IDC Business Software GroupIDC's worldwide Business Software Group leads the research and consulting in software applications, software business models (Licensing, Provisioning, and Cloud Applications) and software and infrastructure channels and alliances.

Specific application coverage includes:

  • Cloud Applications, Software as a Service (SaaS) and Platform as a Service (PaaS)
  • CRM: Sales and Service, CRM: Marketing technology and Customer Experience 
  • Enterprise Applications, Digital Commerce and Asset Centric Networks
  • Social and Collaborative Technologies and Community Platforms 
  • Content and Digital Media
  • Human Capital Management
  • Mobile Enterprise Applications

The current research agenda for the group is built around the concept of business modernization and looks at how businesses can adapt and modernize to thrive in the post-industrial and post-application era. The following diagram shows the areas of focus for the group:

For more information, see the IDC website.

IDC Business Software Group
IDC's s perspective on enterprise software, and emerging software and Internet-enabled ecosystems.


IDC Business Software Group

Proximity Marketing

  • Partner: IDC Business Software Group
Mike Fauscette, Chief Research Officer, G2 Crowd
Mike Fauscette
Chief Research Officer
G2 Crowd

IDCThank you to IDC for underwriting CXOTALK.

Proximity marketing or hyperlocal marketing as it's sometimes called, is on the upsurge this year. The fact that the smartphone market continues to grow with ~1.3B shipments in 2014 WW, and a CAGR of near 10% through 2018 (based on the IDC Smartphone Tracker) is a part of that of course, but also the technology supporting proximity marketing is much more refined and available. There are also some good successes that are getting the attention of all types of businesses. 
Proximity marketing uses technology to find and interact with mobile device users in close proximity to the business or in some way opted in to the interaction. It is permission based and generally uses one of these technologies to interact with the mobile device:

  • Cellular
  • Wifi
  • Bluetooth
  • NFC
  • GPS / SMS
  • QR code

The interaction can be in the form of an offer, a free download app, or some other relevant content download.  To identify the "target" the business usually uses some form of geo-fencing, either GPS/Cellular/wifi or Bluetooth, which is generally the more granular and referred to as microfencing. There is some established signal threshold that is used to establish proximity. Most proximity marketing is push based but NFC or simple QR codes can be used for pull programs as well, where a target interacts with a kiosk or other NFC enabled device, or a posted QR code, to download an app or content. Using the QR code is the simplest type of program to run, and can be very cost effective while still producing solid results, particularly for providing an interactive retail experience (shelf tag QR codes) or in situations where an app download can be used, for example restaurants.

Using a mobile app as a part of the overall customer experience (CX) strategy has gotten a lot of attention over the past year or so. It can be an excellent way to provide customer service, deliver content, tie the customer into the company's community, capture data and improve the loyalty program experience. Proximity marketing techniques can play an important part in driving app downloads and increasing app use and should be considered as a part of that program.

There are some pretty good examples of how companies are using proximity marketing, here are a few ideas and examples:

  • Retail: loyalty program - app download - store maps (particularly useful in large, complex stores like building supply) - shelf tags (QR codes) for education and content - real time promotions - Mall management companies are providing proximity services for Mall tenants in addition to in store operations/programs - interacting with digital signage - capture additional customer data
  • Public transportation, rail station/lines and airports: interactive transit map downloads - app downloads - facility maps - selling access to transport beacons for other business campaigns - loyalty programs - real time promotions
  • Trade shows: interactive show floor maps - app downloads - show schedules - promotions and offers from exhibitors
  • Hotels: app downlaods - hotel maps - loyalty - check in/out and reservations
  • Restaurants: app downloads - loyalty - real time promotions - ordering / take away / delivery services - food information (one recent example for people with food allergies, the restaurant provided a business card with a QR code that drove the diner to an interactive site that listed ways to order different food based on allergies)
  • Consumer products: loyalty programs - app downloads - promotions (particularly in cooperation with retail stores) - campaigns (there's a particularly interesting case study about a UK brand of body spray that used an on campus dating app to successfully promote it's product. Another recent campaign by Redbull used digital signage at the point of sale to bluetooth coupons to consumers.)

