Ford:
Transformation in the Automotive Industry

Michael Krigsman: Welcome to Episode #240 of CxOTalk. I’m Michael Krigsman, an industry analyst and the host of CxOTalk. Today, we are speaking about the future of the automotive industry, and we’re talking with three people who are truly in a position to know. So, stick around for a great, great, discussion. As we talk, there is a tweet chat that is going on right now using the hashtag #cxotalk.

And, before I introduce our three amazing guests, I want to say thank you to Livestream for being our awesome streaming partner. And if you go o Livestream.com/CxOTalk, they will give you a discount.

So, our three guests today are Paul Ballew, who is the Chief Data and Analytics Officer at the Ford Motor Company. Evangelos Simoudis, who is a venture capitalist, and who recently published a book on the automotive industry. And, David Bray, who just left the Federal Communications Commission as CIO and is joining the National Geospatial-Intelligence Agency as Chief Venture Officer.

Gentlemen, thank you so much for being here. And, let’s start with Paul. Paul, please briefly introduce yourself and tell us what you do at Ford.

Paul Ballew: Michael, thank you for the invite. Glad to be here! I’m the Global Chief Data and Analytics Officer for Ford, as you mentioned. We’re the group that’s responsible for everything for the enterprise: our data activities, data strategy, data management, data acquisition, but also all of our analytic activities that go throughout the entire enterprise, including new activities in the mobility space. So, we have the privilege of supporting the entire enterprise as we try to understand our customers, as we try to build better vehicles, as we try to do all those wonderful things that are out there in the future.

Michael Krigsman: And so, if we want to have a conversation about data in the automotive industry, you’re absolutely the right guy to be talking with.

Paul Ballew: Well, I hope so!

Michael Krigsman: [Laughter] Our next guest is Evangelos Simoudis, who is a VC and just wrote a book. Hey, Evangelos, how are you?

Evangelos Simoudis: […] Michael, thank you for the invitation. Indeed, I've been in the venture industry going on twenty years now, here in Silicon Valley. And, I'm a co-founder and managing director of Synapse Partners. We invest exclusively in startups that develop big data applications and focusing on mobility and the transportation industry, the telecommunications and the financial service industries.

And, as you said, I recently published a book called “The Big Data Opportunity in our Driverless Future.”

Michael Krigsman: And, I have to say that your book is outstanding. And, so, and it really helped me prepare. And so, I really recommend everybody to take a look. And, just say the name, Evangelos?

Evangelos Simoudis: Hey, it’s called “The Big Data Opportunity in our Driverless Future.”

Michael Krigsman: “The Big Data Opportunity in our Driverless Future.”

And, our third guest is David Bray, who has actually been on this show quite a number of times. And, David, you have a new role that you’re going into! Welcome back to CxOTalk!

David Bray: Yes, thank you, Michael! Great to be here and I really appreciate the opportunity to join both Paul and Evangelos to talk about automated cars and autonomous vehicles. The role that I'm taking is called the "Chief Ventures Officer." It's a new role, it's the first role of its type ever for the US Government, and it's recognizing that at the National Geospatial-Intelligence Agency, we need to make the shift from mapping the world to mapping and modeling the world so we can actually start to make predictions. And, that’s only possible if we bring some sort of automation and machine learning to what we do.

We’re grounding in data, just to give you a sense. Just one collector right now, per day, collects the equivalent of three years of all the NFL football games. So, you can imagine if you sit a human analyst and say, “Watch every day three years of football games and write a report on it,” that’s not possible. So, we’re going to have to do automation. We’re going to have to do some sort of autonomous machine learning approach to make sense of all the geospatial data in the world. And so, that’s why this is really great to have this conversation.

The other thing I’ll say is separate from starting a new job, as of just a week ago, I am now the proud father of a newborn baby boy.

Michael Krigsman: Oh, well! Congratulations!

David Bray: Thank you! I appreciate it!

Michael Krigsman: All right! So, to begin, how does one begin talking about the automotive industry and the future? And, why don’t we start by asking Evangelos to give us a sense of what are the forces that are shaping the automotive industry? And I ask you, Evangelos, to start because literally you just wrote the book on the subject.

