ultimately, “What did they buy?” And by using behavior like that, we can reposition things in the store according to certain goals: like we’d like to make them walk around more; or we’d like to lead them towards the more expensive items; or whatever it is we try to get them to do. So that technology’s starting to happen, and it’s starting to happen in digital advertising big time. It’s starting to happen in very simple things. Like when you go to a movie theater, there’s a lot of technology watching what people do in environments where we understand the context very well. And, our behavior’s being manipulated in ways that you would be amazed at some of the ways that we’re being touched, that we don’t realize. And then of course there’s a creepy factor to that too, which we have to be careful of.

Michael Krigsman: We are talking on Episode #204 of CXOTalk, with Anthony Scriffignano, who is the Chief Data Scientist at Dun & Bradstreet, and you are welcome to tweet questions in using the hashtag #cxotalk. So, Anthony, we’ve been discussing the technology underpinnings of AI, but AI is unique in the sense that the conversations very quickly turn to questions about the ethics of AI, whether we should be using AI, and to what extent, and where, and where AI should be prohibited. It extends to questions such as Arsalan Khan raised earlier, such as when something goes wrong with an AI system and the outcome, who’s responsible? And so first, what is it about AI that lends itself to these very open-ended philosophical questions? Very different from the cloud in that sense.

Anthony Scriffignano: Totally different. Yeah, totally different. So, we talk about disruptive technology as something that forces you to change your behavior, right? The cloud definitely forced us to rethink security and privacy. A laser pointer doesn’t really force me to change my behavior. It’s a long stick I can go point, right? But AI is here to stay, it’s not going anywhere, there’s every reason to believe that it’s the degree to which this type of technology will be pervasive in our daily lives will increase, and will become more difficult to even notice. So, we just have to accept that.

So, what is it about it that puts us in a position to question some of these, either moral questions, legal questions, ethical questions? Well, as we give up our autonomy, as we let things do things for us, there are certainly some legal questions about whether those things are essentially electronic agents. If I hire somebody to go deliver dynamite, you know, legally, right? I’m not completely exonerated from some stupid thing that they might do while they’re delivering the dynamite like trip and fall and blow something up, right? So there are legal principles for agency. Those legal principles are probably not completely codified to cover digital agency, just as an example. So if you ask a person to do something for you, there is a very clear understanding in the law of the degree to which your liability extends into that action. The law typically does not catch up with technology.

When the law tries to anticipate technology, the purveyors of that technology often change their behavior knowing what the law is. And so you wind up either with a law that either loosely covers a set of behavior, or covers what that behavior was intended to be, and then it changed. And then on top of that, you have the rate of change of bad guys and how people will misuse technology. So, these are really complicated issues.

So, the thing I loved about that question that was asked was “If an AI agent, or let’s just call it an electronic agent for lack of a better term, does something wrong, are you responsible?” Part of the issue here is defining “wrong.” Someone would say, “Look, the system drove the autonomous car into a wall, because the wall wasn’t on the map. And it’s not the car’s fault, it’s the people who built the wall’s fault.” I don’t know about that, because you wouldn’t drive your car into a wall, right? If you were there, you wouldn’t drive your car into a wall. So I could make an argument that the people who made that system did a bad job of creating an AI agent that mimics human behavior, because a reasonable human wouldn’t do that. And this reasonable person standard is in the law already. Does it apply to digital things? Not so much yet.

So I think we have sort of the building blocks there, and I hope that we don’t have to completely rethink ethics and moral behavior. But, I think we really do have to think about how much of this legally applies. And, in certain cases, I’m not a lawyer but I work with them a lot, you know, you have to see how the courts are going to interpret it, and you have to see what’s going to happen in different countries. You have to see how this might change the ability to bring these technologies to the market. We also have to be careful because we’re so afraid of things like that happening, that we don’t put something in like the Watson system that’s in right now that’s using all of the curated medical literature to help emergency room doctors… You know, I really want them to do that! I really want them to do that well because I may have to go to an emergency room someday, and if they’re too afraid to use technology like that because it might make a mistake, and not learn from it, then we don’t do anything. And that first step never happens. We have to, as human beings and rational purveyors of the advances of technology, will have to walk that line carefully and not just be afraid.

Michael Krigsman: So, we only have about fifteen minutes as opposed to three or four days to continue this discussion. And, the issue of data, okay? So we have the separation between, or the AI outcome relies upon the source of data, and the quality of data, along with the quality and the caliber of the algorithms and the learning, the machine learning that has taken place. So, how do you separate from an ethical perspective, for example, how do you separate out those two in order to answer Arsalan Khan’s question, in terms of pointing responsibility when you have a negative outcome, or for that matter, if you have a positive outcome?

Anthony Scriffignano: I don’t think you do. I think that data is permeating everything, and the fact that you didn’t go use the right data to do what you should have done in your algorithm is not an excuse! The fact that you didn’t realize that you took data in motion and created data at rest in order to put it in some training environment, and the world changed outside while you were doing your training, well shame on you. We should know these things. The science of using data hasn’t changed because of machine learning. We have to remember that there are certain things that we need to do in order to use data in motion, or data with varying degrees of veracity or velocity or value to a particular goal. Those are Big Data problems that we had. We’re not allowed to say “Big Data” anymore, though we haven’t completely solved any of those problems yet. So, we need to make sure that we make new mistakes. We need to make sure that we keep all of this learning that has brought us to the point where we can create amazing things like this, and really keep in mind the fact that the underlying data can influence the outcome of the behavior of these things just as well as having the wrong algorithm, or giving it the wrong goal, or not supervising it, and changing it. All of those things are aspects of getting this right. It will not get any easier. It will get more complicated and I would say that’s the work of the future.

You know, everybody talks about, “How many jobs will be eliminated by the creation of artificial intelligence agents, bots, things like that?” Probably a lot! But everything I just said will probably create a lot of new jobs. So, it’s all about us as a human race not drowning in our data, and drowning in our technology, and giving up the fact that we have rational thought. And these things typically don’t. There’s something going way back to Alan Turing ─ the Turing Test. If I could ask a robot a question, and ask a person a question and not know which one was which. The Turing Test is basically the thing is behaving in an intelligent way when I can’t distinguish which one is the human or not. And when bots first came out, people would just say, “Well, are you a bot?” And the bot wouldn’t know how to answer that question and it was pretty easy to fail the Turing Test. Now, they know how to answer that question, and it’s not so easy anymore. So, why? Let’s do some good with this. Let’s make some new mistakes, and move this forward in a rational, intelligent way, and not just sort of be afraid of it evolving.

Michael Krigsman: The questions of public policy then become prominent in here as well, because of the job issue and because of the fear that’s associated with the possible implications of what will happen. So, where does public policy now start to intersect this?

Anthony Scriffignano: Well, I think it’s really something that we need to be thinking about. One example of public policy is marginalization, right? So, who has access to this technology? Do we only put the AI technology that works in the emergency room in the hospitals that are in the inner-cities because there’s a higher volume of people? Somebody could make a rational argument that this needs to be available to everyone. If you make it available to everyone, then you can’t take the first step. So, I think as public policy … As people who are setting public policy do what they do, they need to think very seriously about things like asymmetry and marginalization, and access to methods, and access to technology, just like they do with anything else they do in public policy. The difference is, look how long it took us to even describe what we’re talking about here? This is not an easy conversation to start happening. It’s not like we’re just talking about, you know, changing tires on cars. We’re talking about, you know, something that is very, very difficult to explain. It’s contingent upon us. Anybody can make this more complicated. It’s contingent upon us to make this easier. To let the people who are setting public policy become aware of some of these issues and do what they do well, and set policy correctly. And conversely, if that’s not happening, to speak up and not to just move on and wring our hands.

Michael Krigsman: But this is one of the fundamental problems. It’s the fact that we’ve been talking now for about forty minutes, and we’re just at the point where we’ve been able to cover enough of the basics to even have the actual meaningful conversation from a business perspective, or a policy, or an ethical perspective. How in the world can we simplify this so that non-computer scientists can have a meaningful discussion about it?

Anthony Scriffignano: You know, I talk a lot about sort of reflective leadership that goes into leading an organization that is using technology. You can’t just hire smart people. You have to teach yourself. Every day, you have to teach something or learn something, right? So, the people who are setting public policy, my hope, and this is probably completely naive, is that they are aware that there are technologies that are starting to come about in the news and maybe they should learn a little bit about them. But to put from your question, from the bottom up, so to speak, the folks that are very much aware of these technologies, and what they do and the fears and the hopes are for these technologies, we have to make sure that our voice is not only a heard voice, but a voice that makes sense. We can’t use a whole bunch of jargon. We can’t use a lot of big words. It would be very easy to talk about everything you’re talking about in language that’s so dense, that no one would ever figure out what we’re talking about except the people that teach this stuff. And then what? That doesn’t help anybody, right? So, we have to find ways to bridge these gaps. We can’t lead with the technology.

If somebody comes to me and says, “Well can you use AI to solve this problem?” I don’t know! Tell me what the questions are. Tell me what the problems are. Don’t leap right forward into doing any of this. But, at the same time, think about the implications of not, right? What does it mean to your customers? What does it mean to the communities you serve? What does it mean to the marginalized others? All of these are future questions that we really need to be asking.

Michael Krigsman: I mean, certainly what you’re saying is right, but what happens in this case, just to give a sense of flavor of how complex this is: If we talk about these public policy issues, leaving alone the question of “What is AI?”, it creates this huge black box, for which data scientists can essentially - and companies - can basically do whatever they want without real scrutiny. Or is this perspective just wrong?

Anthony Scriffignano: Well, I think the term “AI” is what causes that, right? So organizations can behave in less than transparent ways, in all sorts of ways. And, you could ask the same question about collecting customer information. You could ask the same question about using behavior of your customers, or your vendors, or anybody who “comes into your store,” to so speak (in quotes), in ways that they don’t intend, and what that portends. I think that the most important thing here is we shouldn’t feel like there’s some sort of wall up because we’re talking about artificial intelligence. If we need a simple definition, we could say, you know, “systems and processes that are intended to behave as intelligent humans would, in well-understood environments”. That’s not a perfect definition; it’s not a horrible definition. It’s sort of an okay definition. And if I had to start a conversation, I would probably start it there. And then I’d probably give some examples, and then I’d probably say, “Like Siri, like a bot, like an autonomous car.” Eventually, you can get into a conversation about the difference between a drone with somebody flying in it, and a drone without somebody flying in it. And is that an … You know, the FAA is worrying about that right now. They’re trying to create regulations that cover things like. But don’t start there. Don’t start where it’s complicated. Start where it’s simple, and at least reasonably possible to adopt a working definition.

Michael Krigsman: So, before we run out of time, there’s a couple of other things that we just need to talk about. And, we have not really discussed the topic of privacy. And so, where does privacy and the data privacy fit into this equation as well, into this landscape?

Anthony Scriffignano: It’s a huge issue. Bots have the ability to observe things, and learn things, and remember them forever. There’s something called an “observer effect.” When you watch people who know they’re being watched, the first thing they do very often is change their behavior. So, if you build models and systems to detect behavior based on the past, you know that those systems are detecting the way that that behavior is not occurring, because you know the people behaving have changed their behavior ─ those kinds of things. Security, privacy plays into this. Do I know I’m being watched? If I do, do I behave differently? Do I have the right to opt in or opt out of being ‘botted’ to, if you will, to coin a word. You know, there’s laws being written as we speak, and laws about to be implemented as we speak that talk to general protection of privacy: the right to be forgotten; what the government may or may not do vis-à-vis business. So, all over the world, these sorts of laws would be written around data. What data can be transported across borders… Think about this: what happens if you don’t transport it across the borders and you make a really stupid decision because you couldn’t see all the data?

So, the answer to everything isn’t always as simple as, “Well everything is private and everything needs to be contained and nobody gets to see anything.” That might be a way of looking at it, but it might be somewhat naive with the amount of data that’s being created now. So, this is happening all over the world, we can’t ignore it, and we’re certainly nowhere near done figuring this out.

Michael Krigsman: Yeah, it seems we have barely scratched the surface of it.

Anthony Scriffignano: Might be a good topic for another CXOTalk.

Michael Krigsman: Yeah, actually I had Michelle Dennedy who’s the Chief Privacy Officer of Cisco as a guest on CXOTalk, and I don’t think we really spoke about AI too much, but you could have endless discussion about this. It’s a very complicated topic.

Anthony Scriffignano: You could probably get two bots to talk about it too!

Michael Krigsman: [Laughter] That might be a lot of fun! So, before we go, two last questions and I’ll ask you to answer kind of quickly, just because we’re running out of time. And again, these are conversation that we could spend all day talking about each one of these but, what advice do you have, first off, to businesspeople, to senior executives who may be listening that are saying, “What do I do about all of this stuff?”

Anthony Scriffignano: So I would say three things: 1) Be humble. Be realistic. There’s no magic button. There’s no secret open-source code you’re going to pull in and solve all your problems. Be humble about what can and can’t be solved with approaches like this. 2) Recognize the fact that doing nothing is actually a choice. You can’t just do nothing because you don’t know exactly what to do because that opportunity cost could be very, very, very serious. And 3) Continuous learning. Continuous learning of your existing organization. The people in the organization ─ the skills that got them there are not the skills that are going to take them forward into the future. They’re just table stakes. And the people that you’re hiring, what skills do you need to fill in those gaps?

Michael Krigsman: Ok. And then, finally, what advice do you have on the public policy side? So we’ve just been talking about the private sector. What about public policy and regulators? What advice do you have for them regarding all of these AI technologies and these deep moral and philosophical implications?

Anthony Scriffignano: I think we should regulate behaviors and not try to overregulate specific technologies because those technologies and specific types of data change so quickly. So, we should look at the behaviors. I think we should also look at the unintended impact of over-regulating some of these things because there’s a lot of good that can come from data being used in the right ways, and technology being used in the right way. So, always consider the balance between the impact of over-regulation, and not having enough regulation. And then the last thing I would say is, from a public policy standpoint, maybe we can use a little AI to figure out what’s working and what’s not working. And not just sort of, you know, speak our way into the truth.

Michael Krigsman: You know, it’s funny. When I talk with regulators, some of the more enlightened ones, that’s one of the things that comes up, which is “What about the role of AI in development …

Anthony Scriffignano: … of policy!

Michael Krigsman: Exactly. Well, we are out of time. We have been talking with Anthony Scriffignano, who is the Chief Data Scientist of Dun & Bradstreet, and what an action-packed 45 minutes this has been! You’ve been watching Episode #204 of CXOTalk. It’s going to be on-demand for the replay immediately when we’re done, and if you are interested in the foundations of AI, and the implications, I urge you to watch it. Anthony Scriffignano, thanks again for being with us!

Anthony Scriffignano: Thank you very much for having me. It was great.

Michael Krigsman: Everybody, thank you and I also want to give a huge thank you to Livestream, who provides our video infrastructure and they’re flawless, it just works, and we’re really grateful for that. You know, funny thing about live video like we do, live video is an exercise in almost ready to fail, because there’s so many pieces. And, with Livestream, it just always works, and so we really, really appreciate that. Thank you everybody, we’ll have another show next week. Bye-bye!

Digital Transformation and Technology Investment

  • Episode: 206
  • |
  • Topic: Digital Business
Bill Briggs, Chief Technology Officer, Deloitte Consulting
Bill Briggs
Chief Technology Officer
Deloitte Consulting
Michael Krigsman, Founder, CXOTalk
Michael Krigsman
Industry Analyst
CXOTALK

The relationship between digital transformation and investment in technology is critical yet frequently misunderstood. On the episode, we speak with a world-leading expert on this subject.

Bill Briggs is the Chief Technology Officer for Deloitte Consulting, former global lead of Deloitte Digital, and a Director in the US technology practice. Bill is a strategist with deep implementation experience – helping clients anticipate the impact that new and emerging technologies may have on their business in the future, and getting there from the realities of today. As CTO, Bill is responsible for helping to define the vision for Deloitte Consulting LLP’s technology services, identifying and communicating technology trends affecting clients’ businesses, and shaping the strategy for Deloitte Consulting LLP’s emerging services and offerings.

As a Director in the US technology practice, Bill served as overall program lead, chief architect, or technology lead on dozens of critical transformation programs for global Fortune 100 organizations across industries, including financial services, health care, consumer business, telecommunications, energy, and public sector.

Transcript

Michael Krigsman: Welcome to Episode #206 of CXOTalk. CXOTalk brings together the most innovative leaders in the world, talking about the impact of technology on organizations; and we're talking to day with Bill Briggs, who is the Chief Technology Officer of Deloitte Consulting. And of course, Deloitte Consulting is one of the largest consulting organizations in the world. I'm Michael Krigsman, your host. I'm an industry analyst and I'm thrilled to be here, and I hope that you are, too!

Bill Briggs: [Laughter] Wonderful, Michael! Two of us are, for sure!

Michael Krigsman: Bill, thanks so much for joining us today! You're coming to us from Kansas.

Bill Briggs: From Kansas City, which is always fine as the CTO and I was actually the global leader of Deloitte Digital, and we started our digital practice and [would] meet with executives around the world, and they'd say, "Well do you live in Mountain View or Cupertino?" And I say, "No, Leawood." "Is that somewhere near metro Palo Alto or Magnolia?", and I'd say, "No, it's in Kansas City." And then I'd say, "Silicon Prairie", and then that gives a chuckle, and then we have to move on. And if they push me, I can say, "the Paris of the Plains," which is nice, but my wife is where family is and I'm in a different city every day, so it's worked out phenomenal. We love it here.

Michael Krigsman: Well, tell us about Deloitte Consulting.

Bill Briggs: Yes, so you started us off on the right place. We're the biggest professional services firm in the world, and we pride ourselves in helping the biggest companies, the biggest government organizations, to transform themselves: full-stop business model reinvention, helping solve the biggest problems that they have with operations, changing the way that they engage with customers, you name it, across every industry with a global presence. And what's great is I joined the firm eighteen and a half years ago, computer engineer, along the way got an MBA, but engineering technology [is] in my DNA. And when I joined in technology, it was an interesting little side-experiment for a firm that was more often known for our tax and audit, which is still an important part of the broader Deloitte. But now, consulting is the biggest player in the world, and technology's the heart of what we're out there with clients, harness[ing] to do all of the things they need to do to drive innovation and growth, so it's been satisfying.

Michael Krigsman: How many employees do you have?

Bill Briggs: Well, globally it's over 230 thousand. That's through the broader Deloitte. I think for the US consulting, it's 80 thousand or so? We should fact-check that but it's close to it, so this is huge, which is phenomenal because I joined out of undergrad. It's really fun to see, as the next generations come up and push our thinking and help us evolve our services, and ... I still think that kid right out of college, when I'm down, especially on campus recruiting and helping our new staff through ... Then I look in the mirror and see the hairline and get reminded that maybe that might not quite be the case - in spirit, right? [Laughter]

Michael Krigsman: Well, it seems like you're having a good time there, but I think one question that immediately comes to mind is: So, you're a professional services organization, and yet, you have your ... you're the Chief Technology Officer. And so, why does Deloitte Consulting need a CTO?