What's in it for the consumer? It's important to not lose this very comon thread, there must be value in your campaign for consumers to want to opt-in and be involved. That's really the biggest question for a campaign or app, what is the value it delivers to your customer? That might be discounts and promotions, better customer service, engaging and entertaining gaming experiences, etc., but overall there must be obvious value. Here are a few other tips:

  • Keep the solution as simple and focused as possible
  • Leverage technology when it makes sense but don't forget that low tech like QR codes might be the most effective for the problem you're trying to solve
  • Always respect opt-in (and just a word to Verizon Wireless, just stop using the track anywhere tags / supercookies on your subscribers; and 3rd party solution providers, do not use them to track people that have opted out of cookies, it's an invsion of provacy)
  • Individualize as much as possible, people want programs that are relevant to them personally. Location isn't necessarily enough to individualize, that's why loyalty programs and apps can help fill in the profile and support a higher level of tailoring.
  • Language matters, in many places you will need multi-lingual support for your campaigns to be effective
  • Keep the content fresh and relevant
  • Use apps if possible, it improves the experience considerably and provides a much richer opportunity to tailor to the individual
  • The campaigns are generally real time, that gives the opportunity to analyze data in real time and correct / change the program as necessary
This originally appeared on the Michael Fauscette blog

A Step Towards Protecting Net Neutrality

  • Partner: IDC Business Software Group
Mike Fauscette, Chief Research Officer, G2 Crowd
Mike Fauscette
Chief Research Officer
G2 Crowd

IDCThank you to IDC for underwriting CXOTALK.

It was rumored for the past few weeks that this would be the week that the Federal Communications Commission (FCC) would preview new rules to protect net neutrality (if you want more background on net neutrality and the issues I wrote this post last year). Today on, FCC Chairman Tom Wheeler explained the proposal that will go before the FCC for a vote on February 26th. It has taken quite a while to get to this point, including the ruling by a federal appeals court last year striking down the earlier FCC Open Internet Rules which were founded on classifying ISPs as information services not common carriers. The new proposal, which comes after a crush of public feedback and massive lobbying efforts against reclassification by companies like Comcast, Verizon, AT&T, TWC, etc. will reclassify ISPs (both landline and wireless) as Common Carriers under Title II. This reclassification will allow the FCC to establish Internet rules on the much more solid footing of Title II which is used to regulate utilities including telecommunications companies. Title II is a collection of rules that are very broad, all of which "could" be applied to ISPs. The longer term question is, which of those rules will the FCC choose to apply to the ISPs?

The basic, underlying goal of the FCC in reclassification is to get the legal grounds to regulate the Internet and keep it an open platform. While the exact rules that will be applied to the ISPs will remain an open question for some time, the underlying objective was made clear by Chairman Wheeler. The FCC plans to put rules in place that will ensure:

  1. The Internet remains an open platform for innovation
  2. Paid prioritization of content (and services) / content providers would be ruled illegal. This is a particularly important point, as the so called Internet fast lanes have been a particularly egregious part of the ISPs actions against consumers and content providers like Netflix, Hulu, etc. The Internet would then be an open conveyance to all content / content providers. Or put differently, if you pay for a certain download speed / bandwidth the ISP would not be allowed to throttle content from providers that it then tries to also charge for the same thing you already paid for, network bandwidth.
  3. Consumers have a place to go for help if they have problems / issues with an ISP that are unresolved by direction interaction between the consumer and the ISP. This is not currently the case, currently consumers can only deal with the ISP but there is no agency to intervene if the problem persists (short of the court of the social Internet anyway).
  4. A level playing field for infrastructure that will likely result in more investments. Specifically this reclassification would benefit Google (it is in support of this change) and its Google Fiber initiative by giving it access to utility poles and other infrastructure assets that it currently would have to pay other utilities to use.

The reclassification still has to pass the FCC vote on the 26th of course, but it seems likely that it will pass. It's also likely that Congress, which is already giving some indication that at least some members are not supportive of the FCC's reclassification efforts, will try to pass some legislation changing the underlying communications act (the bill has been proposed a couple of times before). Whether it would pass is very questionable though. Once the reclassification is done, it is even more likely that AT&T and Verizon (and others) will try to fight the FCC in court.  Also good to note that the changes would take awhile, maybe up to a year, to be put into effect. If you want to support this effort, you can reach out to the FCC here.