Evangelos Simoudis: Yeah. Well, thank you! So, for me, the automotive industry and, by extension, energy is a very complex industry. And, in my book, I started thinking about what is shaping the next generation mobility, as I call it. And, I would say there are four or five trends; I see four or five challenges that I see.

First is the challenge of organization. We have more and more people moving to large cities, and particularly megacities; you know, cities with over 10 million in population. That is putting a lot of strain on both the overall city infrastructure and particularly the transportation infrastructure. We have, as a result of that, issues and challenges with congestion in many, many areas around the world. We are spending too much time commuting too and from work or where we need to go, and when we get there, we tend to be kind of exhausted and not productive. There are many cities around the world, there are many areas where you can see multi-hour commute times.

Next, we have the […] challenge of pollution, and we’ve started seeing that in Asia, but more recently even Europe is starting to face these challenges.

Next is the kind of aging population, and particularly in developed economies. These populations are starting to have special needs, and transportation is a very big component of those needs.

And, finally, the various social and economic problems that are starting to arise around the world, and several of them gave rise to the sharing economy.

So, in response to those challenges, I see a shift that is starting to happen from like a car ownership-centric model, to a model that combines car ownership with on-demand mobility and that’s what is starting to now shape the next generation mobility. And, as part of that, autonomous vehicles, both vehicles with internal combustion engines, but more importantly, autonomous connected electrified vehicles, are starting to be viewed as an important component for addressing some of these challenges in next-generation mobility.

Michael Krigsman: So, Paul and David, it seems like Evangelos just described a set of cultural, societal, emotional, and technological forces that are, can we say, pressing on the auto industry, or driving disruption, or forcing change? Would that be an accurate way of thinking about it?

Paul Ballew: We think of it, Michael, and get our arms around it to the best of our ability and try to forecast it for the future. We see the challenges on one end, which were just laid out, whether it’s congestion, the need to enable mobility, and areas that don’t have the economic buying power in developing markets. Certainly, the challenges from an environmental standpoint that we’ve been focused on solving for decades.

But we’ve also seen the other side, and those are the enablers, the fact that technology is now enabling things that we can only dream of a decade or so ago. It’s really the combination of those factors coming together that make this such a wonderful and crazy time to be in the auto industry.

I would point out that there are other things we have to take into account, which is why we're focusing on a multifaceted strategy to try to seize those opportunities, because we also have the ongoing love affair with my vehicle, especially in developed markets, and especially in cultures like the US so that personal use component is there, and you've got to reconcile that with the factors that were just laid out, and what technology means going forward to enable where we're going not only today but five years from now.

So, for us, what we're focused on is doing what we've always done, and that is enabling people to be mobile. That's a key part of the mission that we started with 114 years ago, and now we're just looking at it in terms of maybe a more diverse way of helping people be mobile and beating other issues and challenges that we face as a society. So it’s an incredibly exciting time with lots of dynamic properties playing out for sure.

David Bray: And, to build on what Paul is saying, I think it’s great that we’ve started off by framing this as it’s a combination of both what society needs and what society wants. So, it’s not just about the technology. In fact, if anything, the technology is 20% of this. It’s the other 80% in terms of how people are living cities and how people are living in rural areas and want to commute to cities or commute to work.

And then, it's also just a recognition that separates from all the technology, there are just so many demands on our day. I mean, we are now connected more than ever. That's a good thing. The bad news is, we are drowning in the amount of email, tweets, chats, and everything like that as well. So it may very well be that the younger generation, Gen-Y, and Gen-Z would prefer to have the car be as autonomous as possible so they can use their ride to work or ride wherever they're going to catch up on other things like connecting with friends and connecting with work, and getting work done, as opposed to what it used to be in the past, which was driving was a sign of freedom in some respects, and it was actually more cherished.

I mean, I would personally love to sit in a car, take my 30-minute commute to work, and actually be productive when I’m doing it, as opposed to being focused on the wheel and being focused on the way there. So, it’s amazing how this is really a combination of human plus technology, and that it’s not changing incrementally. I mean, this is all changing exponentially, both in terms of what the technology and the sensors can do, but also the amount of data that’s being collected and being produced from these vehicles.