Bill Briggs: Well I mean, it comes back to …If we believe that every company's a technology company, and technology is changing so quickly, and the only constant that we have anymore is the constant for change and the surety that tommorow's going to be more complicated than today. And those things come together. My role is about research, about innovation, you know, for our clients and also the investments we need to make within the consulting practice and how we evolve our services, and stay ahead of the issues our clients care most about

Michael Krigsman: Welcome to Episode #206 of CXOTalk. CXOTalk brings together the most innovative leaders in the world, talking about the impact of technology on organizations; and we're talking to day with Bill Briggs, who is the Chief Technology Officer of Deloitte Consulting. And of course, Deloitte Consulting is one of the largest consulting organizations in the world. I'm Michael Krigsman, your host. I'm an industry analyst and I'm thrilled to be here, and I hope that you are, too!

Bill Briggs: [Laughter] Wonderful, Michael! Two of us are, for sure!

Michael Krigsman: Bill, thanks so much for joining us today! You're coming to us from Kansas.

Bill Briggs: From Kansas City, which is always fine as the CTO and I was actually the global leader of Deloitte Digital, and we started our digital practice and [would] meet with executives around the world, and they'd say, "Well do you live in Mountain View or Cupertino?" And I say, "No, Leawood." "Is that somewhere near metro Palo Alto or Magnolia?", and I'd say, "No, it's in Kansas City." And then I'd say, "Silicon Prairie", and then that gives a chuckle, and then we have to move on. And if they push me, I can say, "the Paris of the Plains," which is nice, but my wife is where family is and I'm in a different city every day, so it's worked out phenomenal. We love it here.

Michael Krigsman: Well, tell us about Deloitte Consulting.

Bill Briggs: Yes, so you started us off on the right place. We're the biggest professional services firm in the world, and we pride ourselves in helping the biggest companies, the biggest government organizations, to transform themselves: full-stop business model reinvention, helping solve the biggest problems that they have with operations, changing the way that they engage with customers, you name it, across every industry with a global presence. And what's great is I joined the firm eighteen and a half years ago, computer engineer, along the way got an MBA, but engineering technology [is] in my DNA. And when I joined in technology, it was an interesting little side-experiment for a firm that was more often known for our tax and audit, which is still an important part of the broader Deloitte. But now, consulting is the biggest player in the world, and technology's the heart of what we're out there with clients, harness[ing] to do all of the things they need to do to drive innovation and growth, so it's been satisfying.

Michael Krigsman: How many employees do you have?

Bill Briggs: Well, globally it's over 230 thousand. That's through the broader Deloitte. I think for the US consulting, it's 80 thousand or so? We should fact-check that but it's close to it, so this is huge, which is phenomenal because I joined out of undergrad. It's really fun to see, as the next generations come up and push our thinking and help us evolve our services, and ... I still think that kid right out of college, when I'm down, especially on campus recruiting and helping our new staff through ... Then I look in the mirror and see the hairline and get reminded that maybe that might not quite be the case - in spirit, right? [Laughter]

Michael Krigsman: Well, it seems like you're having a good time there, but I think one question that immediately comes to mind is: So, you're a professional services organization, and yet, you have your ... you're the Chief Technology Officer. And so, why does Deloitte Consulting need a CTO?

Bill Briggs: Well I mean, it comes back to …If we believe that every company's a technology company, and technology is changing so quickly, and the only constant that we have anymore is the constant for change and the surety that tommorow's going to be more complicated than today. And those things come together. My role is about research, about innovation, you know, for our clients and also the investments we need to make within the consulting practice and how we evolve our services, and stay ahead of the issues our clients care most about, and invest the right way in the traditional sense with our people, with the right skills and capabilities, partnering with the right alliance vendors so we can go and make a difference; and in recent years, just as importantly investing in products and hybrid offerings, so we have a way to bring IP to the table that's not just our people and the ability to get really hard things done, but to actually come in with part of the answers pre-baked in products and offerings. And so, it's a mix between those worlds: there's research, innovation; but it's external-facing, most of the time with clients, and then, a nice feedback loop into the things that we need to be doing to go and up our game, and evolve with the same factors that are driving our clients to invest and transform.

Michael Krigsman: So a big part of your time, then, is spent helping advise your clients on their technology, investment, and their innovation strategy with respect to tech.

Bill Briggs: Yeah. And it's been fun to see that conversation, even 8-10 years ago, that was still the CIO or CTO-focused conversation within a big Fortune 50 company. What we're seeing is it's increasingly a CEO-level conversation, or even a board-level conversation, right? What are the things that we need? It's a continuum, and on one side is the hero's journey, this unprecedented opportunity for innovation, growth, which is how do we evolve our services? How do we evolve our business model? How do we evolve how we compete? How do we evolve the values of our industry? The other end of the spectrum is the existential threat of disruption. That's over every one of our clients, in every industry, including even professional services .... So, how do we make sure that you're balancing between those two very real forces? And the challenge is there's so much happening, and sometimes I use shorthand to say, "Listen, macro forces, digital, everything is happening in digital." Everything is happening in analytics, data analytics, advanced analytics, I know you want to talk a little about AI and the like; everything that's happened with cloud, is happening with cloud. Everything that's happening with the core systems we've invested trillions of dollars over the years: our back-office, our mid-office, our front office, the heart of how the business runs, how do we rethink and modernize those core systems? And then, the business of IT: the actual role the CIO, the IT department, the skills they need to bring to the table, and how they need to deliver and operate differently.

So, those five buckets, you can pick any one. So, we could play Jeopardy and pick one. And we could spend this hour on the amazing advances that happened, just in digital or just in analytics; and then you take  a step back and say, "Actually, they're all important, and they're not independent, isolated things. There's so much collision between those topics." And so, you have to quickly get away from being overwhelmed by so much "What” in the world, right? All of these things that are happening, interesting advances, new technology players and platforms. The "what" you've got to understand, but only to get to the "so what?" What does it mean to my business? What does it mean to my customers? What does it mean to my market? And then, what I think we do better than anybody is to actually get to the "Now what?", right? So, harness the "So what?" to get to the "Now what?", and then have the confidence to start making investments, because it's very easy to have “analysis paralysis” with so much potential and so much change.

Michael Krigsman: So, basically then, the easy part is observing; tell me if I'm paraphrasing correctly; so the easy part is observing the state of the world. What's much harder is to figure out what are the investments that we make, that will be the proper, correct response to that?

Bill Briggs: Yeah, and it's not being dismissed. The great work that's happening can advance those individual technology domains. And, that's certainly a challenge, just to understand the actual "what"; and the difference between the promise and the vendors, and the startup community, and the academic community, and what's actually ready for enterprise adoption. But then, the actual two things that are hard: We sometimes say, "How do you imagine? How do you deliver? How do you run the future?" And the "imagine" piece can be hard, because our natural starting point is always going to be in today, or yesterday. So, we're anchored into how we've used technology. And if you think about the earliest days [with] mobile, you might have seen we recently had a great partnership announced with Apple to drive enterprise mobile, and basically free the enterprise. Why have we changed our personal lives so much, and then once you walk into the office, the way you do your job still looks pretty similar to the way it was 10-15 years ago?

And part of the problem is when we go in, and you look at a finance process, or supply chain process, or a sales process; it's very tempting to say, "Ok. How do we take the things that we used to do and just move them to a different form factor and a different technology? And you have to say, "No, no, no. Fundamentally, how could, and how should we do things differently because of all of these new opportunities, this new potential, all the collective 'what?"' And then, once you get that "imagine" piece, then you can actually typically get a very crunchy, very real business case, which solves for the "So what?" And then, take action with the idea that we're going to learn; we're going to have to expand our scope; we're going to have more ambitions over time, and we don't have to solve for all that before we get going and get tangible progress and momentum.

Michael Krigsman: How do you explain, so, I'm sure that many of your clients are going through various types of digital transformation projects. And, how do you explain the connection between the business aspect of digital transformation, and the technology components of digital transformation?

Bill Briggs: Yeah It's perfect in any ... can't even say between the business and the technology, or even the broader digital application versus just the customer, and the marketing, and the places that are easier to start with. And, digital ... When we launched Deloitte digital almost five years ago, we had some criticism at the time, as we acquired agencies and invested heavily in creative and design, and brought a lot of things that we already did, we brought them together to get it to scale. And, a lot of it at the earliest days, were commerce, and web, and mobile development, and content management; and things that had a heavy emphasis on the customer side. And so, at the time, people said, "Why would you limit this new offering that's going to compete directly with the agencies in a way that you haven't before? And Deloitte brand, isn't that an albatross kind of holding you back?", because it doesn't have the awareness with the CMO perhaps, and it doesn't have some of the witty, pithy agencies, like, sexy gleam around it.

And even at the earliest day, when we launched it, we said, "No, no, no," because digital - all of that stuff, for sure; but it's also, how do you reshape the enterprise? How do you reimagine the enterprise; how work gets done? And by the way, most importantly, it's about how do you think about your products and services and offerings, and how do you evolve it? You have either adjacent digital solutions and services, with a physical product? Or do you actually move and pivot more directly to digital being a primary market? So, from the earliest days, we said, "It has to be all of that," and it's been great to see our model of a digital consulting agency,  be the model everyone's trying to emulate now.

But, you hit on a great... Whenever I go in an actual workshop titled as "Digital Strategy" or "Digital Transformation," almost every one of those, the most time we spend is, "Let's just try to define what we think that means." And we have workshops, and a lot of tools that we created to kind of spark that discussion. So, the executive team at a client can say, "When we say 'digital,' it means these three things." And by the way, it's typically not those are the three and the denominator is three, the only things it will mean is an ambition statement that's broad, but then we're going to go after and try to make it real, make it actionable; and we're going to translate "digital" into these initiatives. And almost always, it has things that go well beyond just that customer engagement, and sales and marketing, and the like. So that's still an important part of it, for sure. It's just not the only part of it.

Michael Krigsman: So, I would imagine that there’s a challenge that many clients face, in terms of understanding the full scope of what this actually means, and then how do they get there, because when you talk about “reimagining the enterprise,” that’s a major statement.

Bill Briggs: [Laughter] I just said, I never had more fun because there’s so much opportunity in front of … You know, not actually as an opportunity for Deloitte to grow our business, which is going to happen; but the idea that we’re helping the biggest companies in the world truly, truly, truly transform themselves. And so, the scoping that is big and complex, and challenging…

The other piece to it, that’s a real constraint, is that we’re now almost in 2017, and most big organizations have started the digital journey already, because the opportunity was so clear, and so they launched initiatives to start trying to put predictive analytics into the supply chain, and to try to have omnichannel, context-driven, personalized customer engagement across all interaction patterns, [etc.].

And so, part of the issue becomes … because each one of those has been championed by a different function or a different executive team, maybe a different line of business; to do it at the scale that we like to say the full opportunity is at, you’ve got to bring those things together, which doesn’t mean shut everything down until you have this unified, holistic vision and everyone … because the reason everyone’s investing in making the point providers they’re making is because the opportunities are very real and immediate. But, you’ve got to take a step back and say, “How do we solve for data in a more deliberate way? How do we sift software content in a more deliberate way? How do we stall for integration and APIs in a more deliberate way? How do we actually elevate things to platforms instead of point solutions, and, and, and, and, and …”

And so, that’s a big part of what we do is try to help make sense of that, I won’t call it “noise,” because “noise” might have a negative connotation; it’s just a lot of feverish activities, right?

Michael Krigsman: We have a question from Twitter, and Wayne Anderson is wondering, “How does the Chief Technology Officer relate to security compliance, governance, and the Chief Information Security Officer?”

Bill Briggs: Yeah, it’s a great [question]... I rattle off my five big forces, and I typically say the punchline of risk in cyber as the sixth, which is embedded in each one of those. Security and privacy, regulatory and compliance… And by the way, we’ve started evolving that definition to say, “In ethics and morality, in market risk and financial risk;” so, a broad risk discussion instead of making it just about cyber.

But I work very closely with our CISO, I work very closely with our advisory group that actually owns enterprise risk and cyber. It’s one of the strengths that we have, again, that fifteen years ago, when the prevailing wisdom was you have to split your consulting arm from the rest of your traditional advisory tax and audit businesses, you know, we count them together; we’re the only one that can put them all together, and now we see having that cyber as a part of our technology, digital transformation offerings.

You know, so we can make cyber and the broader risk discussion a part of the outset. When we’re doing ideation, we’re actually having those considerations at the table in the discussion from the beginning, and we know what it’s going to take, and how far we can push boundary-wise, and how aggressive we should be with any given industry and country to make sure that something that’s a discipline throughout the whole life cycle of investment and transformation. If it’s just a compliance activity at the end, to say, “Hopefully, we don’t go to jail or hopefully we don’t do something to get sued, or hopefully we don’t do something that will put us on the front page of the paper and cause a lot of brand damage,” you’ve already lost if that’s all that you’re doing.

And mostly, and a lot of my friends are CISOs, they like to kid that the worst thing that can happen is they become the Chief “No” Officer. [Laughter] Or the one putting the “no” in innovation. You spell out “innovation,” and it’s got “no” in the middle, and if you make them be the people that are always slowing you down, you’ll never get past imaginable risk, right? And we’ve got to get to acceptable risk, and recognizing that risk is real, and it’s something we have to consider, but we have to decide what’s the appropriate response how to mitigate the best. So, I love the question.

Michael Krigsman: What does all of this mean for the CIOs? Because when you say the CISO doesn’t want to become the “Chief ‘No’ Officer,” historically, for many people working in large companies view the CIO as the person who’s the king or queen of “no.”

Bill Briggs: Yeah, I mean it’s funny how if you would have asked me fifteen years ago, I would have said that CIO is one of the worst jobs, because it’s almost a no-win. The best cases that you hear their name your technology brought up in the boardroom or in the C-suite, and it’s such a completely … We actually just did, and we can clean out a link to the study… We just published a global CIO survey, and we basically found last year that there’s three big archetypes of CIOs. And one is a nicely, to say, there’s an operator which is focused on efficiency and driving the traditional things I think IT departments were asked to do: how do we get more reliable, predictable; how do we have better accuracy, to spend, cost containment; so there’s an operator archetype. There’s a business co-creator archetype, which is more of, “How do we align with strategic initiatives, and drive real change?” And then there’s the change instigator which is the one that’s the catalyst for understanding what translating to the “So what” and driving the imaginative, deliberative piece of it.

And interestingly, it’s a pretty equal mix. So we interviewed 1,200 CIOs, we find it’s a pretty even mix between them all. When you ask them [about] aspiration, it over-indexes for the business co-creator and change instigator side. But the point of it is none of them are right or wrong, you’ve got to be the right CIO for your time and for your place. And, we’ve seen over and over again, organizations that don’t have that core operational discipline in place. It’s really hard to elevate IT to anything other than the “no”. [Laughter] … The list of grievances of how things take so long and aren’t dependable and cost too much.

But in that, I think there’s this great realization that the CIO can evolve to these higher levels. It’s not a seat at the table that can be the one actually helping inform about the potential of helping spark the real investment. We shifted from fifteen years ago when I said it’s a really hard job and I wouldn’t recommend my kids getting into it. I think in 2016, it’s actually one of the most exciting jobs that you can have, if this confluence of opportunities is realized the right way.

Michael Krigsman: So, how can CIOs as well as organizations take advantage of this opportunity? And can you elaborate a little bit more on why this CIO opportunity is so great now, during this period of time of digital transformation?

Bill Briggs: Yeah, I mean, we hit on if technology’s the heart of all the change you see in front of us, and not only the full potential, but then … As we dream about tomorrow, we have to get there from today. And so, as we talk about advanced technology adoption and transformation, the thing [...] that’s still going to go through; data and systems, like people, I’ve got to find a way to unlock the foundation I have to make it more agile and let it be a contributing part, if not a really critical part of this journey of digital transformation. And so, that requires me to get there from today, I need the mooring line; as I look to the stars and the moon, I have to have a mooring line that says, “How do I understand the path there to port and how do I get back down again?” And with that, enterprise class, when we say “digital”, it’s truly easy to say, “Let’s do a lot off IoT prototypes, on an Arduino board, and we’re going to play with some open source libraries, use something really interesting, in a plant and facility, a customer site, or retail store.

We then say, “Ok, I’m going to actually sell that as a product, for I’m going to extend my core operations so that my supply chain and inventory management is dependent on that signal I’m getting from those solutions.” Doing it enterprise-class, with all -ilities; I don’t know if you ever heard of the “rattling of the -ilities before.” You get to the valid of the -ilities: [...] ability, and security, and maintainability, scalability, inflexibility, and operability, interoperability. These things have held true inside tech for so long.

We don’t get a pass because suddenly, in this digital realm, we have to think about those things. And so, for CIOs, first and foremost, technology is only more important than yesterday. It was vogue for a while for some of the analysts that the CIO role become the Chief Data Center Officer, or the Chief Electricity Officer, where the technology is a utility that we just happen to [use]. And that’s true if you only think about the world from the lowest end of the operating stack. I think the opposite. It’s the design is more important than ever. Integration, bringing all these parts together is more important than ever. Architecture, with an emphasis on “-ilities” is more important than ever. Understanding what’s coming next; the sensing, the scanning, the vetting, and bringing that to the business with an idea of what it means for your industry, for your company, for your business. You know, all of those things, I would say, are the most important things that any company could do, and do well, and who better to do it than the CIO, where she or he owns that agenda, and a lot of that knowledge today?

You know, but the flipside is what you’re doing today isn’t going to be enough. [Laughter] So, one of the things that we’re seeing is: Like what finance did 20 years ago, and like what the supply chain did 15 years ago, and like what sales did 10 years ago, the IT function itself is going through a transformation phase. And the irony that we didn’t apply technology to the technologist’s job to practice our own craft is being fixed; and so there’s this great confluence of autonomic platforms with virtualization, containerization, and cloud, and APIs, all this is coming together.

Okay, that was a long … Really struck a nerve, Michael. That was a dive-try, Michael!

Michael Krigsman: No! But this is an important issue for may CIOs, and before we leave the CIO topic, can you compare or contrast this future CIO role, say, present or future CIO role, versus what the role was historically? The reason being I think that that comparison will help people understand, help CIOs and organizations understand, where the role - the opportunity in the role, let’s put it that way…

Bill Briggs: Yeah, and I see historically a lot of CIOs kind of grew up through the infrastructure, through the application space. And so, a lot of them had deep technology jobs. And, that’s important; so the tech fluency and the tech IQ is not just important to the CIO and the IT department, it’s increasingly important to the broader business, and we’re seeing companies increasingly invest the tech fluency or the tech savviness or the tech IQ of their organization at large. For the technology-minded CIO, part of the challenge is … We have to understand how we can do things differently than how we’ve grown up, and probably earned our title, earned the role, because of this combination of new technologies and new ways to deliver the new technologies. And so, we use a construct called “Right Speed IT.” Others have used bimodal, or two-speed IT. But part of that is to say, Agile is becoming the new norm, and it’s probably a hybrid Agile, because a lot of what you have to do in those legacy systems don’t lend themselves to the same speed as the pure digital cloud development. So, how do I balance, and truly adopt Agile? - Which means a pretty significant change in my IT shop and how the business interacts with IT to deliver a project and program.