This originally appeared on the Michael Fauscette blog

Cloud Software and Business Modernization: Part One

  • Partner: IDC Business Software Group
Mike Fauscette, Chief Research Officer, G2 Crowd
Mike Fauscette
Chief Research Officer
G2 Crowd

IDCThank you to IDC for underwriting CXOTALK.

The term digital transformation is really popular in tech circles these days. I’ve used it myself over the past year or so, and I definitely think that the concept is sound. I have noticed though, that when I talk to businesses about it, they seem less than excited with the term. Not that most businesses don’t recognize that things are changing and that technology is at the core of much that is creating disruption for them. I think you’d have to live under a rock to believe that business as usual is well, “usual”. Still most businesses have used digital technology for decades, if they were around back in the dark ages anyway. I’m starting to think that perhaps the better way to frame this discussion is as business modernization in the post-industrial enterprise. Tech is at the core of those changes of course, but it’s far from the change of simply implementing some new software / hardware, automating some processes and learning a new workflow. The changes are much more fundamental and alter the way work gets done, the type of work that is done, and the way people interact. Data becomes a core part of every operation.

From my perspective business modernization ties together changes to data, technology, people and process across six major areas. These areas are:

  1. Cloud Platforms/Microservices / Post Application Era
  2. Customer Experience (CX)
  3. Commerce
  4. Workforce 
  5. Innovation
  6. Business Networks

Across six or so post I will take a look at each of the six areas of modernization across those four categories, data, tech, people and process. Culture of course is also an important part of any change, and has to be addressed in a change management plan as the modernization efforts unfold. Before jumping into this conversation, I suppose it’s useful to set a few base assumptions for modernization:

  • Moving to the cloud has become a “when” discussion not an “if” discussion for almost all businesses. Not that everything will move immediately of course, business tech will be hybrid on premises / cloud for the foreseeable future but new initiatives will most likely be in the cloud. Almost all truly modern software is available in the cloud model and almost all (I’d say all but I’m sure there’s an exception somewhere) on premises only software is old technology. There are modern software offerings that are available in a dual cloud / on premises model though, and some (a very few) companies will add on premises apps based on some internal biases, regulatory and / or governance issues, privacy concerns, etc. 
  • We have moved beyond “mobile first” to “any device, anywhere”. In other words, any new app must be device agnostic IMO. 
  • The most interesting technology and modernization efforts are happening at the intersection of data and social (or people). Each post will look at this intersection in detail.
  • Cloud and mobile (any device actually) are simply the delivery and use models. They offer lot’s of value, but that value is already pretty well documented. Cloud offers flexibility, adaptability, scalability, faster time to value, easier upgrades, more frequent updates, etc. Same for “any device”, it’s simply the way we work now. 
  • The Internet of Things (IoT) is interesting and does offer opportunity for business (and for the hardware tech vendors), but from a software perspective IoT is another data source. It will provide some extremely useful data and allow for more automation and better decisions, so I will weave it into the discussions on data in each of the areas.
  • The overall impediments to leveraging data to it’s fullest are really around two issues, making sense of the volume of data (making it smart / adding context) and getting the complete data set across the existing organizational and application silos that exist in all businesses. The issues of context and of overcoming silos are so important that they will likely be discussed in the context of each individual area, but really need to be addressed in a broader way by every business.