Evangelos Simoudis:  Earlier in the week, I was in New York participating in a panel that Reuters organized on this very topic. And, what was interesting, talking both with some of the other participants and some of the other panelists, as well as the audience is that if the overall transportation experience, and the notion of productivity, gaining on productivity; figure very prominently in the thinking of next-generation mobility.

Now, some of this, I will admit, is self-selection. The participants in the audience, very much like us, they tend to have a lifestyle that requires productivity at different times of the day and all that, but it is … It figures very prominently in what drives the design thinking for what’s next.

Michael Krigsman: I want to just remind everybody listening that right now, there’s a tweet chat going on using hashtag #cxotalk. And, we’re speaking with three experts on the automotive industry and the future. And, ask them questions, because you have a rare, rare opportunity.

And we have a question from Twitter already. And, this is directed towards Paul, and this is Scott Weitzman, [who] is asking, “How is Ford adding technology without distracting drivers and is there a large push within for autonomous vehicles?” And I find that an interesting question because it starts to intersect the technology with the human factors and the social dimensions that we were talking about earlier. So Paul Ballew, what do you think?

Paul Ballew: It’s a very good way of thinking of it, Michael. And that’s really for us, how those things intersect to provide greater value, greater benefit to society as well as to the individual. And as we look at this, we have a lot of work underway in terms of distracted drivers and the activities to make sure that we’re ensuring that we’re driving safely going forward. And that, of course, the intersection of potentially some level of autonomy in a vehicle then converges with perhaps, that benefit, along with other benefits that we’re seeking.

The strategy going forward is to continue to progress down these roads whether it’s some form of mobility solution that’s convenient and provides the benefit to the customer whether it’s where we’re going with autonomous vehicles or whether it’s going in other directions because if you can intersect that effectively, you start helping the individual, you provide benefits to the societal elements of this as well. And you take out some negative consequences that are occurring at the same time.

And so, it’s a great question, because that’s the way we think of it each and every day. And we think of this as potentially a seminal moment in the history of the industry, which by the way, on its own foundations is a complex industry. And now, you add this all together with more layers of complexity, but you're doing it and embracing it in a way; at least, we're embracing it at Ford; as offering all these possibilities. So, we see it as more of a positive and that conversation around distracted drivers and other sorts of topics, or some of those related or potential benefits that we could derive, depending on where we end up landing. But certainly, where we end up going, we're looking at those factors as certainly being an element to take into account.

Evangelos Simoudis: And, since we’re talking, Michael, about autonomous vehicles and Paul, I’d be interested in your opinion on this, I view, frankly, the level three autonomy, with regards to the audience’s question, level three autonomy as being the riskiest of these propositions with regards to the technology and the user experience. Because, in level three, you have enough autonomy for the driver to feel if they can relinquish control, but you don’t have enough autonomy where you need the driver’s input in many situations; whereas, in level one and level two, the driver has a very good understanding that they are in control.

In level three, you start relinquishing some of that control, and like I said, it becomes more generous because, in level four, level five, the vehicle will have enough intelligence to be able to operate autonomously and eventually without any driver.

So, I think that that’s where we have a … That’s where the automakers have the biggest challenge in terms of creating the right technology, the right safeguards, and the right user experience there.

Paul Ballew: And so, we’ve been focused on level four and have been very public about that, consistent with those thoughts, as well as other factors, as really where we’re going and where we’re really pushing forward because we believe it’s at level four that we start talking about the true viability of the use-cases for autonomy-type mobility solutions. And so, for us, we have been very public on that, and we remain very committed to it for those factors as well as others; and certainly, as you go down this path, we have to take all of those factors into consideration. There’s not some magic bullet out there that suddenly transforms the journey we’re on, this is a very exciting journey, but it’s a very complex journey and comes with a high degree of responsibility that goes along with it.