It means I have to instill a culture of curiosity, and a culture of learning in my shop, and personally in myself to stay relevant and credible. It means I have to invest in these tools, and I use dev-ops as just a number I love for a lot of things, but I need to be able to automate testing in a way that I probably can’t do at scale today, I need to automate, release management; and so it’s less hands-on, manual labor on keyboards. I need to invest in autonomic processes that help IT run, and help me free up my people to do more important things. And so, this mix, you know, and not just being the order-taker, when the business has decided to invest in a space, or even worse, the business decided to invest in a space and already contracted the vendor to do it. The CIO, the IT department, should be the spark for the imagination, and certainly should help drive the solution-shaping of what the right collection of technology should be in play. And then, owning that whole deliver and run cycle, but doing it faster. And I always say - Right Speed IT - sometimes my tagline or kicker is, “The only right speed is faster.” [Laughter] But, the idea that there are two extremes and never the twain shall meet is fantasy that I’ve never found in the world, right? This hybrid model has to be able to win.

Michael Krigsman: We have a question from Twitter, from Arsalan Khan, and I want to get through this one relatively quickly, because I want to talk about technology as well. So, Arsalan Khan is asking, “How do you think about innovation and the different types of innovation?”

Bill Briggs: [Laughter]

Michael Krigsman: Can you even give an answer to that? [Laughter]

Bill Briggs: It’s a great question! We actually have a very robust framework of ten different types of innovation, which goes from business model, and the traditional product that’s an experience, and so it’s a really great backdrop to say innovation can be a discipline, should be a disciplined process. There’s many different types that we have to think about, and not just focus on product or feature innovation, which is a bias we typically have. And then, how do we institutionalize an approach for sensing and scanning, for experimentation, for vetting, for scaling, and for potentially divesting … and there’s a way to actually… to treat an innovation response to all these disruptive forces. And, what we’re seeing is organizations actually investing in a foundry-like model that as a bit of a lab, a bit of a partnership, where they’re reaching out to the ecosystem and saying, “Our traditional vendors and new startups, and, and, and: How do you all help me and take a piece in investing with me? Because, I’m not ready, maybe, to go as full-in as I need to on any one of these topics. But I also shouldn’t have to shoulder all that responsibility.”

And so, when I mentioned up front our products, our solutions, our hybrid offerings, a lot of that is geared toward those spaces, and a lot of times with specific clients who were co-investing on something that’s extremely important in the future of their business, but they’re not ready or able to take on all the challenges themselves. And typically, it has cognitive analytics, and machine learning, and AI, and digital and these things [...] So I love the question, and if you search the ten types of innovation, it’s a great bit of work that we have. There’s actually a book written about it, and we use it all the time.

Michael Krigsman: And it sounds like this is very consistent with the Agile and dev-ops approach that you were just describing, which is also designed to bring together people who traditionally were in different organizations, or different departments, which were silos.

Bill Briggs: Yeah. And, our Tech Trends for ‘17 is going to be published next month as unbounded IT, which is trying to remove those constraints of silos, of responsibility, how do you get the other … When we started the Deloitte digital round, not only did we hire creative designers and behavioral psychologists, cultural anthropologists, and the like; but when we acquired Monitor and Doblin, true design firm, true strategy firm - it takes bringing all those together; and we pride ourselves in deep industry expertise, which is really important.

What’s really been fascinating is we’re seeing a strong desire to bring cross-industry knowledge. It’s not just how do we understand what other retailers are doing, but can we learn from what oil and gas has done to use fiberoptics to understand the actual flow of oil and gas 25,000 feet down in the ground, that same technology might be able to be used in a retail store to understand customer flow. And so it’s bringing together…You know, innovation, people think a lot about lightbulbs and Eureka moments. Most of the time it’s the importing and exporting of ideas, and we’d love to be the broker of that.

Michael Krigsman: And we have another question from Twitter. Shelly Lucas is wondering, “How do you feel about the notion of data co-ops, which are an outgrowth of data management platforms?

Bill Briggs: So, it’s interesting that we see this explosion of data, and this need to take care of not just the traditional things that we didn’t do well before, but this broader, unstructured view, and one of the Tech Trends of ‘17 is “dark analytics,” which is video and audio and image, and other unstructured techs, and the deep web and, and, and… And so, there’s a platform element of how do we create solutions that can take on all types of data, but not make it so the chaos is unrecoverable? So, the structure backing in whatever we can find, and eventually we go and sift through it.

With this idea of co-ops and other data management, and managed service - can we create teams that are working together? And for a while it just seemed like if we just had data scientists, that would be enough. But [we] actually need probabilistic programmers, and we need folks that are great with visualization and presentation, so the graphic design and … How do we actually illustrate findings, and let people explore how confident we are with the rules and the algorithms, because the move from just insight to automation, to actuation, to allowing a response to be made because of the findings that we had. You need that level of buy-in that a black box model that a machine learning algorithm isn’t ever going to show you, kind of why it came up with the conclusion it came up with, so you have to find other ways to bring that to life.

So, it’s important that two of our biggest priorities right now are data management and managed services, and they go nicely together. Very insightful question.

Michael Krigsman: One of the things that is very important to you as well, I know, are the technologies that are going to be important to us. And so, would you share with us the tech trends that you’re publishing, and how do you choose them? Why did you settle on these?

Bill Briggs: You know, every year. It’s the eighth year we’ve published tech trends, and what we try to do is say it’s the Horizon 1.5, which is the 18-24 month type of lens. And that makes it so they are pragmatic, but prognosticating. It’s the pragmatic side of prognostication, is what I’d say. So, they’re within the realm of, we think in the next year or two, we’ll see mass adoption impact. And so, it’s a yearlong process. We have automated scanning, we would meet clients, vendors, academics, startups, VC’s tap our people for their ideas, and things they think are important and coming. And so, every year, it’s the vetting, and the thing that makes it, when we winnow it down, it’s the one we want a good representation across the full breadth of domains. So, we don’t want to over-index in just digital, or over-index in just analytics, so we want to make sure we’re shining a light on the full spectrum.

And then the second is, because it’s the Horizon 1.5, we have to have real examples of real companies, or real government agencies getting some value out of these things today. It doesn’t mean they’re fully realized, it doesn’t mean they’re at the end of the journey, they could be breadcrumbs and directionally just proving out why it matters. And so, really great ideas that get scuttled the last minute is because we can’t find enough interesting client examples of who’s really doing it, and not just a one-off prototype.

Michael Krigsman: So you care about what’s actually practical. And so, what are some of those things?

Bill Briggs: So I mentioned dark analytics, which I love. That’s the unstructured traditional sources, audio, video analytics, advanced computer vision, advanced pattern recognition. It’s gonna dot, dot, dot into the deep web, which is lurking as a really fascinating potential source of complementary data. So that’s one. It goes hand in hand with another trend on machine intelligence, which is the one trying to make a point of too many people use terms interchangeably that are different, but related. So, a bit of it’s to say, “This is machine learning, versus deep learning, versus NLP, versus NLG, versus cognitive analytics, versus, versus…” But the point of all of it is there’s really great new techniques available, that we can apply, and one: Don’t get wrapped up around the technique of the algorithm or the technology. Again, understand the possibilities you can bring it back to real questions that matter, and if you have any answer to the real questions, you could do something differently in the business or in the market. And so, that’s a nice … It’s trying to bring the broader AI discussion, and make it a bit more grounded and actionable.  

Another one I love, and you might see around me some VR headsets and things in the background, but mixed reality, which is the combination of AR, VR, and IoT, and some others. But, the point not being on the individual headsets, or technologies, or sensors, or connected devices, but how we need this rich context to come together with the new engagement pattern; a new way to experience the world around us, or the world as being simulated for us, with the hooks between the physical and the digital … And, we declare success because we moved from point, click and type; to touch and swipe, and now talk. We hope we get to a new world of being beyond the glass sometime soon.

Michael Krigsman: Can you give us some examples for how mixed reality will be used?

Bill Briggs: Yeah. So, take a field service technician for an oil and gas company: when they’re on site, having the pumps with sensors that can report out its health, and help them quickly get to the place that needs repair, or maybe they’re out making a repair before it actually breaks down because they’ve got advanced analytics and data that knows that a failure is imminent, and we’re going out to prevent the downtime. But if they’re wearing some kind of a smart glass that can actually be guided to that space, so think of a GPS beaconing that’s bringing you right to whatever the piece of equipment is, and scanning to show you exactly what needs response, having [a] work aid in your line of sight, kind of stops for the repair based on all the best-knowing of every other pump like that that’s scaled in the past, potentially have you able to initiate what the second or third level support person that’s back in the home office in Texas, that can see what you’re seeing, and actually tell us straight in your line of sight to give you visual clues, while they’re giving you directions auditorily; and actually help you resolve the issue completely heads-up and hands-free. So, and then by the way, as the repair’s finished, there’s  a video and an image that gets associated with the work order, all the paperwork is automatically done because the machine is reporting out that it’s repaired, there’s proof of your geopositional where you work, video of the repair that was done - so instead of Friday being back and filling out all the paperwork and completing all the system tasks and the workflow, it’s being done for you.

That, a few years ago, would have felt like something out of - I love the TV show Black Mirror - that would have felt like something out of Black Mirror. And it’s real today! And so, our point for all of it is, even while AR and VR get a lot of attention, and even IoT gets a lot of attention with the consumer realm, and you probably guess, Michael, I’m a purveyor of gadgets so I’ve got all kinds of things around the house, it’s the enterprise: what it means to the business, what it means to the government agency, that’s where we think the biggest adoption’s going to come. And the rest will follow. It just you how far we’ve come that some of the press thought it was particularly pithy when I said, “It’s the enterprise a vacation of technology? Is the opposite of consumerization?” And we’ve swung so far over in the last few years, that we’ve forgotten technology adoption, from its inception until 6-7 years ago, it always was the workplace in the enterprise that kind of drove [it], and somehow that’s clever to say again, which I’ll take credit for it.

Michael Krigsman: [Laughter] Well, we have just about five minutes left, and we haven’t spoken too much… You’ve mentioned AI and machine learning, and so maybe, please share your thoughts on that, and also, why are the ethical implications, and ethical issues around AI, becoming so important?

Bill Briggs: Yeah, so the first part of machine learning, algorithms without us are scripting ahead of time what we want the conclusions to make. It’s finding its way to understand relationships between mass datasets, and coming up with correlations, and causation potentially that wouldn’t have been easily discovered otherwise. So, historically, reporting was just get a bunch of data, we’ll look at it, and from that, we’ll be able to intuit what it means. Machine learning is saying, “Listen, tell me a bit of what the question you’re asking is, and I’m going to go look at all the data, and the things you tell me might be important, and the things that you don’t think are important, I don’t care, I’m going to lay out everything, I’m going to trial the combinations, run a bunch of simulations; I’m going to see what actually matters and come up with some conclusions for you.”

What’s really interesting is the first round of adoption’s going to be in these sites. So, it will be an extension of traditional analytics and business intelligence. And so, here’s a few of what’s happening right now, here’s a view of what happened, and some interpretation of it. There’s not a lot of ethical debate about that one. That’s just a better way to do things we’ve done before with data.

The second one, which we think is going to be majority of activity for a while is this augmentation, where it’s actually like the oil and gas example, machine learning could have been running through all the scenarios, given the feedback it was getting from the faulty pump, and all the service history and records, and performance history records it has from all the devices it’s ever seen, can come up with a very personalized approach for that incident, for that repair person, on their level of expertise, and what we can trust them to do with the piece of equipment in front of them. And so, there’s a lot of complicated analytics happening in the background, but it’s not launching a drone to automatically fix the pump, it’s giving it to the individual to help them do their job better. So that augmentation is really where the exciting - a lot of where this is going to go for the next five years.

The last one is where you actually have cognitive agents doing the actual workload itself, potentially. And it can be in a dumb sense, so bots and RPA are topics that have a lot of potential - robotic process automation. A lot of those are just glorified strips. They’re taking repeatable tasks, and doing them in an automated fashion, brute force, instead of having someone hit F5, it’s doing it on their behalf. The end of that spectrum becomes actually, with intelligence, with reasoning, a virtual worker, a virtual agent, doing what a system engineer would do, or doing what a loan officer would do; and we’re seeing the technology advance to make those more feasible, and actually it’s happening in pockets right now. And you can tell - see why that extreme, it really does start seeming like we’re shifting a big part of our workforce to things that we ask our workforce to do potentially could be done by an artificial intelligence.

And so, it’s a real issue. And I think we need to be up front about it, that’s why we put ethics and morality in the beginning of all these conversations with our clients. And it opens up dialogue of what is the social responsibility, not just to show off things, that we care about the environment and civic rights, and a life into the employability of our people, and the people in our communities and the like. And I think we’ll see an appropriate response. Every time that humanity has said technology will forever make us unemployed we found a way to evolve; and so, if you think of this as the second or third industrial revolution, I’m very bullish on we’re going to find a way through and be even better off than we were before.

Michael Krigsman: Wow. You know, we’re basically out of time, I wish we had another hour to go. But you’ll have to come back, and we’ll do it again. But, one very last comment from Twitter - a question from Twitter, which is from Sohail Sarwar, and I hope I pronounced your name correctly, and he’s asking, “Are there mainstream opportunities for small service providers to collaborate with large firms like Deloitte?” What advice do you have?

Bill Briggs: Yeah, there certainly are. I think the thing that I always tell smaller firms is it’s coming in with very pointed opinions of where your services line up with where our clients go, or if you focus in a given industry. And, making it not rather it fill… wouldn’t it be …  I’m a big Beach Boys fan, but it’s not “Wouldn’t it be nice?”, it’s the “Here are the places where we’ve invested, here are the places where we think there’s a market, and we really think there’s a great compliment here.” You know, a lot of what we do now is help matchmake between big companies, and small vendors doing interesting things. And so, it’s just a matter of making that pointed … make that so it doesn’t take a meeting to get something exciting on the table, what that particular potential combination could be. The beauty of the time we’re in right now is there’s no such thing as “too big to fail,” and there’s also no such thing as “too small to matter,” so …

Michael Krigsman: So be simple and clear and have a very specific understanding of what the needs of the target are.

Bill Briggs: Yeah. For sure.

Michael Krigsman: Well, we are out of time. We’ve been talking with Bill Briggs, who is the Chief Technology Officer of Deloitte Consulting. And I have to say before we go, you have a most interesting office.

Bill Briggs: [Laughter] Thanks! You know, it’s funny how for a long time, you had to kind of hold back your, let’s call it “geek sensibilities” and things, and as engineers and technologies inherited the Earth, it’s nice to be able to celebrate what a lego death star or a chess set …. There’s a Notre Dame helmet behind. I’m still a proud Irish alum, even if we’re on dire times right now, but thank you!

Michael Krigsman: [Laughter] And you have a guitar.

Bill Briggs: Yeah, and there’s pinball machines right through there, but we’ll have to do the Cribs episode next time, Michael. Maybe we will. Secret doors, home theaters, pinball machines, Hefe cans, it’s a beautiful thing.

Michael Krigsman: Well, next time we’ll ask you to play for us.

Bill Briggs: Okay, sounds good!

Michael Krigsman: Alright. Well thank you so much, we have been talking with Bill Briggs, who is the Chief Technology Officer of Deloitte Consulting, and you’ve been watching Episode #206 of CXOTalk. Tune in again next week. Thanks a lot, bye-bye!

Digital Transformation at Scale

  • Episode: 205
  • |
  • Topic: Digital Business
Didier Bonnet, Global Practice Leader, Capgemini
Didier Bonnet
Global Practice Leader, Digital Transformation
Capgemini
Michael Krigsman, Founder, CXOTalk
Michael Krigsman
Industry Analyst
CXOTALK

For large organizations, digital transformation involves rethinking processes, technology, and customer relationships. On this episode, we talk one of the world's top experts on digital transformation in big companies. Didier Bonnet is an author, researcher, and leader of Capgemini's digital transformation practice.

Didier believes that Digital Transformation will have a profound impact on all sectors and that no company will be immune from this transformation. His interest is in understanding how digital technologies are impacting every aspect of business: strategy, customer experience, people and operations. In his view, the digital revolution creates huge opportunities to make organizations more efficient and responsive, to change the way people work and share, as well as strongly enhancing the experience of customers as they interact with organizations.

Didier is co-author of the book: Leading Digital: Turning Technology into Business Transformation, published by Harvard Business Review Press. Leading Digital makes the provocative argument that the next phase of digital technology adoption will make everything that’s happened so far look like a prelude. Based on researching over 400 global corporations, Leading Digital presents the DNA of Digital Masters, those companies that have mastered digital transformation to gain strategic advantage.

Prior to his current role, Didier was the Global Leader of the Telecom, Media & Entertainment practice at Capgemini Consulting for 15 years. He joined Gemini Consulting as a strategy consultant in 1991. He has more than 25 years’ experience in strategy development, globalization, internet and digital economics as well as in business transformation for large multinational corporations.

Didier graduated in Business Economics with an MBA from a French business school and holds a DPhil from Oxford University.

Transcript

Michael Krigsman: Welcome to Episode #205 of CXOTalk. I’m Michael Krigsman. CXOTalk brings together the most interesting, innovative leaders in the world These are people who are genuinely shaping the future. And, I’m again, Michael Krigsman. I am an industry analyst and the host of CXOTalk. Today, we’re talking with a very interesting gentleman, an old friend, who is named Didier Bonnet, who is a senior executive at Capgemini, one of the largest consulting firms in the world. Didier is an author, he is a researcher, and we’re going to be talking about digital transformation inside large companies. Didier Bonnet, how are you?

Didier Bonnet: Very well, thank you. Glad to be with you.

Michael Krigsman: Well, it’s so good to see you again! The last time we spoke was about two months ago, and you were here in Boston?

Didier Bonnet: ...over dinner!

Michael Krigsman: Over dinner! And so, I’m so thrilled that you’re here on CXOTalk.

Didier Bonnet: Oh, thank you! Thank you very much for inviting me. Delighted!

Michael Krigsman: So, Didier, please tell us about Capgemini, and tell us about your role at Capgemini.

Didier Bonnet: Ok. So very briefly, I belong to the strategy and transformation arm of Capgemini, which is called Capgemini Consulting. It’s about 3,500 consultants focused entirely on digital transformation. And of course, we’re part of the bigger Capgemini group, which is about 13 billion dollars, 180 thousand people worldwide really delivering the technology that we’re trying to shape as consultants. Within that time, I run the digital transformation practice globally, and also responsible as the exec sponsor for our research partnership with MIT.

Michael Krigsman: So, you spend a lot of time talking with large organizations, and you wrote a book. And you know, why don’t you tell us briefly about the book that you wrote as well, because I think that will feed into our conversation.

Didier Bonnet: Ok. So I think the whole, without going too far back in history, I mean one of the things that surprised me - this is going back to around 2009, when I started really looking at this phenomenon - most of the stuff that was written in the press, or that you could see in research, was around industries that were really either tech industry, or Apple, or Google, or the music industry, the publishing industry. So all the industry that I like, or companies that I like. Altogether, these industries represent about 6% of the world economy. And, I sort of said, “you know, if this phenomenon actually transfers to many more industries (which I believed at the time), then we have 94% of the world economy which is not looked at.” And this 94% is composed of fairly large companies in very traditional industries like pharmaceutical, like manufacturing, like banking, insurance, retail … So I really wanted to focus on really looking at what happened: How do they shape this transformation in large companies? Because, as you well know, large companies have been in existence for hundreds of years, sometimes with loads of legacy systems and organization. And therefore, the transformation is a really complex endeavor. So we’re really focused on that.