So with those assumptions, the logical starting point is with cloud platforms or PaaS and the concept of the post application era. The way modern applications are developed is quite a bit different from the older monolithic code base applications. With the widespread use of services oriented architecture (SOA), isolated services, and APIs in loosely coupled systems, modern application development has evolved down a path toward a microservices methodology and what is known as reactive systems. (for a good discussion on microservices read this). As software as a service (SaaS) replaces old monolithic systems, the need for the older application packaging becomes irrelevant. The new reactive systems are a lose coupling of microservices based on a business process not a collection of monolithic application blocks that can be integrated into a “suite”. Modern systems are an assemblage of microservices that execute a business process, that can be continuously integrated and updated much more easily. Reactive systems are more scalable, flexible, fault tolerant, and adaptable. As the microservices get more granular it becomes easier to assemble them more dynamically using the new platforms / PaaS into best fit processes. Today these microservices are preconfigured by software companies into processes, but it’s easy to see a future where these services could be custom configured based on each companies need, and offered in marketplaces that would test, certify and assemble them into reusable modules of services. We’re not there yet of course, but the first iteration of these marketplaces for APIs and custom configured / assembled modules or components already exist, Salesforce’s AppExchange Marketplace for example. This modern approach to services and business processes leads to what we have called the post-application era, where the old functional packaging of apps is not necessary or even desired, and where eventually the services can be configured into an individualized business process for each company.

Microservices are part of this picture, but the platform, or more correctly the platform as a service (PaaS) is the other part. There are many PaaS offerings available and they are evolving in functionality quite rapidly. There are a set of functions and features that make up the basic PaaS offering, that includes:

  • Services / Application API, flexible integration support for all current web standard integration technologies
  • Granular control over security / access / identity (standards based)
  • Web services broker
  • Shared resources
  • Customizable/programmable user interface (UI) - support for browser, web services and any device deployment
  • Workflow engine
  • Tools for creation, configuration and deployment of persistent objects
  • Container management
  • Application / services management
  • Embedded services: storage, analytics, collaboration
  • Autoscaling
  • Monitoring, logging, metering
  • Self provisioning

While not a feature, the PaaS should also be a part of an ecosystem that is supported by a marketplace of additional services including APIs and applications built on the platform. Often the services are built by other 3rd parties, but the marketplace owner provides the “certification” for anything delivered through the marketplace.

What you can do now: This varies quite a bit based on your current maturity level with SaaS of course, but PaaS providers are offering platforms that are relatively mature and can be used now for integrations, extensions of currently deployed SaaS applications and for the development of custom applications / services. In general, start with the data and work out to the problem you’re trying to solve in developing a list of requirements for both the platform and the resulting solution. From an integration use case the PaaS you choose should be able to support cloud to cloud and cloud to on premises integration needs. If your needs are related to extending / customizing existing SaaS deployments your selection of platforms may be limited to the associated vendor’s offering, although not always. In selecting new SaaS solutions it is essential to evaluate the associated platform to ensure that it will support your customization and integration needs, or to have an existing PaaS that will accommodate your needs. More and more companies are working off the base applications and adding custom extensions and solutions to address adjacent business processes. 

In part two of the series I’ll take a look at CX and the associated technologies that are helping companies build and deliver on a more comprehensive CX strategy.

This originally appeared on the Michael Fauscette blog

Some Non-Predictions for 2015

  • Partner: IDC Business Software Group
Mike Fauscette, Chief Research Officer, G2 Crowd
Mike Fauscette
Chief Research Officer
G2 Crowd

IDCThank you to IDC for underwriting CXOTALK.