David Bray: So, actually, if I can ask a question of Paul: So, obviously, there’s a lot of data being produced as you go to level four. Do you see that being stored and processed more by the car? Is it being collected sort of more by the road or infrastructure or somewhere else? And then given that, what do you see the possible three years from now, the ecosystem looking like in terms of what’s being done with the data and being made sense of the data there?

Paul Ballew: So, to answer your direct question, I would say “yes.”

David Bray: [Laughter]

Paul Ballew: […] by the car, processed by the car; could be within the ecosystem proper. Certainly, will be in some type of central environment as well. Again, what exciting about the journey we’re on is that the technology is enabling us to do things on the data side which ultimately then allows you to go down the brain development side of autonomy-type vehicles or autonomous—type vehicles. And that, for us, at least for what I do for a living, is very exciting because it’s prompting us to push forward not only with edge data analytics but edge data management. And, that is a very, very exciting area for us to play in, so I think the answer to your question is going to be all of those factors together.

And, when we think of something as complex as what we’re trying to do here in the massive data analytic challenges going on with it, you’re going to have to have a more diverse ecosystem to enable that.

And if you’re really going to go beyond autonomy but have smart vehicles that are interfacing with each other, that could have all sorts of other individual and societal benefits, then you also have to make sure that the ecosystem is going down that path as well, and that includes smart infrastructure and related activities.

So our thought process as we’ve been going through this is to be pretty agnostic, to be pretty humble as the technology is changing from a data and analytics standpoint, and then realize that the ecosystem is not going to be a traditional one where, miraculously, somehow we’re just going to hook up every vehicle to some pipe and collect every data element and somehow build data centers that are the size of the state of Texas. That’s really not the strategy because it’s just not feasible. But, the good news is that technology is letting us now do other things that offset those concerns.

Evangelos Simoudis: […] Michael, if I can add something here. David, to your point, is a point in my book, actually. There's a need for both kinds of new frameworks around which to think about data. I mean, you mentioned there is the transportation infrastructure data, there is the data from the vehicle, there is the data from the passengers of the vehicle, there is the data from other vehicles, as well as data providers. I'm sure it's a very complex ecosystem that we are talking about here. I mean, we tend to think about the data that is produced by the vehicles, but this goes a lot beyond that.

And, I’m glad that Paul mentioned the fact that there is a need for rethinking data management. This is not all about cloud-based storage. Even though telcos with whom I've worked quite extensively, they are thinking very, you know, very deeply about that. But, you need policies on what data to keep in the car, what to push outside of the car…

And the other thing that makes it complex, I mean, as this ecosystem is being reshaped; you have to understand that we are not talking about a single cloud. So, this is not about Ford's cloud versus BMW's cloud or GM's cloud. This is … You know, Ford would have a cloud, but Delphi could also have a cloud … will also have, not "could," will also have a cloud and weather.com will have a cloud and all of those. So, even fro the data that’s going outside the vehicle to this type of an infrastructure, the decision in that [which] has to take place is very complex.

And, again, what was interesting to me in researching the book, is that obviously, over the past twenty years, the automotive industry, as the car has become more and more software-dependent, has become aware of the importance of data. There are already quite a few sensors in vehicles today. But both the type of data, the complexity of data, the volume of data, the big data that we’re talking about, in an environment where we have autonomous and eventually driverless vehicles and on-demand mobility is so stupendous compared to what we have been used to dealing with today. And, that’s what requires the new thinking.

Paul Ballew: We agree, and one of the reasons why we brought together an organization to do this was in part to bring that new thinking forward. And certainly, it applies to autonomous vehicles, but it also applies to other things that we have underway such as IoT. When we start talking about the Internet of Things with an industrial setting and plans, you can’t just go down a conventional data management approach, and expect to be able to manage that even if you use cloud-based storage for physical data centers, it’s still impractical and makes absolutely no sense in terms of a sustainable model.