And I found a wonderful partner with MIT that was willing to get along with the journey with us. And really, for years, try to put some frameworks and understanding and data around what’s happening in digital transformation in large firms. In those days, very few people were talking about digital transformation, but we really were focused on really shaping: “What does it actually mean? What areas of the firm does it actually cover? Where do you actually start? What kind of capabilities do you need?” And really the book is about conveying those frameworks, particularly how you go about them - evolving and changing your organization for digital technology.

And, the purpose was really to say, “You know, if we think what’s happening right

Michael Krigsman: Welcome to Episode #205 of CXOTalk. I’m Michael Krigsman. CXOTalk brings together the most interesting, innovative leaders in the world These are people who are genuinely shaping the future. And, I’m again, Michael Krigsman. I am an industry analyst and the host of CXOTalk. Today, we’re talking with a very interesting gentleman, an old friend, who is named Didier Bonnet, who is a senior executive at Capgemini, one of the largest consulting firms in the world. Didier is an author, he is a researcher, and we’re going to be talking about digital transformation inside large companies. Didier Bonnet, how are you?

Didier Bonnet: Very well, thank you. Glad to be with you.

Michael Krigsman: Well, it’s so good to see you again! The last time we spoke was about two months ago, and you were here in Boston?

Didier Bonnet: ...over dinner!

Michael Krigsman: Over dinner! And so, I’m so thrilled that you’re here on CXOTalk.

Didier Bonnet: Oh, thank you! Thank you very much for inviting me. Delighted!

Michael Krigsman: So, Didier, please tell us about Capgemini, and tell us about your role at Capgemini.

Didier Bonnet: Ok. So very briefly, I belong to the strategy and transformation arm of Capgemini, which is called Capgemini Consulting. It’s about 3,500 consultants focused entirely on digital transformation. And of course, we’re part of the bigger Capgemini group, which is about 13 billion dollars, 180 thousand people worldwide really delivering the technology that we’re trying to shape as consultants. Within that time, I run the digital transformation practice globally, and also responsible as the exec sponsor for our research partnership with MIT.

Michael Krigsman: So, you spend a lot of time talking with large organizations, and you wrote a book. And you know, why don’t you tell us briefly about the book that you wrote as well, because I think that will feed into our conversation.

Didier Bonnet: Ok. So I think the whole, without going too far back in history, I mean one of the things that surprised me - this is going back to around 2009, when I started really looking at this phenomenon - most of the stuff that was written in the press, or that you could see in research, was around industries that were really either tech industry, or Apple, or Google, or the music industry, the publishing industry. So all the industry that I like, or companies that I like. Altogether, these industries represent about 6% of the world economy. And, I sort of said, “you know, if this phenomenon actually transfers to many more industries (which I believed at the time), then we have 94% of the world economy which is not looked at.” And this 94% is composed of fairly large companies in very traditional industries like pharmaceutical, like manufacturing, like banking, insurance, retail … So I really wanted to focus on really looking at what happened: How do they shape this transformation in large companies? Because, as you well know, large companies have been in existence for hundreds of years, sometimes with loads of legacy systems and organization. And therefore, the transformation is a really complex endeavor. So we’re really focused on that.

And I found a wonderful partner with MIT that was willing to get along with the journey with us. And really, for years, try to put some frameworks and understanding and data around what’s happening in digital transformation in large firms. In those days, very few people were talking about digital transformation, but we really were focused on really shaping: “What does it actually mean? What areas of the firm does it actually cover? Where do you actually start? What kind of capabilities do you need?” And really the book is about conveying those frameworks, particularly how you go about them - evolving and changing your organization for digital technology.

And, the purpose was really to say, “You know, if we think what’s happening right now with those technologies is completely magical and superb, we ain’t seen nothing yet. What’s coming ─ and you know that very well what’s coming down the pipe ─ with robotics, with artificial intelligence, is going to make the software technology even more amazing. And, therefore, the opportunity for business is even bigger.

But, the only firms that will be able to leverage that are the firms that are able to transform themselves and have gone through a few cycles to really integrate those technologies for business benefits. So there’s really the story of how we … So after four years, we published that book and since then, we’ve continued drilling down into the topic in a more precise segment of the digital transformation journey.

Michael Krigsman: I remember when you were doing that research before you published the book, and at that time, digital transformation was a relatively new concept, and you were right on the cutting edge. Today, if we fast-forward four years, digital transformation has become kind of this almost meaningless buzzword. Every marketing department, every business marketing department, it seems, have adopted the phrase, and it means whatever they want. And so, from your standpoint, having been researching this, and really one of the pioneers in this, what does “digital transformation” actually mean? If we strip away the jargon and the hype, what is digital transformation?

Didier Bonnet: Yes, so I think you’re right. This...Today, everybody who’s either selling a product or doing something with technology is either using the term “digital transformation,” and unfortunately I couldn’t come up with anything different. So, I will stick with that for now. But to me, it’s kept its original meaning. It’s really how do you fundamentally transform the business operation and the customer experience, or the business model of a corporation through the use of digital technology? And the emphasis is really not so much on the beauty and the power of the technology, but more of its effects on organization for the benefit of the customer or productivity or efficiency or whatever. So, I still really, in my head, every time I talk to a client or I start to figure out a problem around that, really try to think in terms of, you know, connecting with my customers, which are themselves changing and getting more digital about…

As you know, today, the operational side is really taking great prominence with the Internet of Everything, but also automation, and artificial intelligence; and also thinking about business models. Because, we’re in a world where equally the word “disruption” is being bantered around all over the place ─ everybody’s getting “disrupted” and it’s all about disruption. And really try to get behind that and say, “Ok, who is getting disrupted and at what speed?” and “How do you defend, as a large corporation, against potential disruptives?”

Underlying all this, you see there’s a big layer of digital platforms, which is the next evolution of the IT platforms, that is happening. And also, a massive endeavor of analytics. You know, today we talk about that Big Data and analytics. But, if you look at these large corporations, just getting to the point where you can condense the data that you need, and then getting to the point where you can take that data and make different decisions is a massive endeavor for these ─ I’m talking about, you know  ─ multibillion dollar global organizations that are thought to go through these processes.

So to me, the point of these exercises is really to say, “How can I really transform my organization through the use of digital technology?” With the main goal being, “Can I actually move the needle on my bottom line or my top line?” Because, that’s what business is all about.

I forgot to mention one thing, which is that I think I’d like to emphasize (which is equally important is, in note of this) I still have the fundamental belief that despite the fact that these transformations are really technology-based, and very complex technology, there is still a massive human element behind that. So, organizations are made of people, and I think we have to understand that as part of a transformation, if you don’t get your people on board, upgrade their skills, and really engage them in this transformation, usually it’s not a good sign for succeeding in this kind of transformation. So that’s kind of our, if you know what, it’s a pretty broad topic. Not everybody’s trying to do floor-to-ceiling-type of transformation. You can start with your customer experience. You can start with operations. But fundamentally, these technologies are really going to touch every single point of the organization and to some extent, that’s one of the messages I said in the book. Hence the need for a good strategy and a good vision, because you could spend a ton of money to try to, you know, change everything in your organization. But, you can’t truly change every part of your organization with technology. So one of the exercises is, “How do I focus my investments to make sure that there is a payoff?” and also “Whether the organization can actually deliver on the vision, and on the strategy?”

Michael Krigsman: One of the pieces that I think is so interesting, is the fact that we’re always talking about putting the customer in the center. And why is that so important for digital transformation?

Didiet Bonnet: So I think that’s a good point. I think to be honest in fact, up until a few years ago, if you start[ed] a conversation about digital transformation with most executives, you’d end up talking about digital marketing, social media, and this kind of discussion. Primarily because the major focus, I don’t know, it’s probably not 100%, but it certainly is a large percentage, maybe 80% of the activity was focused on the front-end. And, to be honest, there’s nothing wrong with that. I mean, customers are what the firm’s all about, so it’s quite right to start with the customers. But I think it’s probably missing a big point in terms of the other potential parts of the front end that you need to align. And by that I mean that, for instance, if you take an application where you’re changing the way that you connect with your customer, you probably… a big part of the work is going to be around the customer experience, but a big part is going to be about, “How do I deliver on that promise from an operational perspective?” And if you think about e-commerce or short-run delivery, or the last mile for if you’re in the retail industry, these are all operational issues that you have to solve at the back of the customer experience. 

So the reason mainly that people, in my view, start with customer experience is a good reason, which is: How do we really improve the customer experience from, this kind of silo delivery that we have? And also because digital has just multiplied the touchpoints so much, that we have, you know: kiosks; loyalty cards; social channel ─ I mean, you name it. We have a multitude of touchpoints with the client; it’s becoming more and more complex to connect in a seamless way with your customers. And hence, all the projects and endeavors that we see over the last few years around multichannel integration, because it’s an incredibly difficult exercise to do. And I think it’s quite right to start with the client.

Probably also, as you go in front of your board and ask for investment, it’s probably easier if you say it’s about [the] customer than it is to say it’s about something else in the organization. So there’s probably that as well. But I think the focus on the customer for me, is every transformation that I see being successful has always been fairly customer-centric, and really taking an outside view of the organization. Because you know….Most industries today are facing a set of clients that are fundamentally changing themselves, and we talk a lot about Millennials. But, I think it’s not just age groups that are changing, so it’s not just demographics that drives that. It’s actually behavior. So, we’re seeing...And if you look at the research, you will find that demographics is only a good indicator, but you find a very traditional and conservative 30 year old, and a very digital-savvy 55 year old. So, you cannot be a perfect guide.

So that is really important, because the way these people want to interact with the firm, want to engage in … with the firms are fundamentally different. And the more traditional corporations have really got to understand that and recalibrate how you want to do banking. I’ve been banking with the same bank for 15 years. I love them and I’ve never talked to a single employee in all these 15 years, and I’m happy with that. So those are the kind of things that are really changing the way that we connect with our customers.

Michael Krigsman: We have an interesting comment from Arsalan Khan on Twitter. And he’s pointing out something that I was going to ask you about, which is: “Is it fair to say that digital transformation is the business process re-engineering of our time? Or is there something different here?”

Didier Bonnet: Yeah, so it’s a very good question. I really like that question, because I actually believe so. I think you actually have to look at it as a portfolio. So digital re-engineering, re-engineering has bad press. I don’t know why, but it has bad press. But, I think yes. A part of digital transformation is about re-engineering. So in other words, if you’re touching… if you think about a two-way matrix where on the one hand, you’re not really covering the entirety of your value chain, so you’re looking at maybe a single department like maintenance, or something like that; and on the other hand, it doesn’t really have an impact on your business model. Then, you’re truly in the world of re-engineering with digital tools. And you know what? There’s nothing wrong with that. Actually, I love projects and programs. And I love to see clients who have got a good dose of this kind of re-engineering aspect to it, because that is a route to a faster payback, and it’s also the route to raise investment capacity that you can then invest in the things that are truly transformative. So, in other words, the things that are much more complex to deliver from the value chain perspective ─ and I mentioned multichannel integration, for instance. That covers something you want to work right across the silos and the organization.

Or the things that are changing your business model. And if you think about, you know, what GE has done with the, you know, the industrial internet and Predix. I think that’s a good example of a digital transformation that’s fundamentally changed the nature of your business: how you go to market; the kind of skillset that you have to hire; and so on and so forth. So, I think you have to think about it like a portfolio of activity where some of it will be more re-engineering, some of it will be tweaking your business model without changing too much. So, think about the insurance companies selling insurance by the hour, or mobile phone. You know, that’s a fundamentally new offering, but it’s not really changing your fundamental business model. Then you have the really complex, I would say, cross-value chain type of transformations. So, if you think about banks, and telecom back-office system, it’s a mind-boggling endeavor to actually start, you know, modernizing and automating this current system. And then in the GE example I’ve just taken, where it’s complex from a value-chain perspective, and complex from a business model perspective. And these are kind of the moon-shots and the big bets that people are taking, and I think GE is going to …You know, if you think about when … how long they’ve taken to actually do that. You know four years is actually a very short time. And it’s an example of an impressive case.

But, I love the question, because people tend to think always about disruption: “We have to change everything!” No! I think you have to think every type of these… within a big digital transformation, you have different types of programs, and each of them have got a different risk profile, and a different investment profile, and a different timeline. And actually, it’s good to manage it as a portfolio so you can add your bets, and your risk, and your investments.

Michael Krigsman: It’s very interesting to hear you describe it as a portfolio of activities with their own investment, their own timeline. To what extent are companies making the big bet change, that you were talking about at the extreme? I mean, if you read the press, it seems like every other company is, you know, completely rethinking their whole business! But …

Didier Bonnet: ...Yes, and…

Michael Krigsman: … But I was going to say it’s not quite …

Didier Bonnet: So I see different types of companies. I think they are companies… You’re absolutely right where we have big discussions around, you know: What if we get disrupted over the next three years? We need to change our business model completely. You know, it’s going to be a radical change for our capabilities, and so on and so forth. And then when you look at the digital transformation roadmap, it’s mainly optimization. It’s mainly optimizing the existing. So, there’s a gap between the strategy thinking, and the actual delivery. So I think that’s one case.

I do think that this is why I really emphasize this notion of managing as a portfolio, because you need to have both your eyes on protecting what you’ve got today. So, you’re getting attacked in your backyard on a daily basis by all sorts of competitors, being the traditional ones, but also ones you’ve never heard of, or people that are not even in your industry. So you have to protect that backyard. And at the same time, you have to keep an eye on, “What is the future state of my organization if I want to be successful and doing well?” So you have to have kind of two heads all the time, and to some extent design your programs that way. Hence, my point about portfolio, because the way you tackle those initiatives are very different.

 For instance, let me give you an example. If you think this technology might have an impact on your organization but you’re not sure ─ things like AI or robotics, or really anything today; 3-D printing; and it’s quite okay to have what I call “edge” innovation. You have a sandbox or an innovation department that actually talks about this technology; try all the math; see if there’s some sort of application… But this is a long-term process because it takes a while to nurture those technologies and bring them to the business side. But it’s also the reasonably limited risk for an organization to do that.

If you’re in a case where your business model is entirely dependent on an acquisition of skills. So, for instance, if you’re a bank, and you have very little data analytics capability today, then your route may be more in acquisition, because the speed to market becomes essential for your strategy. So, the acquisition becomes a nice way or a quick way. It’s not cheap, but a quick way to get access to these skills.

Equally, I mentioned earlier on the very complex transformation that some industries are contemplating today. You can do it in house, but you can also greenfield. So, in other words, a few companies are actually doing that as we speak, which is basically: If I know it’s going to take ten or fifteen years to change my call systems and my call processes within a firm, then is it not quicker to start with a greenfield operation, where I can build a stack which is completely different of new technologies and new processes targeting a certain segment of the plan and then slowly migrate my existing base to that.

So I think that’s, again, the notion of every piece of the portfolio that I’ve described earlier has got different ways to go to market whether you have time or not, whether you have money or not. And it includes things like innovation processes that you could put in place, whether it’s a fund or a sandbox, or an innovation center in California or whatever, or whether it’s acquisition, or even greenfield. So that’s kind of the panoply, I would say, of tools that you could use to actually deliver on that.

But the point you made is very valid. You have to do that, because you have to keep an eye on what you can optimize today, which is worth doing from a technology and a re-engineering aspect. But, also the part that you’re going to start touching your business model, and therefore, creating some real danger in your competitive position. And this has to be tackled too, through acquiring capabilities and understanding where the market is going to end up, and really taking a position early on.

The trick that’s the most difficult in all of this ─ and I see most CEOs I talk to really struggle ─ is everybody talks about disruption, but nobody’s putting a timeline on it. And so, for a businessman, if it’s all going to collapse or go off ship in two years, or in twenty years, it has massive different implications as you can imagine. And I think part of the strategy ─ part of digital transformation ─ I think really needs to crack, in a pretty deep and fundamental way is: How long are we talking about? And because, if you’re …

I’ll give you an example where this has become an impediment actually. I see a lot of financial service institutions, for instance, that I mean they are being disrupted left, right, and center by all these startups and businesses. You listen to them, you feel like the business is going to collapse tomorrow morning. And then a month later they publish their results and they’re up 20% in profits, up 10% in sales or whatever. And therefore, and this is good. But, the problem is that there is no way to generate the need and the excitement to actually transform, because there’s no pressure from the top. If you’re in trouble, it’s easy because it’s what I call a type of crisis-induced type of transformation. They’re easier because you have a natural enemy, which is your business is degrading very fast. So if you think about the post office business, for instance, it is clear that the latter business is going down like a stone, and it’s not going to come back anytime soon. So you have to think about a fundamental shift in your business.

If you’re in the bank, or in pharmaceutical, or some of these industries, and your results are great, and you’re still growing and making good money, then it’s harder for maybe not the CEO, but at least to convince a sufficient population of your exec. to actually have the empathy and the willingness to really change the organization. So, I think this notion of pressure is pretty important.

Michael Krigsman: So you’ve been talking about the business and really, the human element of transformation. But, you mentioned earlier, when we were talking about the components, “What is digital transformation?”, you mentioned earlier about platforms and data. And so we know the technology has some role to play here, and what is the role of tech?

Didier Bonnet: [Laughter] It’s huge, it’s huge, because it’s … So first of all, I think the notion that, and it’s a notion I’ve been fighting against for a long time, that we have technology on one side of the organization and the business on the other is such an old-fashioned concept. I mean, I think we’ve got to get rid of that as soon as we can. Unfortunately, that’s how we designed organizations ninety years ago. And you know that for a very long time, the IT department or the technology department had the virtual monopoly of technology introduction in the firm, and we know that is gone! This world is finished.

But it goes further than that. I think the education of executives in organizations needs to change. By education, I don’t mean your university degree, but what you yourself learn personally. It is virtually impossible for, in a company, to have executives today that have absolutely zero tech-savvy competencies. You know, it’s impossible. You know, in the US, I must at least have a collection of fifteen business cards of people whose job it is to be CTO marketing, and I always said, “What the hell is that?” And, they usually tell me, “Well, you know, there is so much technology just around the marketing function, or just around the automation of marketing tasks, that you need to actually start sifting through all of these technologies to truly understand what that can do to your business.”

So my point is, technology, with a big T, has a role to play at any point of this transformation. It’s not going to go away, and I think it’s more the opposite. I think we’re seeing more of a fusion between IT and the business side, where IT people have got to be much more educated around the business challenges, and the business strategies that the company is trying - to become businesspeople. And equally, the businesspeople ─ the business side ─ has got to become much more attuned to what technology can do for them. It doesn’t mean that each are going to replace each other; that’s not what I mean. But I think there needs to be a lot more communication, a lot more cross-functional collaboration between these two teams. And therefore, the levelling, even the language to be able to communicate is important. And of course, the best companies I’ve seen in the research world, the companies where the businesspeople were totally okay to have a technology conversation, and then the IT guys were totally okay to have a conversation about channel strategy. And that’s where you want to end up - as people that are really…

Because [this] is not the world where (with maybe a few exceptions in the world of systems and records) a world where we were having technology developing in a dark corner ─ all this kind of stuff, and making sure all the lights are switched on is over. If you want to succeed in digital technology today, or in digital transformation, these two worlds have absolutely got to fuse. And I must have done 55 or 60 projects, which were usually titled, “How do we align IT with the business strategy?” And I think this is, again, over. It’s not about alignment; it’s really about fusion. And the way that you deliver these projects has got to be with cross-functional, multiskilled team that includes IT, creatives, marketing people, supply chain people, and so on. So we really have to … to some extent, we’re breaking down some of the natural barriers we’ve built in the organization over the years. And this is, in a very large organization, very hard to do.