It’s that time of new year when you get deluged with analysts / bloggers predictions and prognostications. I join in most years, and of course there’s the IDC predictions process to contend with as well. This year I swore that I was skipping it. I’ve already done the new IDC “Futurescape” document and webcast with my colleague Vanessa Thompson on social technologies, and I suppose that should be enough…but, the pull is strong… alright, no predictions, in fact how about some non-predictions? Actually this post is really more of a state of the industry, a summary of some random thoughts that I’ve been mulling over for the past few weeks. Maybe I should have called it random thoughts on software, business and digital transformation, but it already has a name so here you go, in no particular order: 1. Customer experience (CX) strategies are more important than ever. As tired as this topic may seem to many of you, this is still one of the top initiatives for most companies today and an area where companies are struggling. There is a lot of budget being spent, the results are mixed, many customers are not seeing results but some companies are winning big by "getting it right". Providing a good CX across all channels is just hard, face it.  There are many issues here that still need to be resolved for most companies. these include data silos (and these silos are increasing in many companies, you must get a complete view of the customer including transactions, social data and consensual data from communities, etc.), system silos (and again, these are getting worse as companies / departments add disconnected solutions to try and address pieces of the strategy), poor workforce management, poor difinitinos of "customer facing" organizations, outdated business processes (including sales, marketing and service of course, but also logistics, product planning, finance, etc.), lack of executive support for initiatives, and probably a dozen other things I'm forgetting. I'm not going to try and provide a map to successfully building a CX strategy in this post, it would be 500+ pages long, but I will say that building and executing a flexible, adaptable and comprehensive CX strategy is critical. 2. The nature of getting work done is changing.  We have done several workforce transition threads this past year, and I'd say this is an area that is heating up quite a bit as we learn more about the changes that are impacting how work gets done and how companies can increase productivity. There are a lot of dimensions here that range from new tools and processes to behaviors and dealing with change. The use of networks is a key technology and can help facilitate behavioral changes but that's not enough. I've written before about the productivity gap and how social technologies and new platforms can help close it in the future, so I won't go back through that discussion here, but it is still very relevant. There's also a whole thread around sourcing - hiring - training - retaining the modern workforce that is connected to social technologies and better employee experiences. There are underlying changes happening to the employee - employer relationship, with more outsourced or consultative engagements becoming the norm. Internet and project technologies have also opened up the ability to break processes into micro tasks and distribute the work differently and in a flexible model which will impact the type of work many employees will do in the future (see the comments on business networks later in the post).

I read something the other day (sorry, don't remember the source) about moving beyond knowledge work. The concept was that it's not about knowledge anymore but instead about your ability to learn new things. I get the concept but to me it is really misguided and naive to think that from a worker perspective it's only about your ability to learn and not about your knowledge, experience and skills. The modern worker, or knowledge worker (KW) has to be adaptable, no doubt, but the biggest shift is in the activities themselves. The KW applies experience and knowledge to business decision making using new collaborative tools, data / analytics and increasingly technology assistive technology like cognitive computing and artificial intelligence (AI). The ability to synthesize inputs (data, predictive analytics, prescriptive analytics, cognitive assistance and AI) into business decisions and strategies to drive better outcomes is the new nature of work IMO.

I am for the moment ignoring robotification (but if you're interested this Wired post is a pretty good primer), that would most definitely get into the land of predictions and well...

3. Commerce is moving beyond channels and silos and will converge into a more seamless experience.  Consumers are growing very tired of the segregation of channels that many businesses seem to have accepted as normal. Around the edges this is eroding though, as more companies start to think of the complete experience and not segregated on and offline. If I want to shop in a physical store but order off my mobile device for home delivery all in one experience shouldn't that be an acceptable model? And the reverse is also true, I want to research and shop online but pickup and inspect in a physical location. Add to that the new beacon technologies that can put context and identity into the experience and the convergence should accelerate and include loyalty, promotions, community, etc. Since I just posted on digital wallets, I'll leave that off here for now.

4. The modern business is becoming a network of connected entities.   Yes, I've talked about business networks for a few years now, but finally the concept is getting a lot of attention and I think we clearly now see where current businesses are being successful in transitioning. There are three areas business networks are adding significant value to businesses today, 1. CX / Communities. 2. Enterprise Social Networks (ESN), and  3. Commerce / Marketplaces.  Customer communities have become a key part of many CX strategies and play an important role in collecting and integrating the voice of the customer into a business and it's innovation process. ESN's are the backbone of the new collaborative workforce and are becoming a part of the business processes of many companies. They also provide an important conduit for getting people and data together to drive better business decisions / outcomes. The marketplace model is an importnat part of the current business model innovation trend. The oldest part of business networks fall here, the supplier network (i.e. Ariba) and marketplaces like eBay and Amazon, but we're seeing this model explode across many different markets in the past few years. Capital markets have moved into the marketplace model with crowdfunding sites like KickStarted and Indiegogo. What was perhaps inaccurately called the "sharing economy" also leverages the marketplace model with companies like Airbnb and Uber leading the way (we should probably call this the rental economy as we all see that it's not about sharing but about creating value). The marketplace model is also redefining how companies can get access to critical data sources that will feed decision systems across a broad range of business functions including marketing, sales, service, product design, etc. in what are being called data clouds or data as a service (DaaS).