So, our way of describing is modern master data management. So traditionally, we talk about, yes, those core principles and data management are essential, data structure and related activities, but it is a completely unique way of thinking about how you ingest and curate and leverage those data assets to support business objectives. And I actually think it’s going to be one of the more exciting areas for us in the next five years or so, on top of the vehicle and on top of mobility solutions. We’ve got to get that right, and it’s once again, one of the reasons why we’ve established a group that I’ve had the privilege of leading a couple years ago, because we could see that we’ve got to go beyond the conventional thought processes that any company has, not just automotive, in the way we’ve thought about data management: build a central environment, call it a data lake, put some type of identifiers, and all those things with it. The world is moving well beyond that.

By the way, for us, we’re taking many of the principles of what we’re doing in data management with the vehicle and applying to what we’re doing to support our manufacturing organization. So, that’s pretty cool as well that the people that are responsible for one are sharing the capabilities with other parts of our overall organization.

Michael Krigsman: Evangelos, in your book, you describe all of this as the automobile or the car, the device, the mobile device, mobility device, as a platform.

Evangelos Simoudis: Yeah. So, again, over the past whatever twenty or so years, I think the automotive industry has been thinking of vehicles as platforms. In fact, much of the terminology that they have been using, companies including Ford, has been around platforms.

I think what is different here is that we're talking about different type of platform. It's no longer a platform for electromechanical devices for some computing, but it's a platform of sensors and actuators with an immense amount of computing power and quite a bit of storage to address the issues that we were just talking about.

So, some people have described it as “robots on wheels.” I think when you think about on-demand mobility and applications such as ride-hailing, you could think of robot taxis and robots on wheels. If you think about long-haul tracking, which is another application, another projected application for autonomous vehicles, again, you’re thinking about these vehicles that are very robotic.

But this idea, what I wanted to communicate, is that we have a very different kind of platform than we’ve used to date in vehicles.

Paul Ballew: It's interesting to describe a vehicle as a platform but any of us that have grown up in the industry, when we think of platforms, we think of the physical architecture of a vehicle. There was a small utility platform. There's a mid-car platform. And the evolution of the last few years have been talking about Vehicle-as-a-Platform for a variety of different ways. And when we describe a platform now, we describe it as an interface point, an insight-generating point, or the ability to leverage and connect vehicles together.

And so that particular word has evolved in a very short period of time in our industry. And now, when we describe it as a platform, we actually have to pause a moment and describe what do we mean by platform. Never thought I'd have to put an operational definition around Platform in the auto industry because it's one of the things that was just common terminology.

Michael Krigsman: David Bray, I was just going to say… David Bray, we have a couple of questions from Twitter where people are wondering about the public policy implications of all of this, and you’re the man who works in the government. So what about the public policy implications of all of this?

David Bray: So do you want me to answer on behalf of the entire US government?

Michael Krigsman: That would be helpful. [Laughter]

David Bray: [Laughter] But, I will first caveat and say I’m not a congressionally-appointed commissioner, so I can’t just answer there. But it warmed my heart to heart for both Paul and Evangelos to talk about how there’s not going to be a single place where this data is going to be. I think that is a massive change, and it's going to create interesting challenges for public policy.

I know that in Europe, there’s a thing called GDPR, which has certain rules as to whether data can be done and what can be done with the data. Also next year, about this time, the summer, there’s going to be a rule that if you make an automated decision, you have to be able to explain how you made that automated decision. So that’s going to create some interesting challenges on the Europe side.

In the US, actually, so I was actually just at, last week, with Vint Cerf at a conference. It was a data summit in Ireland, and we were talking about the exponential increase in data. In fact, to give you a sense of the scale, data is doubling about every eighteen months on the planet. By some estimates, by 2022, we’re talking about 96 billion terabytes, which is actually more data than all human eyes see in the course of a year, or twice all the conversations we’ve ever had as a species will be on the planet.

And so, this is going to create new challenges both for how the data’s stored, but also how you make sense of it; what you keep, as Evangelos mentioned. And I think, actually, we nee to actually have, and it’s great how we were talking about how Platform evolves; we may actually need to think about how data as a platform evolves as well. Right now, in most cases, we’re storing data on the same platform where we set our privacy permissions and other rules. But what we may need is something much like, we have a mutual friend that you and I have, Michael, at the University of Texas by the name of Phil, who’s actually looking at what’s called side-chain technologies in which students own their student records, as opposed to the registrar, and then they choose who they share it with.