So back to your question. Technology with a big T is, to me, 100% component part of digital transformation. And, the IT groups within that called the CTO groups within that, absolutely have got to play their part. You cannot do business transformation properly without the complete collaboration of these communities. And I know a few companies have tried, and I’ve seen very, very few succeeding without actually involving the technology side of the business.

Michael Krigsman: I want to remind everybody that you are listening to CXOTalk. I’m Michael Krigsman, an industry analyst and the host of CXOTalk, and our guest today is Didier Bonnet, who is a senior executive with Capgemini consulting, and truly one of the pioneers writing and researching digital transformation. So, Didier, you were just talking about the need for businesspeople to understand tech, and technologists to understand the business. But when you have this kind of environment, what actually is the appropriate role for IT? In the best organizations that you’ve seen, what’s the role of IT?

Didier Bonnet: Right. So, the organizations that I’ve seen that were really successful at digital transformation are I think, first of all, I will go back to a leitmotif of our research and the book, which is that it’s leadership plays a massive role. So, you just have to look at the leaders. And some of the leaders that I see were CIOs, or CTOs driving or helping to drive these transformations, are people that are absolutely understood what this transformation is about ─ understood the way that you deliver. The way that you experiment in a digital environment is very different, and absolutely part of not only delivery of the system, but the conceptualization of the business problem, and the business solution. So, you do have to have a different mindset.

I’ve also seen the opposite. I’ve seen people that have stayed in their traditional model of IT delivery. And I personally don’t think there’s a great future for these type of leaders, because I think the world has moved on. But equally, I think we’ve gone a little bit too far sometimes in the price where I see a lot of us talk about “bimodal IT”, and “dual speed IT”, as the panacea of everything. I’m always a bit careful, because I think I’ve seen, you know, a CIO actually running bimodal-type IT within the IT department very effectively. So, it’s not a matter of taking out some responsibility for IT and putting it somewhere else, whether it’s in marketing or somewhere else. It’s more about can we actually have these dual demands of, on one hand, having some systems which are absolutely fundamental to the corporation being run with 100% safety, 100% reliability ─ if you think about the back office of the bank, for example, a transaction processing system. And that is not going to change; you’re still going to have to have this level of utmost security and delivery. But on the other hand, you have a more, I would say, untraditional type of IT, where you’re doing a lot of piloting, a lot of proof of concept, a lot of data capture. So, you can actually trial many more experiments, and then if they work, scale them. If they don’t work, throw them out; then move on.

And, the type of competence of people that you put in these two boxes are very different. The type of IT delivery process, delivery methods, that you use are very different than at once … I promised myself that I would not mention the word “Agile” but I’ve just done it. So, [laughter]... So you know what I mean… So all this is very different. However, it doesn’t mean that they have to be separated from the technology function. I’ve seen cases where it worked extremely well, when it stayed within the IT department because the technology leaders have the perspective - the view and the vision to say, “I get what you’re trying to do. I understand, and I will reshape my IT department very, very differently.”

Equally, we’ve seen examples where, you know the IT [garbled] in this traditional mode of everything you say ends up with two or three months of requirements gathering with the business, and that doesn’t work. So, people have recreated IT functions or digital IT functions, separate from the traditional IT. So, you don’t have to do it; it just depends on the kind of leadership and competence and capabilities you have within the IT function. And that’s why you’ve also seen cropping up digital divisions, or digital development units, all over the place. It’s really to try to capture that kind of new developments that these are absolutely essential to the world of digital.

But, there’s [garbled] there is no silver bullet that says it should be in IT, or we should throw away IT and start anew. You need both and you need a little bit of … you need a lot of leadership from both sides ─ the business and technology ─ to really figure out what is the best solution for your particular organization. Because, for instance, the form of your particular organization can be very cultural. So if you’re a highly decentralized organization, and you’re building a very centric and centralized type of IT, digital IT solution, it’s very hard to make it work. So, you have to really figure out how the organization is constructed ─ what’s the culture of the organization, how people work, how it’s structured ─ in order to do effectively these kind of IT developments and digital developments.

Michael Krigsman: We have an interesting question from Shelly Lucas on Twitter. And you know, we always talk about the best practices with high-performing organizations, and Shelly’s asking, is there something that you have seen, in relation to digital transformation out in the field, that just shocked you?

Didier Bonnet: Yes, there’s many. Many. I’ve seen a few shocking things. I’ll tell you the main one, and it was a surprise to me. I’ve always had an eye on the human aspects of this change, for obvious reasons. Because I’ve studied organizations for a long time, I know that an organization is just a collection of people, [in] the end. And if you don’t get the people aligned and engaged, then nothing will happen. So, I spent quite  a bit of time trying to understand how is it we are currently facing one of the biggest skill change, or skill improvement, or skill update in our corporation?

Some of the biggest that I’ve seen in my career is that we are all to make an effort within an organization to really challenge ourselves ─ to reskill ourselves ─ whether you’re in marketing or in technology, or anywhere. And yet, I’ve rarely seen the HR departments in large organizations being in the game or at least in the driving seat. That was a big shock to me. But, there were a few exceptions where HR were really taking on the baton. Usually the people that were caring were the operations people ─ the COO, or the CIO, or you have the people who really understood that, “Oh my God, we’ve got to get the people with us. We’ve got to up-skill the whole marketing department to be able to handle the digital capability, or we don’t have any … You know, we talk about analytics but we don’t have any data scientists to speak of. So where do we get them?” That kind of stuff.

So, this skill change is very important. Mainly it was driven by the business, and I think my plea to corporations is we have to really, rather than counting the number of holidays, there’s a bigger problem. There’s a problem that needs to be tackled, which is “How do we mass-skill?” And we’re talking about scale ─ sometimes hundreds of thousands of people. How do we mass-skill the population? Because otherwise, you will end up, which is already happening in some firms, with a kind of two-speed community. It’s not two-speed IT anymore; it’s a two-speed community of people who get it, and people who don’t. There are plenty of things that, when I say HR, I’m not pointing the finger at the department or anything.

Largely, the people who care about the development of the people within an organization, and being able to design programs, but really re-skill the organization. And, of course, it’s about hiring and training. But, it’s also about incubating. It’s about conquering. It’s about doing reverse-mentoring program. Whatever tools you can use, there’s a whole panoply of them that you need [such as] building your own transformation university, which many companies are doing right now. So it’s using this tool to really scale or mass your population, because if you… One of the findings we had from the research was when you ask the corporation, “What is the biggest impediment to you accelerating your transformation, your digital transformation?” In 80% of the case or 77% of the case, the answer was “capabilities and skills ─ people”.

So, we’ve got to tackle that problem, because it’s not going to go away. And we don’t have the luxury of waiting until all the people who are not skilled retire and then we hire new ones. So really, my plea to the community in HR, is to rebuild … We used to call them in the old days “organizational development, [or] management development people” ─ people who really get the business side of up-skilling an organization. And I think these people need to come out, or be hired to really support the transformation, because the business is already overloaded with digital initiatives and transformation. And we really need support from every function in the firm. So that was a big surprise for me during the research.

The other one was the number of people who say they’re not talking now… CEOs mainly, who would say, “Yes, digital transformation is important, but I will wait until my competitors move,” or “I will wait until something else happens, and be a fast follower.” And, you know, the number of people … or delegating, or saying, “[I] put one guy on the job to look at digital transformation,” and you find out the person is Level -5 [Level minus 5] in the organization. So, you know from the start that this is not going to work. This lack of awareness, and I think it’s getting better over the years, but this lack of awareness of what we’re talking about here, which is not another fad ─ you know another technology fad that’s going to go away in two years ─ but something that’s really going to profoundly change the shape and operation of your organization. So those would be the two main ones.

Michael Krigsman: We have just a few minutes left. Now, where does all of this go? Where is the future of digital transformation? And maybe, you can give us a glimpse into some of the research topics that you’re focused on next, because I know you’re beginning your research and your writing cycle, authoring cycle. So, where are we going?

Didier Bonnet: So, yes. So this is a question I get all the time. They say, “Didier, you keep talking about ‘digital transformation’, but surely, now everything is digital so we should stop talking about digital transformation,” and I wish it were true. Unfortunately, it isn’t. I think we on balance … I think very, very few corporations have really, truly transformed to the point where they are totally at ease with integrating all these technologies. And second, the flow of technology is just not going to stop whether we like it or not. And I have a lot of clients saying, “I wish that this technology could just stop for two or three years so we can integrate all this, and we’ll see the next way.” But, that ain’t gonna happen.

So, we’re going to see more advanced technology coming on board. The cycle time between research, prototyping in the labs, and going into the business front is reducing. I mean, think about 3-D printing. We’re getting composite material 3-D printed nowadays, and it’s already being trialed out in the business world. So, really reducing cycle time. So, I think this agility ─ it’s a bit like running a marathon, you know. You need to do a lot of digital transformation because it helps you to stay the course in the flow of all this technology.

So where is it going? I think for the firms that are really, I would say, at the forefront ─  the firms that we call “digital master” in the book ─  I think what you’re starting to see is fundamental change in the way that these corporations actually work. And they’re around not just the digital mindset, but the way that, for instance, the organization is flattening. And I’m not a believer in the completely flat organization with no boss or anything. I don’t buy that. But you do see the organizations flattening. You do see a lot more decision power coming closer ─ where the large decisions are being made or the important decisions are being made because you can at the same time delegate power but at the same time control the data. So, that is happening. And therefore, the decision base ─ database decision making ─ is becoming more of a way of operating for these kind of firms. And you’ll see also a lot of automation happening, which has got positive implications for productivity and efficiency, but also some pretty negative implications for staff and employment, which we’re going to have to tackle.

So I think there’s a layer of fundamental organizational change that is happening to corporations, which is starting to change the shape of these 19 year old organizations that were designed basically on the military model, where information was cascading top-down. There were middle managers and all this kind of stuff. So I think we’re seeing a crumbling of that. It’s just it’s very hard to figure out what’s the end-game. So, we tried to put some fresh [thinking] around that with the MIT [garbled…], try to get at least some directions as to where the organization is going, but it’s very, very hard to figure out where is the end-game. It’s fundamentally going to change the way that we structure functions within the firm, I believe.

And then the second part of where the future is going is I think we’ve got to… I’m a firm believer in that we need to recreate and reinvent corporate innovation. You know, one of the things that large firms are always scared by? Startups. It’s always startups that are going to eat your lunch and you get [you. You know ], somebody tomorrow, [a] 200,000-people insurance organization is going to be killed by two guys and a dog in San Francisco. Maybe. But I think the corporation can fight back. There’s one lever that a corporation can use is scale. Because if you talk to a startup, that’s what they want. They want scale. They want geographical spread. They want distribution channels. So, it’s how … We need to really fundamentally reinvent that corporations actually do innovation. And it’s quite a complex endeavor, because it’s again, it touches not just the creativity.

The problem with innovation is not ideas. Everybody’s focusing on ideas, but that’s a piece of the problem. You can get ideas from everywhere. The problem is how do I get my idea to a business application through, you know, my organization: through prototyping; through testing; through experimentation; and then being able to scale? So today, I think quite a few corporations have got the idea of, or have got the concept of, “I get the point where I can see, and conceptualize a solution that provides a hard proof of concept.” A load of companies are doing that. But I still see clients that have got the proof of concept running for 2, 3 years because they can’t scale it. There is no process within the organization to scale it, no capabilities to do so.

So, I really believe that the two frontiers that we are looking at right now. One is the notion of how is the shape of the organization going to change once our organizations are very transparent, very data-driven, and so on and so forth; and therefore, what is it that we need and don’t need in this new world to actually operate this organization? And secondly, how do we actually use our scale to really completely reinvent the way that corporations actually do innovation? Let’s talk about, you know, talking to three startups, and open innovation. Digital innovation is not about talking to a startup or taking your board to Silicon Valley to meet with Google and Apple. That helps, on the cultural side, but you really need to fundamentally change some of the processes, systems and culture within the organization to really drive these changes. In particular being able to scale, because the scaling is where the business case lies, not in the prototype. Sorry.

Michael Krigsman: [Laughter]

Didier Bonnet: Those are two topics, by the way, that we are starting to research for the MIT right now.

Michael Krigsman: Wow. Well you have given us an incredible amount of advice, and this time has gone by so quickly, so I would like to thank Didier Bonnet, who is the Senior Vice President and Global Practice Leader for Capgemini Consulting, for taking the time and speaking with us today. Didier, thank you!

Didier Bonnet: Thank you!

Michael Krigsman: You have been watching Episode #205 of CXOTalk. Next week, there is no show, because of Thanksgiving here in the US, but we’ll be back the following week, and I hope you’ll join us. Thank so much, everybody, and have a great day.

Digital Transformation at Brooks Brothers

  • Episode: 200
  • |
  • Topic: Digital Business
Sahal Laher, CIO, Brooks Brothers
Sahal Laher
Chief Information Officer
Brooks Brothers
Michael Krigsman, Founder, CXOTalk
Michael Krigsman
Industry Analyst
CXOTALK

Brooks Brothers is one of America's iconic clothing and retail brands, founded in 1818. On this episode, we learn about the changing retail environment, shifts in consumer expectations, and how this brand is managing digital transformation. Our guest is Sahal Laher, Executive Vice President and Chief Information Officer of Brooks Brothers.

Sahal is responsible for ensuring that Brooks Brothers information technology investments, resources and project execution are aligned with its strategic business objectives. Brooks Brothers is the oldest men's clothier chain in the United States founded in 1818 as a family business. Prior to joining Brooks Brothers, Sahal was CIO for Stride Rite Corporation. His experience is deeply rooted in enterprise technology transformation dating back to an ERP consulting background at Deloitte and Accenture.

Transcript

Michael Krigsman: Welcome to Episode number 200 of CXOTalk. I’m Michael Krigsman. CXOTalk brings the most innovative, interesting business executives in the world for in-depth conversation, where we talk about innovation, we talk about disruption, and we talk about leadership. And, on Episode #200, I’m so thrilled, because today, we’re talking with Sahal Laher, who is the Executive Vice President and Chief Information Officer of one of the most iconic and longstanding brands in American retailing and American fashion, which is Brooks Brothers. Sahal Laher, how are you, and thanks for taking the time and joining us!

Sahal Laher: Good afternoon, Mike. Good! Thank you! Doing very well.

Michael Krigsman: Sahal, Brooks Brothers was founded in 1818, and we all know the name of brand, but please, give us a little background and history of Brooks Brothers, and then during our conversation, we’ll take it up to the present.

Sahal Laher: Absolutely, absolutely. So, really excited to be on the show, and, share a little bit about our journey. So, we are a 198 year old brand, and have outfitted, you know, 39 of the US presidents. And, as we continue to evolve, we are really moving more towards a lifestyle brand, which appeals to not just people looking for the traditional, formal attire, but also, you know, a recent partnership with Zach Posen, who was signed as designer for our women’s collection, and, you know, really, a lot of the things that we’ve done with our red fleeced brand, which appeals to, somehow, a younger demographic. So, I think our company and our owners have done a really good job of keeping the brand evolving and trying to remain relevant, and remain a true lifestyle brand, as we are in this era of just mass change, competition, and, you know… The change is on many levels, it’s not just the consumers themselves and their expectations changing, but the entire market and the way people shop has changed, and therefore, you know, a lot of the way that we go to market is changing, and obviously digital and technology are very big enablers in that journey.

Michael Krigsman: That’s amazing to think that you have been around for almost 200 years, and you’ve outfitted 39 presidents. And I think it’s pretty obvious that a company that’s been in business for so many years has had to have gone through many different types of changes and reinventions, and evolutions. And so, you were talking about change in the market, change in customers: what are the… Maybe can you elaborate on the market forces, the competitive landscape, the nature of changing customer expectations. And so, what is driving the evolution of Brooks Brothers today?

Sahal Laher: Absolutely, absolutely. So, our business has always been kind of founded on personal relationships, and really the white glove service that works with our customers to really uniquely understand you as an individual and your preferences, and based on that, really curate a look for you, that is, you know, 100% you. It’s not a one size fits all, it’s not what one or five different looks on the shelf, but it’s really, you know, very unique and it really is something that we take great pride in, in working with everyone and their unique preferences. I think the changes that we’re seeing, obviously, are, you know, people shop in different way than they used to. They obviously are a lot more, the customer in general, not just in fashion but really in every industry with the web, is a lot more informed. And, generally, what you find is that people come in now with a much better understanding of what it is that they want, they have a much better understanding of the competitive landscape of where you are in the industry and some of the things that differentiate you. They also are a lot more aware of the brands and brand loyalty, and that, you know, to some extent, brand loyalty is not really what it used to be, so, our Chairman and CEO, Claudia DeVecchio

Michael Krigsman: Welcome to Episode number 200 of CXOTalk. I’m Michael Krigsman. CXOTalk brings the most innovative, interesting business executives in the world for in-depth conversation, where we talk about innovation, we talk about disruption, and we talk about leadership. And, on Episode #200, I’m so thrilled, because today, we’re talking with Sahal Laher, who is the Executive Vice President and Chief Information Officer of one of the most iconic and longstanding brands in American retailing and American fashion, which is Brooks Brothers. Sahal Laher, how are you, and thanks for taking the time and joining us!

Sahal Laher: Good afternoon, Mike. Good! Thank you! Doing very well.

Michael Krigsman: Sahal, Brooks Brothers was founded in 1818, and we all know the name of brand, but please, give us a little background and history of Brooks Brothers, and then during our conversation, we’ll take it up to the present.

Sahal Laher: Absolutely, absolutely. So, really excited to be on the show, and, share a little bit about our journey. So, we are a 198 year old brand, and have outfitted, you know, 39 of the US presidents. And, as we continue to evolve, we are really moving more towards a lifestyle brand, which appeals to not just people looking for the traditional, formal attire, but also, you know, a recent partnership with Zach Posen, who was signed as designer for our women’s collection, and, you know, really, a lot of the things that we’ve done with our red fleeced brand, which appeals to, somehow, a younger demographic. So, I think our company and our owners have done a really good job of keeping the brand evolving and trying to remain relevant, and remain a true lifestyle brand, as we are in this era of just mass change, competition, and, you know… The change is on many levels, it’s not just the consumers themselves and their expectations changing, but the entire market and the way people shop has changed, and therefore, you know, a lot of the way that we go to market is changing, and obviously digital and technology are very big enablers in that journey.

Michael Krigsman: That’s amazing to think that you have been around for almost 200 years, and you’ve outfitted 39 presidents. And I think it’s pretty obvious that a company that’s been in business for so many years has had to have gone through many different types of changes and reinventions, and evolutions. And so, you were talking about change in the market, change in customers: what are the… Maybe can you elaborate on the market forces, the competitive landscape, the nature of changing customer expectations. And so, what is driving the evolution of Brooks Brothers today?