So it may very well be in the future, the car, even parts in the car, as well as infrastructure and the passenger, are able to choose who they share data with and for how long. Maybe it’s only being shared for a day. Maybe only for thirty minutes; maybe it’s for a longer time period. But, this sort of dynamic sharing of data, and then where it’s being processed and where it’s being made sense of, given that you’re going to have limited compute cycles, I think that’s a rapid chain from right now the world, in which we have the Googles, the LinkedIns, the Facebooks of the world, in which data is co-located at the same place as your controls, we may very well look in the future where your controls are separate from where the data is and there are conversations going forth both with the passenger but also with an autonomous system as to "I need this data now, or I'm sending this data to you right now because I want to make sure there's not going to be a collision." Things such as that. That's a completely new approach to Platform even further beyond what we usually think of platforms where it's the data and the application programming interfaces in the same place.

Evangelos Simoudis: David, you’re bringing an excellent point and this notion of a data half-life. And, the … What is particularly important about your statement is that we will start … we will need to start, having rather, several definitions of half-life that might be … One definition may be for how much do I keep the data in the vehicle? You know, I collect a lot of data, not everything should be kept forever or for a long period of time. But, there are other notions such as the one that you just mentioned, for how long can I share that data if I decide to keep it?

So, this notion of data half-life is again, is another novelty that, in the transportation industry in general, we never had to think about. And now, all of us who are working in this industry will need to start creating this polymorphic definition of half-life; data half-life.

Paul Ballew: The data stewardship activities associated with this are just an example of how we’re going into this next phase of managing all of it. So whether it's data half-life or our storage policies, or use-cases, or all of the things going along with it, it's part of the fun of this journey right now because we are going into areas where I'm not even sure other industries have fully had to deal with all of that complexity because of the nature of our industry has such a profound impact on individuals and on society. And that prompts a real set of emphasis for us to make sure that our approach in terms of stewardship and the journey we're on tries to take all of those factors into account, including things like data half-life. But, there’s a whole other list of issues that we’re discussing and trying to get our arms around each and every day.

David Bray: Michael real quick, recognizing you got a question but I actually wanted to add one dimension to this. So, part of what I'm doing when I'm going over to the National Geospatial-Intelligence Agency is that we believe that we're sitting on top of forty years of very valuable data about the planet and geospatial. And so, what we're looking at is, assuming Congress gives us the approval, we're actually going to set up a public-private partnership where individuals, if you have a neural network or if you have a machine learning algorithm and you want to train your algorithm with our data, and we think it's a win-win for both of us, that is going to actually help make sense of geospatial information better, we're thinking that the currency of our data is so valuable, you'll actually work with a nonprofit to train your machine against our data.

You keep your intellectual property, but it’s the idea that it’s actually this win-win both for the government because we get better algorithms to make sense of all this data. At the same time, US companies can actually train their machines against large, pristine data, and benefit. And so, I think the same thing to think about for both Paul and Evangelos with the data for cars: do we need the equivalent of a place where people can actually practice and teach the machine against that data, see what works and doesn’t work, and go from there.

Evangelos Simoudis: So, having data for training the systems that will go into these autonomous platforms is becoming a much bigger deal than we even thought. And in fact, today, one of the investment species in my firm is identifying startups that do simulations. Because, if you think about even the companies that are fielding test vehicles, they can collect very small amounts of data, both because they have very small fleets, but also the amount of data that can be collected physically tends to be a relatively small sample of what we will need in order to effectively train this artificially intelligent system to reliably create and provide the autonomy to these vehicles.

So, we … Today, I mean, Waymo and Tesla have probably the most data, but even that is a very small amount compared to what is needed. So, creating their larger collections, whether of other contributors that have actual data or creating simulated data that can be used to effectively train systems, I think will be a very big deal on our journey towards kind of like a driverless future.

Michael Krigsman: We have only ten minutes left, so I’m going to ask everybody to keep your comments relatively on the shortish side so we can cover as much ground as we can in our last ten minutes. And we have a question from Twitter that links back to the earlier discussion on the ecosystem. And, Paul, you mentioned the importance of that ecosystem, and so Sal Rasa is asking, what are the necessary cultural shifts that need to take place to ensure alignment between internal efforts inside Ford, alignment with your partners, and alignment with this goal that you described earlier regarding the customer experience? So how do you think about changes in the ecosystem going forward as a result of all of these data shifts and things that we’ve been talking about?

Paul Ballew: Well, we think long and hard about this. And if you go from Bill Ford's approach even a decade ago to what we're focusing on today, we look at it in terms of a high degree of humility of working with partners, finding a common interest, not trying to build everything internally, find those opportunities to collaborate and enable and support. That's a change not just for Ford, it's a change for most companies to try to do that. But as we go down this journey, it's going to be an ecosystem that's going to advance the cause.

You know, we get often asked is are we unsettled by the fact that there are others playing in the autonomous vehicle space, and our normal response is, “Well, we actually like it because we think it will advance the cause across that ecosystem.” And that’s an interesting way of viewing it, but it shows that we focused in terms of embracing the opportunities going forward.

And then, for us, as an industry, the ongoing pivot towards being very customer-centric is at the center of our journey. One of the reasons you set up a data and analytics organization is to have insights about your customers where you can make a difference in their lives. And so, it’s at the center of our journey and it’s been a lot of fun over the past couple of years.

Michael Krigsman: We… One of the questions that David Bray gave me before we began, as he and I were discussing this, is he was asking about the algorithms. And, when you have autonomous vehicles from different manufacturers, how do you ensure that a car from one manufacturer, from the driver point of view, performs in the expected range of if they get into a car from another manufacturer?

Paul Ballew: Yes. So, David wanted to talk about amalgamation, which is a fancy word for trying to get us all … I firmly believe that at some point in time, as this evolves, we'll solve those issues. Developing in the algorithms to empower this cognitive machine that we're talking about, what we described as the VDS system, the brain of the vehicle, there's a lot that goes into that cognition. There's a lot that then has to be harmonized with its operating environment. But, I’m pretty confident that we'll sort that out because guess what? We, as an industry, with support from the public side as well as those in the private sector, are driving some commonality of standards and harmonization and so on and so forth. We all drive on the correct side of the road. We all obey, for the most part, traffic signals and devices. The vehicles all have similar technology associated with them; things like airbags and so on.

So, I’m pretty confident we'll sort that out. And the good news is, the geeks of the world, which are me and others, live for these challenges.

Evangelos Simoudis: And, Michael, one more point to make to indicate where we are on this journey, because I think that sometimes, and particularly in certain centers including Silicon Valley, one would think that the next couple of years, it will be possible for all of us to go to a dealer and go to an internet site and buy a fully-autonomous vehicle.

Today, there's still a lot of technology problems to be solved, and software, in my opinion, software-related problems, since you mentioned algorithms, are some of the hardest problems to solve in having, and reliably fielding these fully autonomous vehicles. So, I don't think that we will have, you know, fully addressed these problems in the next couple of years; two or three years, as some people and some manufacturers, may believe, or they've claimed. So, I think, on the software side, I will feel much more comfortable in a seven to ten year journey, if you will, when, again, going to David’s point, where we will be able to reliably and in a homologized way, talk about autonomous vehicles that can coexist with the conventional vehicles because, we’re not going to, anytime soon, we’re going to replace everything on the road with just autonomous vehicles. So, there is a lot of work to be done to address the software problems; a lot more work than will be necessary to address the hardware problems.

Michael Krigsman: And, very, very quickly because we’ve only got a few minutes left, Paul Ballew, and I hope I’m pronouncing your name correctly, Paul, because I should have asked you earlier.

Paul Ballew: You are!

Michael Krigsman: What’s the timeframe for these changes?

Paul Ballew: I think the next decade’s going to be interesting. We’ve talked about a level four vehicle being out there in the early parts of the next decade. I think the next five to ten years is where we’ll start to see that jump in terms of technology and deployment. There’s a lot to do between here and there.