Sahal Laher: Absolutely, absolutely. So, our business has always been kind of founded on personal relationships, and really the white glove service that works with our customers to really uniquely understand you as an individual and your preferences, and based on that, really curate a look for you, that is, you know, 100% you. It’s not a one size fits all, it’s not what one or five different looks on the shelf, but it’s really, you know, very unique and it really is something that we take great pride in, in working with everyone and their unique preferences. I think the changes that we’re seeing, obviously, are, you know, people shop in different way than they used to. They obviously are a lot more, the customer in general, not just in fashion but really in every industry with the web, is a lot more informed. And, generally, what you find is that people come in now with a much better understanding of what it is that they want, they have a much better understanding of the competitive landscape of where you are in the industry and some of the things that differentiate you. They also are a lot more aware of the brands and brand loyalty, and that, you know, to some extent, brand loyalty is not really what it used to be, so, our Chairman and CEO, Claudia DeVecchio, is always, “We’re not as good because we’re old, we’re old because we’re good.” I think that’s, you know, a very articulate way of putting it, because, you know, we really do continue to look at what is it that our customers want? What is it the market wants? Obviously, online shopping, and mobile shopping, and digital in general has really disrupted the market, and now you have a number of pure play online retailers that are in the space as well.

But, you know, I think that for the space that we’re in, there’s always going to be a home for the brick and mortar stores, because of the level of service that we provide, and, you know, the white glove nature of how we work with our consumers. The reality is that even if your were to buy, you know, things online, other than probably ties and shirts and, you know, maybe pants, a lot of the other things are going to require some kind of tailoring or alterations anyway. If you’re looking for something that is again, unique, and really is a look that is not, you know, something that, you know… Everyone has different things that they look for, but also, you know, one of my arms is half an inch shorter than the other, and you can take an of the rack item and not alter it, but it’s really, if you want to go that extra ten percent and really have a great look instead of a good look, then there’s an element of tailoring that needs to take place. So, those elements I think, continue to be extremely important, and will continue to be important. And, you know, the store again for us is a very important part of our brand. We have over 600 stores globally, and there are no plans to drastically change that number, neither up nor down. We feel like we have a good mix of, you know, direct-to-consumer online versus the traditional retail stores and also the Brooks Brothers factory stores. So, overall, I think it’s the key message for all retailers, but really also specifically to fashion, is that, I think it’s unrealistic to punt on one of your channels just because the market is shifting.

Michael Krigsman: So, it sounds like customer service and that, the white glove service as you described it, has been a centerpiece of Brook Brothers’ approach for 200 years. And now, what you’re doing, I don’t want to put words in your mouth, but it sounds like what you’re doing is translating that into a multi-channel, or multiple or omnichannel approach.

Sahal Laher: That’s exactly right. I think that manifests itself in many different ways. So first and foremost, it requires that we have a consistent customer experience across channels, and that doesn’t apply just to personalization, but it really applies in general, where every company now needs to break down the silos between channels, because I think, traditionally, retailers have thought in channels, and they’ve been organized in channels, and had separate business units for online versus brick and mortar, versus factory, and what is very evident is that the customer doesn’t see it that way. The customer doesn’t think in channels. They think of it as Brooks Brothers. And so, it’s critical that, you know, we have the same products available on all of our channels, we have the same level of personalization available on all channels, and … Most importantly, I think people are really looking at retailers and companies: they’re not easy to do business with. It has to be simple, it has to be intuitive. You know, you can’t have a very complex aggregation on your website, you can’t have extremely long and tedious checkout process, because we’ve all been to those websites, and lost motivation to complete the checkout.

And, I think Amazon really has set the tone, not just in terms of usability, but also in terms of fulfillment. And so, that is the new norm in terms of customer expectations. You know, there was a period in time where you could ask for a ten or twenty dollar shipping charge and people didn’t mind that, there was a time where you could say you’ll get your product in seven to ten days, and people didn’t mind that. But I think that’s really changed, and that’s gone away now. And everyone expects the ease of use and, you know, in some cases, you know, you do want the instant gratification and … As an Amazon Prime member, you know, quite frequently just opting for the next day shipping option. And, you know, obviously Amazon is working on same-day shipping and … But, the reality is that next-day shipping is mobilizing to become the norm, and for all of these online brands, whether you’re a 198 year old brand, or an 8 month old brand, if you aren’t … You know, if it’s not simple and you’re not easy to do business with, and you don’t have a supply chain that can fulfill in a fashion that is geared to give the people the product they want, when they want it, then you’re really going to be at a big disadvantage, and you really are going to go to another site where it’s easier to do business.

Michael Krigsman: We have an interesting question from Alan Bergson on Twitter, who’s wondering, “In a business where there is so much service and customization, how do you maintain that customer experience, especially going across multiple channels?” And then, he’s asking about the role of culture in this as well.

Sahal Laher: So those are both great questions. So let’s talk first about, you know, just how we do that, and how that level of, you know, personalization and white glove service is replicated across channels in a seamless way. So, just to give a little bit of background, right? I think there was a period of time where everyone used to go to their store on Main Street in their town, and they had relationships with the Brooks Brothers associate and they’d probably been going there for many years. And, you know, all your preferences were written down in a black book, and that sales associate that you worked with really knew what you want for a look, they knew everything that you had purchased in the past, and all of that was kind of maintained in that black book, and that’s a great model obviously, because you get a very high level of service, and you have someone that has a personal relationship with you. The reality of the world we live in now is that it’s just not like it used to be in that, now we travel more. We may want to go to the store, not in our hometown, but where we work, or we might be on business at a conference and we might want to go to a store.

And so, what we’ve really been working really hard on in the last couple years is trying to figure out: If John Smith comes to the store, and he’s never been into that store before, but he’s been a customer for ten years, we are missing the mark if we don’t give him personalized service based on the information we already know about him. And so, a store associate at that store in Las Vegas where you are for a conference, in a very short period of time, needs to equipped with tools that can really tell them who is John Smith, and what are his preferences? What are his likes, and what is in his virtual wardrobe in terms of his purchase history? And really based on that; we can mend, you know, equip that associate you have just met you two minutes ago, to still provide a high level of service, because they will have… We will have turned data that we have into actual, actionable insights that you, the store associate, can use to really have a more personalized conversation, as opposed to talking to everyone who walks into the store that you don’t know about the same five products in the Fall collection.

So that’s a very important piece of who we are, and, obviously replicating that requires a lot of translation of this data into insights. And, everyone talks about “big data,” everyone talks about these buzzwords of “big data” and “machine learning” and so on, but this is really a case study where it’s the differentiator, and really in all industries, I think, can be a differentiator not just for personalization but for many different parts of your supply chain and the way that you go to market. If you use the data that you have, and implement machine learning type of platforms, which, in their simplest form, for those not familiar with machine learning it’s: computers now have the ability with these platforms to learn from data and to spot trends in data without being explicitly programmed. And that’s a very powerful trend in the market right now, and really, without that, in the past, you would have to find a specific use case that you are after, and comb through all of your data, aggregate it, and come up with these findings.

And, the way that the machine learning works, is that we can do that on the fly, and we can do that for terabytes and terabytes of data, which, in the old days obviously it’s just not possible, right? Even if we took every single black book, every single store associate’s black book from the old days, where they had customer service and all of that done in paper books, that’s already a lot of data. And now, you multiply it by, you know, everything like your online clickstream, right? So every time you go online and you’re navigating the website there’s a trail of breadcrumbs that every customer leaves behind in terms of what have they browsed, what have the put in a cart and not bought, how much time have they spent looking at a particular item. And so, all of this information, when you aggregate it together, and you have a true big data strategy, that utilizes some of these next generation tools like machine learning and in-memory databases. And, we have the ability to really replicate that service, and now, you can also make that all available online, and you can make more thoughtful recommendations for you online, as opposed to the showing everyone the same five products that have just come out as things that the might be interested in.

You know, the research shows that Amazon has done a very good job with this, Netflix has done a very good job with this, and, there’s an extremely high number of, I think, the number in the McKinsey study was over 65% where things that you buy on Amazon, or shows that you watch on Netflix, are based directly on the recommendation that was given to you by the site. So that’s a fascinating number and has huge potential, you know, when you move past personalization and just, in terms of the challenging market that retail is now, you know, that’s an extremely critical piece, because if you have, again, a personalized way to upsell and cross-sell products, that is obviously going to be a win-win, because it’s going to be things that the customer really sees as being things to augment the existing wardrobe, and obviously from the retailer’s standpoint it’s going to result in additional revenue.

Michael Krigsman: That’s pretty incredible! So, you have adopted machine learning in order to improve the recommendations that you provide online, and I’m assuming that your sales associates can provide based on purchase history, frequency of interaction, I’m assuming in the stores… Can you tell us just briefly about the tools: did you develop the tools in-house, did you buy them? Talk about the technology.

Sahal Laher: So this is an initiative that is ongoing, because as you know, this is a very big undertaking, right? It’s not something that you can spend a short period of time, or your traditional project cycle of 9-12 months and say “We’re done,” right? This is really, truly a dynamic thing that has to become part of your DNA as a retailer and as a company. So, you know, if we just take a step back and provide a little bit of context: When Pandora started, they took a subset of their collection of songs and they took, let’s say, 9 or 10 thousands songs, and they paid professional musicians to come in and listen to all of these songs. and then they had developed this Excel spreadsheet with multiple attributes. So, it had literally dozens of attributes, over a hundred total attributes for every single song based on you know, I’m not a musician and not even qualified to speak to them, but obviously way deeper than what is the gene of the song, who is the artist, etc., but it really got into what is the tempo? What are the instruments in the song? So anyway, they had all of these attributes, and that was really, that project was called the “Music Genome Project,” where they took their products and … Obviously you always have attributes for any product in any industry, right? So in the case of music, they knew who the artist was, they knew the length of the track, but they really didn’t have a lot of meaningful attributes that the consumer could relate to. And that was really what was needed for personalization.

So, after they went through this initial process, and the musicians had kind of populated this entire database of attributes across nine or ten thousand songs, then they ran it through this tool and said, “Okay, let’s see how it works! Tell me a song you like, and let’s see what the engine recommends to you.” And, they found that it was nine or ten thousand songs, sounds like a lot, but it’s really not a lot, it’s a really small sample size obviously, but they were really encouraged by the early results and that’s where they said, “Okay, we have to do this for every single song.” And, that was really the birth of Pandora and the way that it … You know, the premise of all of these platforms is that the more you use it and the more it gets to know you, the more accurate are the recommendations.

So, similarly, what we’re in the process of doing is, we’ve had hundreds of attributes for all of our products in our PLM system, our product life cycle management system, and that’s a tool that we implemented about three and a half years ago. It’s from Vendor PTC, which is a Boston-based company, and very well-known in the apparel space, or apparel and fashion. And, you know, what we looked at is that, you know, yes we had these attributes, and we had these attributes when that system went live, and probably even prior to that.

But, how many of those attributes are truly customer-facing attributes, or ones that would be meaningful to make a recommendation? And, the reality was that there weren’t many, right? There was color, there was obviously the name of the product, and there was a handful of other things. But, there wasn’t… You know, if we want to get to the next level of sophistication, either online or in-store, but, you know, it has to be as sophisticated as being able to ask, “I need a suit for a Cape Cod wedding,” and getting a recommendation. You know, most search engines, most sites, you enter that, you would get a few sites, you would get a few hits for “Cape Cod,” you would get a few hits for “wedding,” you would get a few hits for “suit.” And, they wouldn’t necessarily all be, you know, interrelated to the point where you would have a recommendation or recommendations for a suit you could wear at a Cape Cod wedding. So that’s just one fairly rudimentary example, but the bottom line is that there’s a lot of work to do, similar to what Pandora went through.

There’s work for us to do to really populate those attributes for our, you know, entire collection eventually. But, obviously, you have to start with a subset of the collection. We have a large assortment of over fifty thousand SKUs, so this is not going to be something we can do overnight, but the basics, and you populate those attributes, then you have a very good foundation to come up with these recommendations.

Michael Krigsman: Now, can you talk about the relationship between service, engagement, customer experience, this machine learning project, because it’s all part of a broader perspective.

Sahal Laher: Absolutely. So, you know, I think, again, customers don’t think in channels, right? And so, regardless of what channel they are interacting with you on, they expect that you know… So if I went onto the website and I made a purchase, and I come into the store two weeks later, and you don’t have any information on my order, or don’t even have any information on what’s in my wardrobe, then you’re missing the mark. So, you know, ultimately, everyone … There’s another big buzzword of “360 [degree] view of the customer,” which really applies both ways, and what I mean by that is that it’s equally important for a company to have that, but the customers expect you to have that as well, because, again, if I come into a store today, and I placed an order last night, and you can tell me, you know, my order status, or if I come into the store and I see something else, you can help me change that order based on something else that I found in the store. That then is a customer service process and a customer experience.

So, you know, one of the first things we did a couple years ago was really work on creating this 360 degree view of the customer, which sounds fairly obvious and it sounds fairly intuitive. But the reality is very few people have that all-in-one place, because over time, it doesn’t matter how long you’ve been in business, and obviously, the longer you’ve been in business, you might have more silos of data. But even if you haven’t been in business for decades, and you’ve only been in business for a few years, nobody has just one sales system, right? You always have at a very minimum have a point of sale system and you have a website. And you may need some kind of system for customer service, you need some kind of system for your store associate, be it clienteling or looking at alterations, or made to measure, or whatever the case may be.

So, what we try to do is all of those systems that I named was one or more different databases when we started, and what we’ve worked to do is really bring all of this into a single database. And that single database now has John Smith’s customer record, it has all his personal preferences, it has his e-commerce transactions, it has his in-store purchases, it has his alterations and measure information, and it also has any interaction that he’s had with our call center is all logged in one central place. So what that allows us to do is obviously elevate the level of service that we can provide, because regardless, again, of what channel is your preference to interact with us on any given day, we will be able to have a consistent view of who you are as a customer, and therefore we’ll be able to better service whatever needs you have on a particular day, and they won’t be these handoffs or, “Let me transfer you to the place you ordered that, let me transfer you to call center or the e-commerce fulfillment team to look at where your order is in the fulfillment process.” It really needs to be, again, simple, right? If it’s not simple and intuitive, people are going to get frustrated and go elsewhere.

So that is really, I think, in a nutshell, the driving forces behind why that 360 degree view of the customer is important. And, you know, again it’s really now something that is a big enabler for us because our call center has tools that they never had before, and it allows them to really provide a level of service to the customer that, from where we started, when they had to alt-tab to multiple screens and transfer people to different associates and to different stores.

Michael Krigsman: So the right type of technology combined with keeping it simple and intuitive makes life easier for the customer and and also makes life easier for people inside the stores, or inside the call centers to respond quickly and in a more appropriate, detailed, customized manner.

Sahal Laher: Absolutely, absolutely.

Michael Krigsman: We have another question from Twitter, and this is from Arsalan Khan, who’s wondering, as the technologies change, and as the environment around you, the customer environment, the competitive environment is changing, how do you plan? How do you go forward and consider this ongoing change in your business strategy?

Sahal Laher: That’s a great question, and I’m glad that it was asked, because one of the things we haven’t really touched on so far is the need for a strong, what I call “digital core,” right? So, in the ‘90’s there were ERP projects and, you know, people moved on to CRM projects and, you name it, there has been multiple waves of kind of software solutions that have been the hot trend that customers and companies have gone after. The reality of it is that, you know, very few people still to this day have that strong digital core, and what I mean by that is that: You know, whenever people think about digital and whenever they think about innovation, they automatically jump to, “How do we come up with the sexy new technology that’s customer facing, and what can we implement, in terms of beacons, or RFID, or IoT that is cool and sophisticated and elevates our customer experience?”

And all of those are great questions to ask, and again, things that everyone has to continue to do because, I think the biggest lesson learned for, you know, for retailers in the last few years is, you know, if you don’t innovate and advance yourself as a company, then you can become irrelevant, right? I mean we’ve seen numerous stores where, you name it, Blockbuster Video, where they thought they had such a good customer base and such a good value proposition that they were invincible and didn’t need to change, and didn’t really buy into the streaming online praise that hit, and that was unfortunately their downfall.

So, you know, I think the digital core, so coming back to that: What that really entails is, do you have a strong supply chain that can allow you to fulfill orders any time, any way? That’s really the bottom line, right? The customers want their stuff. They don’t care where it’s being shipped from, they don’t care how it’s being shipped, as long as you can honor your commitment to get that particular merchandise to the customer on a date that’s promised, then you’re meeting the customer expectations.

So, that’s obviously very difficult, and when we talk about omnichannel, right? And we talked about 360 degree view of the customer. But another extremely important piece that we touched on very briefly was the silos across channels coming down. And as those silos come down, you know, this digital core becomes more and more important, because in the old days it was a fine for you to have a website, and a website only having inventory to your e-commerce warehouse merchandise. But now, you really need to make sure that you have, you know, it’s almost another 360 degree view, it’s also a 360 degree view of product and inventory. And looking at that across all of your channels, and the ability to, you know, come into a store, we don’t have the right size, style, and color of your shirt, which, you know, even in our larger stores is very challenging because again I mention, we have a large assortment, fifty thousand SKUs, so it’s going to be physically impossible to keep in stock every single size, style, color, variation for everyone.

So, you know, there’s obviously tools that allow you to allocate product, and to come up with these assortments, but there’s always going to be times when someone comes in and we don’t have that product, and how do we get you that product? We have fifty of those units in the warehouse that are available for e-comm orders, but it’s a shame if that inventory’s not available to in the store, or vice-versa. So, that digital core and this is kind of, a little long-winded response to the question, but it’s an important context that I think needs to be provided, as if you don’t have that supply chain that’s dynamic and nimble, and you as a company are unable to really react truly dynamically and real-time to customer demand, then you’ve missed the mark.

So, there’s a back-end piece here that’s not sexy. No one, the customer again doesn’t care what you run for a supply chain package, they don’t care what your digital core is. What they do care [about] is if you have a good one, and if you don’t have a good one, then you’re not going to be able to meet those customer requirements.

So I think the key message here is you need the strong digital core, and then you need to augment it with sophisticated and specialized technologies that are sexy and customer-facing, such as beacons and RFID and IoT devices that really enhance the customer engagement process. And, you know, really, those are all possible only on top of that base.

Michael Krigsman: That’s really interesting. So, this view, then, of both the customers and your supply chain means that as you are developing that digital core, it transforms both your front end processes that the customer-facing processes, as well as deep into the back-end processes.

Sahar Laher: Absolutely, absolutely. And that’s a great point. We’ve invested a lot, and I think the other thing I’ll point here is that not all of these are technology projects, right? Before we’ve done an ounce of technology work, we’ve done a significant process re-engineering work to come up with things like global view of inventory in a global trading company where we can really, you know, leverage our inventory and flex it across markets in a way that allows us to maximize the needs of the customer and meet those demands. And just one example that I’ll give there is that, you know, we’re a global company, but obviously a huge part of our business is North America. So, as a result, we have two kinds of product. We have the basics product that’s available year-round, and that would be your white shirts, blue shirts, gabardine pants, ties, etc. And then we have the seasonal product, and there’s four seasons of that product that’s released, obviously based on it. And it follows the season in North America, so it’s northern hemisphere seasons. Now what that means, obviously, is that when our Australian market comes to look at the Fall collection, it’s not going to be Fall in Australia for six more months, but they still need to make an educated guess in terms of how a certain product is going to do in their market, and place a buy, or place an order of that merchandise, so that they can have it.