By the way, I think when we talk about this, we often just focus on the autonomous vehicle side. There are things already occurring with regards to mobility solutions that are here and now. And so, autonomy, we’re talking about the early stages in the next decade to really start seeming to ramp up because of the software challenges and the technological challenges. But, there are a lot of other things happening in mobility that are occurring right now in front of our eyes, and that makes it equally as exciting.

Michael Krigsman: And David, would you care to make a prediction? You’re not inside the auto industry, but you’re certainly a data guy!

David Bray: I am a data guy! I would probably agree with Paul that we’re looking at the next decade for autonomy to fully mature. But at the same time, there are already advances here and now and things coming along the way. And also to just echo the comments that were said earlier about what do we do about algorithms together, and that’s a really hard computer science challenge.

I think one of the nuts that we also have to crack is how do we solve interoperability amongst the data? As one who has participated in human standards groups, they usually have three to four-year timer horizon to actually create standards for that. That doesn’t really strike me as a reasonable thing to think about in terms of setting data here. So, we're probably going to need some semi-autonomous mechanisms to make sense of data from different devices, different vehicles, and have some interchange among that. Because, if we rely only on the human condition, we’re going to be slowed down by ourselves.

But, I do think we’re going to see advances over the next decade and I think full-fledged autonomy – probably seven to ten years, but hopefully make advances along the way.

Michael Krigsman: And, Evangelos Simoudis, you, in fact, as I said before, wrote the book on the topic. And so, in one minute or less, what advice do you have for the automobile industry? That's like, you know before David was representing the entire US government, and now you can give advice to the entire auto industry in less than a minute. I just chewed up some of your time, so I apologize for that.

Evangelos Simoudis: I was […] bold, making this statement earlier. I think there needs to be a cultural change in the industry from being the design and manufacturing business to being in the insight generation and transportation solution business, at least terrestrial transportation. Some companies, including Paul’s, they’ve already started thinking about that and going that journey. I mean, the CEO change at Ford is a very good indication of that, in my opinion.

But, that's going to be the biggest obstacle. I don't think it's going to be technology to the degree that we think about today. I think cultural change and appreciation of the data and the fact that the cultural change is both for a different kind of solution and a different kind of collaboration with startups and other types of partners in order to make next generation mobility a reality. And again, it’s not only about autonomous vehicles.

Michael Krigsman: And, let's finish it out with Paul – I'm giving you the last word. What advice do you have for the car industry, the automotive industry, as a whole, regarding the transition into this future?

Paul Ballew: Yeah, I started in this industry in the mid-1980’s and one of the thing that I always trust for the industry that we have to do is we have to embrace change and embrace the opportunity that comes before us. We’re an industry that’s been around for over a hundred years. And sometimes, it’s been hard for the industry to embrace change, and we have to do it in this case. And if we do so, I look at our industry having a very bright future because of the ability to get from Point A to Point B and transform your life is a human desire that has been with us since the dawn of time. And that's the opportunity in front of us; 114 years ago, we put the world on wheels. Our goal is to make the world more mobile going forward.

David Bray: Real quick, Michael, for ten seconds. I look forward to the day when we can have the Indy 500 be the Indy Robo-500.

Michael Krigsman: [Laughter]

All-righty. So, that concludes our show, and boy, that time went quickly. I would so much like to thank our three guests today. Paul Ballew is the Chief Data and Analytics Officer for the Ford Motor Company. Evangelos Simoudis is Managing Director at Synapse Partners. He’s a VC and author of a great book on the automotive industry. And, Evangelos, tell us again the name of your book?

Evangelos Simoudis: “The Big Data Opportunity in our Driverless Future.”

Michael Krigsman: "The Big Data Opportunity in our Driverless Future." And, David Bray is the incoming Chief Ventures Officer for the National Geospatial-Intelligence Agency.

Everybody, thanks for watching! Next week, we have another incredible show. Workday, a Software as a Service company, has got four female C-level executives. And they’re all going to be here talking with us together. So tune in next Friday, and check out CxOTalk.com/Episodes for all of our upcoming shows.

Thanks so much, and have a great day.