In the old days, what would happen is that every market can put those requests in, and they got those requests, but a lot can change in six months. We may find that Australia under-ordered, but Singapore over-ordered. And in the old days, there was no way for us to dynamically reallocate that inventory so that we could still maximize the inventory on hand, and still keep the sale, and not lose those sales. So, now we truly have that ability where we have a global view of inventory, we have a team called GIM, Global Inventory Management Team, and they are really the gatekeepers of inventory and they have the ability to do this, and to flex product across markets. And, you know, when the Fall Collection is done for North America, then we have the ability to hold that merchandise, and fulfill demand in Australia 4-5 months from now, if that is where we need it.

So, that piece of it I think is extremely important, and I think it goes back to the original point that you made. And you know, I think the other point that this is highlighting is that this is not all about the technology, right? I mean the technology is obviously a very critical enabler, but again, we’ve done many, many projects that are purely business process-focused and organizational-focused before we’ve launched some of these technology projects, because the worse thing that we could do is just take a hundred year old process and put in a new technology tool, which is really not elevating our brand at all.

Michael Krigsman: So, at first I want to remind everybody that we’re talking with Sahal Laher, who is the Executive Vice President and CIO of Brooks Brothers, and what he’s talking about, breaking down silos and changing all of these things, remember, keep in mind Brooks Brothers was founded almost 200 years ago, and so it’s just amazing to me to hear about a 200 year old company and the way that you are adapting, and remaining nimble. But we have a very interesting comment from Kirk Born, who is the Principal Data Scientist at Booz Allen on Twitter. And Kirk Born makes this comment, he says, quote: “Cross-channel is a type of customer analytics, not a type of customer.”

Sahal Laher: That’s a great point. And I think, you know, again it comes back to, you know just the role that analytics plays in today’s world, and again, it’s really to me it’s cross-industry, right? It’s not just something for retail or fashion companies. And so, I think, you know, that’s spot-on where it’s really mining that information and, you know, let’s not limit ourselves to internal information only, right? It shouldn’t just be about the systems that we have internally, or the order management system, or the e-comm system. You know, nowadays, there’s a ton of information that’s available, that is on external data sources. You have social media, we have, you know, for a nickel you can buy two hundred attributes of data on almost anyone in the US in terms of their buying patterns and purchase behaviors and so on, and that’s already finding widespread use in other industries as well. And insurance companies are using that to do things like lifestyle-based analytics and underwriting.

And so, I think that remark is spot-on, because, you know, you really have to change your mindset as a company to see data as a very critical cross-channel, enabler and differentiator. And instead of just traditionally people have just kind of hoarded data, and like I said earlier, it’s … I’m not being critical, I mean everyone did it; we did as well because no-one is staffed to have hundreds of people in the analytics department that can go do this. And so, it’s only now that these tools are becoming available and we have the ability to be able to run hypothetical scenarios on terabytes and terabytes of data within minutes, based on advances in things like in-memory databases and so-on. And, that in the old days was just not possible. So I think that it’s a very interesting time that we live in right now, and we have great tools available to us. A year from now, if we have this conversation, there will be additional tools that we can’t even envision to today that will have come out to even elevate this further.

But, I think that really is highlighting the need for companies to continue to innovate, and any of these initiatives around customer service, or customer experience, or omnichannel commerce and digital commerce, they can not be a one-and-done initiative where you say, “Okay, our mobile app is done.” The world is never going to be like that anymore. You’re going to need to continue to have your continuous improvement mindset and organization, you’re going to need to innovate, and be testing new technologies in-house and in innovation lab or something like that and seeing which ones work for you, and then adapting those to your brand and then rolling those out across your markets.

Michael Krigsman: Sahal Laher, CIO of Brooks Brothers, we have literally about one minute left, and maybe can you just, can you share with us, or give your advice to other companies who are undertaking various types of programs of change, which clearly Brooks Brothers is in a constant state of reinvention and innovation. So what’s you advice? How to get that done, and make it happen inside an established organization?

Sahal Laher: Absolutely, so I think one of the guiding principles that we as a company have adopted is the crawl-walk-run approach, which is very important because some of these initiatives otherwise can be overwhelming, right? When you try and look at the big picture of everything that needs to be done, and you try and take it all on together and boil it in the ocean, that is not a good strategy for success. And, you’re going to end up with a lot of projects that are kind of disjoined, and you will ultimately not be able to meet the promise to your customers. So, I would really encourage everyone to take that approach, and to really prioritize. And, you know, look at very objectively where you are as a brand in relation to the market, in relation to the competition, and figure out which of the capabilities you’re lagging on that you want to invest more in, which are the ones that you are on parity with the rest of the market that you may want to leapfrog, and which are the ones that you lead on that you want to continue to be a leader in? And ultimately, that roadmap is really going to drive your success.

And, I think the other piece that I would mention again is, we’ve touched on a couple times during this call, but be very careful of getting into the trap of making it all about the technology. So again, the technology, it can be a very strategic enabler, it can absolutely drive some of these initiatives from an execution standpoint, but don’t shortchange the process component, the process re-engineering component, and the change management component of what that’s going to mean to your associates, and to you customer.

Michael Krigsman: Wow. You have given us a real education and a fascinating look inside one of the most well-known, iconic brands in the United States. Thank you so much!

Sahal Laher: Thank you!

Michael Krigsman: We have been talking on Episode #200 of CXOTalk with Sahal Laher, who is the Executive Vice President and Chief Information Officer of Brooks Brothers. What an amazing conversation, I can’t wait to go back and listen to it again, and just hear this wealth of knowledge about how a large and very old company has remained relevant and remained current in a changing and highly competitive environment. I’d like to thank everybody for watching CXOTalk, and I really want to give a shoutout to Livestream, who provides our video infrastructure and distribution, because Livestream, it just works, which is the best possible thing I can say. Thanks, everybody! Have a great weekend, and we have two shows this week, so go to cxotalk.com/episodes and please join us again, Bye-bye!

Digital Transformation and the CIO

  • Episode: 198
  • |
  • Topic: Leadership
Martha Heller, Founder and President, Heller Search
Martha Heller
Founder and President
Heller Search
Michael Krigsman, Founder, CXOTalk
Michael Krigsman
Industry Analyst
CXOTALK

Business expectations of the Chief Information Officer role have changed dramatically, forcing CIOs to adapt and evolve. This episode explores what's happening with CIOs and offers practical advice to both the business side and to CIOs themselves.

Our guest is author Martha Heller, who is president of Heller Search Associates. Before she established her career in executive search, Martha was Founder and Managing Director of IDG's CIO Executive Council, a professional organization for CIOs.

During her seven-year tenure at CIO magazine (IDG), Martha developed leadership programs for CIOs and directed the CIO Best Practice Exchange, a members-only network of IT leaders from top-tier organizations. Martha wrote a weekly column on IT leadership and led a series of executive events on IT staffing, career development, and leadership. Before CIO, Martha was an editor at Rutgers University Press.

Martha continues to engage with CIO audiences every day. She is author of The CIO Paradox: Battling the Contradictions of IT Leadership, and Be the Business: CIOs in the New Era of IT. Martha writes CIO.com’s Movers & Shakers blog, and her e-newsletter, The Heller Report: You and Your CIO Career, is read by thousands of IT professionals every week.

Transcript

Michael Krigsman: Episode number 198 of CXOTalk. I’m Michael Krigsman, and CXOTalk brings the most innovative leaders in the world to talk about the impact of digital disruption on our world, on our society, and on our companies and organizations. Today, I am so thrilled, because we’re speaking with Martha Heller. Martha is a multiple book-author, and she is the founder of Heller Search Associates. Martha is a very prolific speaker at Chief Information Officer events, and without a doubt, one of the leading and most important thought leaders among CIOs, and supporting that CIO community anywhere in the world. so, I’m so thrilled to welcome Martha, and I want to say a huge thank you to Livestream, which provides our video infrastructure. And Livestream folks, if you are listening, we love you, you guys are great. Thank you. So, Martha Heller, how are you?

Martha Heller: I’m doing great! You’re making me feel like a rock star, Michael. I appreciate it!

Michael Krigsman: Well, I think in the world of CIOs, you are the rock star, and that’s no lie!

Martha Heller: My point exactly!

Michael Krigsman: So, Martha, tell us about the things that you do, give us some sense of context and place, and I see sitting next to you is your latest book, so tell us!

Martha Heller: Absolutely! So, thanks so much for the question, Michael. You know, I joined CIO Magazine back in the late 90s, when I started an online column for CIO magazine called “Soundoff”, and aging with the CIO community ever since then. So, I believe I have communicated some kind of message to the CIO community on a weekly basis for the last 17 years. So, if you do the math on that, that’s quite a bit of content, quite a bit of volume. In 2005, I decided to parlay that experience in those networks into the wonderful world of executive search, so my firm recruits CIOs and the folks who work for them, and boy once you’re trying to convince a CEO to hire a CIO, your knowledge of the challenges and contradictions of the CIO world becomes quite acute. So, at this point, I run a search firm, and I write all kinds of content for the CIO community, and I’ve just been endlessly fascinated by the evolving nature of that role.

Michael Krigsman: You know, I aso find it interesting that historically, and this is changing, historically the CIO role has been a male-dominated profession. You’re one of the top influencers in that community, and yet you’re a woman. So I find that’s also quite interesting as well.

Martha Heller: Well, you know, I’ll just address the gender diversity among CIOs. It’s true that the percentage of women who are CIOs is very, very small, and you know, what’s changing is that IT is not the only destination for women who are interested in technology. Marketing, for instance, is hiring technologists. Every company is becoming a technology company, so women interested in technology need not have IT on their career plan, there are many other opportunities for technology-oriented women. In terms of my role, being a woman in this sea of men, my background is journalism, and journalism, which has been more oriented towards gender diversity, let’s say, than IT. So even though I have chosen the wonderful CIO as my journalistic subject for the last 17 years, my background really ultimately is journalism, where you do have more gender diversity.

Michael Krigsman: In fact, we are doing a show next week with Andi Karaboutis, who used to be the CIO of Dell, and is now an executive vice president at Biogen, along with Kim Stevenson, who was the CIO of Intel, and is now Chief Operating Officer of one of their divisions, and we’re going to be talking next week about exactly these issues.

Martha Heller: What is interesting about that is both those instances, very strong female CIOs who are now leading organizations that have CIOs in them, while they have moved on to more broad business responsibilities. I’ll bring up another

Michael Krigsman: Episode number 198 of CXOTalk. I’m Michael Krigsman, and CXOTalk brings the most innovative leaders in the world to talk about the impact of digital disruption on our world, on our society, and on our companies and organizations. Today, I am so thrilled, because we’re speaking with Martha Heller. Martha is a multiple book-author, and she is the founder of Heller Search Associates. Martha is a very prolific speaker at Chief Information Officer events, and without a doubt, one of the leading and most important thought leaders among CIOs, and supporting that CIO community anywhere in the world. so, I’m so thrilled to welcome Martha, and I want to say a huge thank you to Livestream, which provides our video infrastructure. And Livestream folks, if you are listening, we love you, you guys are great. Thank you. So, Martha Heller, how are you?

Martha Heller: I’m doing great! You’re making me feel like a rock star, Michael. I appreciate it!

Michael Krigsman: Well, I think in the world of CIOs, you are the rock star, and that’s no lie!

Martha Heller: My point exactly!

Michael Krigsman: So, Martha, tell us about the things that you do, give us some sense of context and place, and I see sitting next to you is your latest book, so tell us!

Martha Heller: Absolutely! So, thanks so much for the question, Michael. You know, I joined CIO Magazine back in the late 90s, when I started an online column for CIO magazine called “Soundoff”, and aging with the CIO community ever since then. So, I believe I have communicated some kind of message to the CIO community on a weekly basis for the last 17 years. So, if you do the math on that, that’s quite a bit of content, quite a bit of volume. In 2005, I decided to parlay that experience in those networks into the wonderful world of executive search, so my firm recruits CIOs and the folks who work for them, and boy once you’re trying to convince a CEO to hire a CIO, your knowledge of the challenges and contradictions of the CIO world becomes quite acute. So, at this point, I run a search firm, and I write all kinds of content for the CIO community, and I’ve just been endlessly fascinated by the evolving nature of that role.

Michael Krigsman: You know, I aso find it interesting that historically, and this is changing, historically the CIO role has been a male-dominated profession. You’re one of the top influencers in that community, and yet you’re a woman. So I find that’s also quite interesting as well.

Martha Heller: Well, you know, I’ll just address the gender diversity among CIOs. It’s true that the percentage of women who are CIOs is very, very small, and you know, what’s changing is that IT is not the only destination for women who are interested in technology. Marketing, for instance, is hiring technologists. Every company is becoming a technology company, so women interested in technology need not have IT on their career plan, there are many other opportunities for technology-oriented women. In terms of my role, being a woman in this sea of men, my background is journalism, and journalism, which has been more oriented towards gender diversity, let’s say, than IT. So even though I have chosen the wonderful CIO as my journalistic subject for the last 17 years, my background really ultimately is journalism, where you do have more gender diversity.

Michael Krigsman: In fact, we are doing a show next week with Andi Karaboutis, who used to be the CIO of Dell, and is now an executive vice president at Biogen, along with Kim Stevenson, who was the CIO of Intel, and is now Chief Operating Officer of one of their divisions, and we’re going to be talking next week about exactly these issues.

Martha Heller: What is interesting about that is both those instances, very strong female CIOs who are now leading organizations that have CIOs in them, while they have moved on to more broad business responsibilities. I’ll bring up another topic in a moment, and that is CIOs on boards, and that is a topic of great interest to the CIO community and corporate boards, “How do I get in on one of those opportunities?” In many instances, CIOs on corporate boards involve women, that, you know, whether it’s corporate boards trying to achieve diversity? I don’t know. But you have many instances of CIOs being appointed to corporate boards.

Michael Krigsman: So, you mentioned, you spoke about tensions, and of course the CIO role is changing, the goal of technology in the organization is changing, and maybe a good place to begin is what is your view of what exactly is changing in the world that’s driving CIOs to need to evolve?

Martha Heller: Sure. So, you know, I’m going to quote Bask Iyer, who is the CIO of VMWare.

Michael Krigsman: He was a guest on our show.

Martha Heller: It’s a small circle! You run in small elite circles. So Bask talks about the “CEO missing out syndrome”. And it’s where a CEO says, “I like my CIO. He, or she, has kept costs down, we’re as secure as I believe we can be, we’ve outsourced the appropriate functions, we’ve got good resilience, employee productivity tools; my CIO has done a great job, in fact, he’s done everything I’ve asked him to do! However, I feel like I’m missing out. There are cool things happening in Silicon Valley. You know Uber? What’s going to be the Uber in my industry, and are we really on top of the technology innovation that’s going to allow us to not be disintermediated? And, I look at my CIO and think, my CIO has never really been an innovator. He’s an operator which is everything I’ve asked for, but I’m going to go hire a Chief Digital Officer.”

So, that move, which many CEOs are making, can be fine, but it can also spell trouble for an organization for a number of reasons. CIOs who would like not to work under yet another technology leader, would be well-advised to step into the so-called “digital technology void”, and drive digital transformation not by themselves, but through partnerships and alliances as they’ve always done everything. But why now, what is happening with the CIO role? It is CEO-driven. And it’s in part, and it’s CEOs saying, “We need digital transformation, but my CIO’s an operator. I’m going to hire this other person. I’m not going to hire a new CIO.” So, digital transformation is driving an evolution of the CIO role toward influence, strategy, getting closer to the revenue stream.

What I will also say is that I’ve talked about the demand-side part of the CIO evolution, it’s CEOs expecting more from technology, more from IT. But I think CIOs themselves are also thinking, “You know, how am I going to spend this incredible digital revolution that we’re in the middle of? Am I going to sit around implementing the ideas of others, or am I going to move and go to another company, or change my role here, that allows me to really be a part of it, and to create a whole different layer, or level, of change?” So, ultimately, what’s changing is every company is becoming a technology company, software is making its way into products and services in ways that we’ve never seen before, that will have an impact on the leader of the technology function.

Michael Krigsman: So when you talk about the digital void, what do you mean by that, and how can a CIO fill those shoes?

Martha Heller: So I think one important concept to understand is that digital is not a function that requires a new executive and new hires and new resources. Digital is a capability that companies need to adopt across all of their businesses and all of their functions. CIOs who understand their roles as critical capabilities champions, “I have a uniquely end-to-end view, and I can see where we’re doing little pockets of digital innovation, where we’re not doing any innovation, which business leaders are spending on digital technologies and which aren’t. I need to create digital as an enterprise capability, and bring all of that to my company. Because if I don’t, we’re going to have little pockets of what I think of as ‘vertical digital innovation.’ We don’t have enterprise scale, we don’t have an enterprise strategy, and we’re entering risk into the organization.” So, you know, the “digital leadership void” is where CEOs are attempting to clamp down on, or get behind this concept of “digital”, so their instinct is to throw a new executive at it and throw a function at it, when really, digital is an enterprise capability that a CIO with an end-to-end view is capable of driving.

I’ll make one more comment on this. Whenever I talk to a CIO and they say something pithy or philosophical or existential, I steal from them and I tweet it out. I tweet out something that they said without attribution because A) we don’t have the character space and I want it to be more real-time than that. And then at the end of my book, I took my favorites from the last year and I listed them. And one of my favorites is when a CIO said to me, “We don’t need a digital strategy. We need a business strategy for a digital world.” And I think that that is a concept that all the leaders in the company need to have, rather than thinking, “What’s digital? We don’t know what it is, it could mean a lot of things, maybe it’s marketing, maybe it’s supply chain, maybe it’s employee productivity. Let’s hire a new executive to figure it out.”

Michael Krigsman: So the idea that the digital strategy is really a business strategy, rather than just a technology strategy, makes perfect sense. But I think the question then comes up: if you are a CIO and you want to be the person that is leading this, what are the obstacles that may interfere with that happening, and how do you overcome those obstacles?

Martha Heller: So, probably the greatest obstacle is the perception that IT is an operator, and that IT is about support and enablement, and not about innovation and strategy. And, what I would say to CIOs in their own companies is that if that perception is so embedded into the fabric of this culture and it is so deeply held, perhaps, this culture is not the right environment, not the right place for you to achieve your digital leadership dreams, and it may be time to pursue another opportunity where you have a chance to change those perceptions. That would be one major obstacle, and probably the most significant.

Another obstacle is the team. If you have a team of people who feel that their role is wait for the order, then take the order and execute on the order, you will not be able to achieve digital leadership, because you may change your relationship to the business but if your senior team hasn’t changed theirs, and you don’t have the right people in those spots, you will also have trouble changing that perception. But I would say, you know, the best way to start moving toward digital leadership is again, to recognize that digital is a competency and your job is to create that competency.

So I’ll give you an example: Dave Smoley is the CIO of AstraZeneca. And Dave said that, “We’ve got pockets of digital activity happening all over the place, but we’re not talking to each other.” So he set up a digital center of excellence. This is a cross-functional group, it does not exist in marketing, it does not exist in IT, and he brought in people from all different parts of the business that he felt had a leadership role in digital transformation. Once he got the center off the ground, he brought in a leader from another area of the business, someone with a lot of experience and respect, and this is critical, had some systems implementation experience. It’s fine and pretty to talk about the front end, but everything’s got to tie up with architectural integrity, and somebody with implementation experience will understand that.

He also made sure that in the center of excellence, he placed somebody in his IT organization. He happened to put his CTO in there. What he said was, “I want to avoid the scenario where there’s the digital conversation, and then there’s the IT conversation. There should be one conversation.” And so Dave incubated it, he got it off the ground, and then once he felt that the digital center of excellence was on firm footing, he moved on within AstraZeneca to climb other mountains.

Another thing that he did and that I’ve seen maybe CIOs of companies do, is that they take their executive committee on a field trip to Silicon Valley, where they meet with a whole host of digital vendors who are doing cool work in their field! That’s the work of a CIO in digital transformation, and those are some first steps, and it’s not easy, but what’s easy really? Those are some first steps CIOs can make to combat the past perception that IT enables and supports but does not drive, and to start getting that digital competency grounded across the enterprise.

Michael Krigsman: Yes. Dave Smoley is certainly a great CIO and innovator. Arsalan Khan on Twitter is asking how do you prioritize things like strategy, politics, education, from the CIO perspective? How do you move forward and fill that digital void, as you call it?

Martha Heller: Well, I would say the first priority is get your house in order. You know, if we think about Maslow’s Hierarchy of Needs, don’t talk to me about self-actualization before I have a roof over my head. Don’t bother having a conversation about strategy is no one’s getting their email. So, I would say, if you’re going to prioritize, the first thing you would prioritize is if you would have your basic fundamentals of IT in shape. The second piece is the team. If you have a team that can partner with a certain area of the business, and have a conversation that that business leader feels is peer-level conversation. You have that in order. The other thing I would look at is, do you have Agile development and DevOps and some other forward-looking development and delivery processes in place, and once you’ve got your house in order, it’s about making sure that you’re part of the conversations where vision and strategy are discussed. And I’ll bring up another concept now in response to our audience question.

This comes to me from Scott McKay who is the CIO of Genworth Financial. And Scott says, “In a boardroom, in an executive boardroom, around me you’ve got chairs around the table and chairs along the wall. The chairs around the table are filled with the ‘what’ executives. They decide what the company is going to spend its money on and what the company is going to do in terms of strategy. And then you’ve got the chairs around the walls, and those are the ‘how’ executives. ‘Oh, that’s the strategy? Thanks for letting me know, and here’s how we’re going to get it done.’ And CIOs have traditionally been in that ‘how’ seat, and it’s a good thing too, because ideas without execution are cheap! So, the ‘how’ executives, the CIOs spend their careers getting stuff done. Now, when IT has an opportunity not only to support business strategy but actually to inform and define it, it’s time for the CIOs to switch chairs and to get up to that ‘what’ table. Now you can’t let go of the enabling because everything has got to get done, but it’s about expanding their horizons.”

So, in terms of prioritizing, I would say get your house in order which includes your killers in your team, but after that it’s to do that gut check and make sure you’re ready to be that “what” executive. It’s a different level of peronal risk to say, “Here’s what we should do” versus how we’re going to do it. And then it’s getting into those meetings and making sure you understand the strategy. And then of course if you don’t understand the business context, don’t worry about the strategy. And then it’s just like everything else: vision becomes a strategy, strategy becomes goals, goals have timelines, and Lord knows CIOs know a lot about that.

Michael Krigsman: Martha, everything you’re saying, of course, makes perfect sense, but it also has built into it the assumption that the CIO has the business capability, the experience, the skill to take on this innovative business role, and work across silos and departments and organizations inside the company. And that can be a challenge as well.

Martha Heller: Well, that’s part of the job. You know, recently, I was giving a keynote to a large group of CIOs, and when I got to the section about being a ‘what’ executive rather than a ‘how’ executive, and doing the gut check and taking the personal risk to do strategy, a CIO stood up and said, “I don’t have the skills to do that. I like implementing. I could implement all day long.” And I said, “Great! Know yourself. Know that you like to implement, but don’t be surprised or confused or concerned when your CEO hires a Chief Digital Officer or Chief Innovation Officer.” So what I would say to those CIOs who say, “I don’t have the skills, I don’t have the business acumen, I’m happy doing what I’m doing,” keep doing it but understand that as the business becomes more technology-oriented, your role will be marginalized and new technology leaders who are not in IT are going to come on board and you’re going to have to deal with them as business partners. So, know if you don’t have the business skills or the business context and you’re ok with that, define your role accordingly. But if you want to be a digital leader, having business understanding is everything.

Here’s a great place to start. This is actually quite pragmatic and revolutionary all at the same time…Let me just finish this thought Michael… Here is a great place to start. Stop using traditional IT metrics to measure your team. Stop defining investments by 3-9’s and uptime and least-times, and start using the metrics of the business. JetBlue, for example, Eash Sundaram who was CIO of JetBlue but is now CIO and Chief Innovation Officer, he’s certainly someone who’s moved forward in this way, he no longer measures his team on any traditional IT metrics. He shares with them the metrics held by the entire airline, which is called “Departure Zero”. How many of our flights leave the gate 0 minutes after departure? He measures his team’s performance and he measures their investment priorities based on its impact on D-0. When you are measuring your team based on the same metrics that the business holds dear, guess what? You’ve got a level of business acumen that you didn’t have before, and so does your team.

Michael Krigsman: And you know, it’s a very interesting point. How common is it in today’s world that’s very much in transition?

Martha Heller: I would say, one of the biggest challenges for CIOs is letting go of a degree of traditional control that their own IT organizations have always had over technology. And when you let go of metrics such as uptime and resilience and cost, and start using business metrics, it can be very unnerving and scary for people who have not done that before. So I think that in the whole wave of companies that have been slow to adopt new technologies that have kept IT in their own silos, I would say that business metrics are a ways off. But, my book is filled with CIOs who are leading innovation in their companies, who are business leaders, and it’s become much more widespread. And I think we will see a permeation through IT organizations in all different industries of business metrics as the barometer of success rather than IT metrics. And a comment on that: when those CIOs turn around to manage their IT vendors, I’m sure they will be employing traditional IT metrics.

Michael Krigsman: We’re talking with Martha Heller who is a multi-book author and truly one of the most important influencers in the CIO community. And Martha, you have your most recent book next to you so please, hold it up for us.

Martha Heller: I do! Here it is right now!

Michael Krigsman: “Be the Business.” And Martha, let’s talk about the relationship between the CIO and these positions like CDO, Chief Digital Officer. And you explained how the CDO role comes about, which is there’s this “digital void,” as you call it, and if the CIO doesn’t step up to fill that void, the organization will hire somebody else who does. But in many organizations, that’s not even an explicit decision that happens. The organization or CEO says, “Hey, we need to get a CDO in here.” And so, what is the quote-on-quote “right relationship” between the CIO and other executives like the CDO, CMO that are all encroaching and overlapping with IT today?

Martha Heller: You know, I’m going to take a step back in answering that question and say that we have been in an industrial economy since, I would say, the very early 19th century. We’ve been in a digital economy for about five or ten minutes now. The industrial economy is all about “more assets, more plants, more real estate, bigger teams.” The industrial economy is all about building walls around companies to separate us from other companies, and building walls around our departments. The digital economy is very different. The digital economy is all about algorithms trumping teams. You can do something with an algorithm and you don’t need a team, and that is often a better way to go. It’s about leveraging partnerships and breaking down the walls between departments in a business. It’s about creating permeable boundaries so that our vendors are not held at arm’s length, but become part of our workforce. And so, the most important work for a CIO to do vis-à-vis her executive peers, as per your question, is to use an end-to-end perspectives to free executives from their traditionally-held vertical prisons so they can look up, across, out, at their digital future together. So it’s the CIO’s ability to get their peers thinking fundamentally different about their business, and I’m going to give you a great example.

So this is one of my very favorite CIOs, Kathy McElligott. She is now the CTO at McKesson, but when I interviewed her, she was the CIO at Emerson, the electronics company. So when she was CIO at Emerson, when she came on board, she said, “You know, we’re aligned, IT has a strategy that is aligned to where the business is going. However, this business is putting sensors in all of our products, we’re collecting a tremendous amount of data, which is great, but we have not crafted a business strategy that capitalizes on any of that. The very fundamentals of what we are and what we do as a business must change, based of Internet of Things and Big Data and all of that.”

And so what she did what she put together what she called the “Business-IT Strategy Board,” 25 executives across the business, and they want to meet quarterly, monthly, I don’t remember the frequency, and let’s talk about big topics. So in her first meeting, she got them all together, and then she realized they were all sitting around waiting for her to give project status updates. And she said, “That’s really not what this meeting is.” So she brought IBM in to really workshop a strategy with them, and then after that she really was able to run meetings about internet security, about Internet of Things, about, “What would happen if we put the customer at the center of everything that we did here?” Now, some of these topics had a technology bent and some did not, and that’s almost irrelevant. Her job, as CIO, vis-à-vis her executive peers, was to facilitate a conversation that allowed them to look horizontally and together at the future of the company, regardless of whether there’s a CDO or a Chief Information Officer in the mix. That’s the CIO’s most important work.

Michael Krigsman: But still, as a practical matter, the organizational boundaries and the politics in many companies start to come into play. So again, what is the right way for the CIO to interact with these peers?

Martha Heller: Well, I would say, you know, this is classic stuff, I mean I probably wrote this article in 1999 for CIO Magazine. But it’s understand your business partners’ challenge, understand in business terms; consult with them about the growth plans or challenges of their business, and then define an IT strategy to help them with that; and then oversee its delivery. I mean, that’s how you win friends. But when it comes to driving innovation, which is one of our topics here, pick a fearless executive for who you have successfully delivered in the past, who believes in you and has your back, and work with that person on something new and innovative, and use that as a test case. Once you’ve got a success there, as my friend Steve Gold, the CIO of CVS says, “Wash, rinse, and repeat.”

Michael Krigsman: So collaborate on an innovative and interesting business case with the right business partner.

Martha Heller: Absolutely, and use that almost as a marketing tool to bring in the more skeptical executives.

Michael Krigsman: That’s a really key point. Now you talked about putting the customer at the center, and how does that translate into the CIO and the CIO activities?

Martha Heller: Well, I think for a long time we looked at business opportunities from the perspective of our supply chain, or our manufacturing processes, or in terms of what makes our numbers move in order to create shareholder value. Well, now we’re in a situation where customers call the shots. Customers have a lot more flexibility in who they do business with, customers have different thoughts about the style in which they want to to business, and companies that are not acknowledging that the customer is at the center of everything that they do are going ot be spending money in the wrong places.

I would also issue a cautionary tale. Putting the customer at the center of everything you do was a strategy that Kathy McElligott at Emerson brought forth to her team. But here’s where I would have a cautionary note about that. When companies imagine the idea of digital transformation or innovation, very often they think about marketing, right, and the customer-customer engagement and marketing. “That’s our digital, that’s our technologies, that’s where we want our CIO to spend most of his or her time.” But the fact is that digital is not marketing but with social media instead of print ads. Digital is much more than that. Digital is supply chain. Digital is employee productivity. Digital is the way we engage with our partners. So, you know, while, sure, you want to put the customer at the center of everything you do, you want conceptualize digital transformation as something larger than at that point where the customer and the company meet.

Michael Krigsman: Now, we’re going through some of the strategies that you go describe in your book that CIOs should adopt to be successful, and an interesting one is you talk about storytelling, and we hear storytelling again in relation to customers, we hear storytelling associated with marketing. So when you say that the CIO should be a storyteller, tell us what you mean by that.

Martha Heller: Sure. So ever since we were little, we loved to hear a story, right? And for those of us who have children, you know exactly which books have the pages falling out of them because we have to read the story so many times. And stories are a great way for two people of different backgrounds to get to a common ground on something abstract, and CIOs are always in a position of having to get to common ground on something abstract. So, I’ll just give you a quick example. Malini Balakrishnan, when I spoke to her, she was the CIO of a construction company, and when she got there, she said, “We have such old technology, we’re having outages left and right, and what we need is an ERP.” So she went to the team and said, “We need an ERP” and the CFO said, and this is a verbatim quote, “You will pry the old system out of my cold, dead hands.” So she thought, “Ok, I need another approach.” So she came up with the idea of taking a clip from the movie “Speed,” and in that clip, Keanu Reeves is a detective and he’s on a bus that’s got a bomb on it that will explode if it goes less than 50 miles per hour. So he has the idea of bringing another bus onto the highway, got to keep both of them going at 50 miles per hour, and everybody from the one bus has to walk across a rickety scary plank on the speeding buses from one bus to the other. So, she presented that clip to the executive committee and said, “This is our ERP situation. We’ve got to get a new bus ready while the old bus is running and everybody’s got to walk from one bus to the other.” And once she was able to show that clip, she was able to get them to the point of understanding the need for an ERP, and of course, people mentioned that story to others, so she had people carrying that story forward for her, where if she had shown an architectural schematic of the legacy systems overlaid with the ERP, she would not have had as much of an understanding of what was needed to move forward within the company. So that’s just an example. She didn’t have to come up with the story herself. She found something great that everybody could relate to, that’s a great way to get executives on the same page, at least initially, in moving forward.

Michael Krigsman: So the issue here is communicating in a manner that the business will find compelling, particularly that the business will find relevant and meaningful to their situation and that will push the business, therefore, to make the change that you as the CIO want to be made.

Martha Heller: Absolutely! I’ll give you one more example, and this was the CIO of a large pharmaceutical company who said he was having trouble getting his fellow executives to understand the multiple roles that IT plays. So he hired a photographer to take an aerial view of a three lane highway. In the highway you had one lane, motorcycles, in another lane, taxi cabs, and in another lane, big 18-wheelers. And he said the 18-wheelers are our global processes and our global technologies, we’re not creating change there, don’t even bother asking us to change that, that’s solid. The taxis are the more localized solutions for different regions that need something more specialized, and the motorcycles are pockets of innovation, new, cool stuff we’re doing, and with time, the motorcycles become taxis and the taxis become trucks. But he said, after he walked out of that meeting, having shown that aerial view, he saw the light in the eyes of his executive committee. So a story doesn’t have to be a fable. It can be a photograph, it can be a pie chart, but it needs to be designed to expressly communicate something abstract to a variety of audiences.

Michael Krigsman: So relevance is at the heart here, and we hear about relevance and the CIO. So let’s talk about factors that make a CIO relevant to the business.

Martha Heller: I love that question because I have a great answer for it. And this comes to me from the CIO of GE, because you know, Michael, I have no original thought, all I do is take the good thoughts of CIOs and put them together in a palatable form. But what Jim Fowler, the CIO of GE is concerned about is the relevance of CIOs and the relevance of IT and he says that, “We have a generation of workers graduating from college and coming into our businesses, and they are self-helpers. They want to create their own algorithms, their own digital tools, and they don’t want to wait around for IT. So for IT to stay relevant, it has to find a way to embrace that innovation, and be a catalyst for that innovation.”

So I’ll bring up the concept of “shadow IT” for a second. When I think about that old-school style of IT saying, “No shadow IT on my watch! No business executive is going to go out and buy their own technology and damage my architectural integrity, and introduce security risk and cost challenges into my infrastructure,” I imagine a man alone on the beach with his hand up, and a tsunami is coming over the beach. Well, that CIO can go ahead and put another hand up, but it’s not going to stop the rise of workers who want to be much more powered with the ability to create their own technology solutions. So Rob Lux is the CIO of Freddie Mac, and when he joined Freddie Mac, there were a lot of concerns about end-user computing, that is business leaders who hired their own development shops to create their own applications. Well that’s all well and good until those applications become mission-critical and have performance problems, and then they call IT to say, “Hey,” and the phrase they use is “productionalize,” “Can you productionalize?” And IT would say, “Boy, it would have been nice if you had involved us a little bit earlier.” So rather than clamping down on EUC’s, or End-User Computing, Rob created a development platform to allow end-users to go crazy! Develop your own tools, but do it in a secure environment using these tools. So a real concept here that I want to get across is, it’s one thing to say to IT, “Be the business,” but another thing we’re really saying is, “Let the business be IT.” IT does not own IT innovation, and delivery investment decisions and adoption, or even development! If end-users want to develop, they’re going to develop. Let them do it. So give them the platforms to do that. So that is being a catalyst and staying relevant, rather than saying, “Yeah, I’ve got to wait for IT.” That’s a perfect way for CIOs to become obsolete.

Michael Krigsman: We have about five minutes left. So it seems that the core of what you’re saying is that the successful CIOs are finding ways to engage the users, not put up boundaries, but invite the users in.

Martha Heller: That’s exactly right! So what we’re starting to see, and I’m glad you mentioned we only have five minutes because, you know, I could go on all day long. But, I want to bring up an important concept, and I’m seeing CIOs replace titles in their organizations, of, you know, this is an applications manager. This person has responsibility for all the technologies. And instead, they’re starting to talk about product management. Whether that product is something that will hit the external market, or whether that product is a finance system that’s for internal use only. And so what we’re starting to see on these product teams are cross-functional teams, so marketing, business analysts, business development, IT. You know within IT you’ve got apps and ops and architecture all on these same teams. And in fact Jim Fowler, CIO of GE, calls it a “teams of teams” structure. So when you conceptualize email as a product, or ERP as a product, suddenly you realize, on that product team, you can’t only have people from IT on that team, you need end-user representatives on that team. Product teams blur the boundaries between what is IT, and what belongs to the, quote, “business” that IT serves. So that product management, and one of the chapters in my book is called “Think Product” because as software makes its way into most companies’ products, where does IT development stop, and product development start? That is a blurry line that product leaders and CIOs need to start figuring out, because that is where a lot of innovation can happen.

Michael Krigsman: So we have just two or three minutes left, Martha, and would you summarize the distilled essence of your advice to CIOs. What’s the bottom line here? What’s most important?

Martha Heller: I would say that what’s most important is that 1) CIOs start to conceptualize their role in the organization, and this comes to me by the way from Cole Chapman, the CIO of the Gap; “As an internal professional services firm, that professional services firm provides information security, software development, product development, management consulting, email, data center hosting, vendor management, and once you see yourself as the CEO of a professional services firm, providing all these services out to the business, suddenly those boundaries in organizational design is all going to become clear to you. So that’s one. 2) Let go of control. Not everybody who uses the tools of finance in a company report into the CFO. Not everybody who considers themselves a developer needs to report into IT. Let your people go. Get into the digital mindset where empire-building is out. It’s about collaboration, blurring boundaries, letting go of control. And here’s the critical one: 3) Despite the fact that you run an organization, CIO, that is not your primary role. Your primary role is to use your end-to-end view and all of your analytical tools that demonstrate what is going on in the enterprise and become the critical capabilities champion of your company. Let your executive peers know what your company is good at, where it needs improvement, and that is where they should be spending their precious investment dollars. That’s your job.

Michael Krigsman: Wow, well, Martha Heller has given us a textbook on how to be a CIO. And there it is! You’re holding up the book, Martha’s most recent book, and what an amazing show this has been! You’ve been watching Episode number 198 of CXOTalk, with Martha Heller. And if you’re a CIO, catch the replay. Go back to the CXOTalk site, there will be a transcript up in a few days, and you can read it, and there’s your textbook. Martha, thank you for joining us today!

Martha Heller: It was my pleasure, Michael. Thank you.

Michael Krigsman: And I hope you’ll come back and you’ll do it again another time.

Martha Heller: Are you free tomorrow?

Michael Krigsman: [laughter] Next week would be good! Everybody, thanks so much for watching. Come back next week, we have two shows, they’re both going to be great, I’ll see you soon. Thanks, bye-bye.