5. Cloud is simply the way businesses consume new technologies and forms the foundation of the new business platform. In other words it's not a new edge technology but simply the way that modern applications (services), platforms and utility computing services (like storage, data, security, etc.) are consumed. Companies are increasingly accepting and utilizing the cloud for IT modernization and busniess competitive advantage. Cloud platforms have huge potential, especially when combined with the concept of micro services, to disrupt the application landscape and become the new source of value for delivering business processes to the enterprise.

6. Stop talking about mobile as if it's a new / different way of working. I don't want to hear "mobile first" strategies anymore, it's not about mobile, it's about working anywhere with whatever device I have handy. Tech vendors can't dictate the end point technology anymore, the user does. Instead make the technology just work no matter what device I happen to use! 

7. The world's a scary place and online is no exception. 2014 was the year that we all saw hacking and security as a threat to everyone who has a connected device. Personally I had to change debit cards three times due to hacking and even had one credit card somehow dublicated physically. There are scary places with little or no regulation where hackers are multiplying and adapting as quickly as security companies can deploy new / better system security. And worse than that, many companies still have huge holes in security that they are ignoring. We've even gone beyond private hacking and are now entering (well, really now aware of) the time of cyber warfare and state sponsored cyber terrorism.  

 8. Privacy is not an outdated concept but both your concept of privacy and the way we provide privacy protection have to change.  In a world where technology changes in an almost continuous cycle we have to adapt our concept and methods to provide an acceptable level of privacy to everyone. That doesn't mean that the base definition of privacy might change, I'd argue that it already is/has. What it does mean though is that governments and businesses have to adapt to the technology changes by making regulation and policies that meet theose technology changes. In other words the rules need to keep up with the technology, not the other way around. This is a serious problem when the people making the rules are not tech savvy in any way, and make no effort to understand the technology (I'm referring to the US Congress and Judiciary, but I'm sure it applies in other countries as well).

9. Data silos are the enemy of the modern business. Okay, I know this seems obvious, but is it. I recently had a conversation with a friend at a large financial institution who had been tasked with providing a consolidated view of the institutions customers. Now you'd think that this person would be in IT, or at least have IT support for this project (you might also be surprised that in 2015 we're talking about starting to build a complete customer data model, but that's just the reality of most businesses) but that was not the case. Line of business (LOB) tasks with building a plan to consolidate data across multiple systems in even the most rudimentary way is a serious challenge but more and more, it's the reality that many businesses face. No matter who is tasked to solve the problem, we have a serious problem in most businesses with customer, employee, product / service data. And in many companies LOB is adding new cloud based systems to try and solve other operational problems, but adding new system silos just makes the data silo problem worse. Big data, smart data, small data, predictive and prescriptive analysis and just basic business decision making depends on complete data pictures so if you can't bridge the silos, all of the other benefits are unavailable. 10. Net neutrality is a fight we must continue to pursue. I get very frustrated over this subject and I did already write a fairly long post on it last year so I guess I won't go back into my rant here. Still I have to say, we cannot ignore this topic, there are too many large, well funded threats to the free and open Internet today to let it fall off our radar.

So that's my non-predictions for 2015, what do you think? Feel free to add more in the comments. Oh, and Happy New Year!

This originally appeared on the Michael Fauscette blog

Transforming Data into Action: Part Three

  • Partner: IDC Business Software Group
Mike Fauscette, Chief Research Officer, G2 Crowd
Mike Fauscette
Chief Research Officer
G2 Crowd

IDCThank you to IDC for underwriting CXOTALK.

In part three of the series we will focus on sources of data beyond in-house transaction data and data collected from social listening, and the impact of the Internet and Cloud Computing on both the distribution of data and the business models that are evolving around that data. Data brokers, that is, companies that aggregate and sell personal data are not a new concept. Companies like Dun & Bradstreet, Experion, Equifax and others have packaged and sold data for business use for many years. These data brokers sold data used for all sorts of marketing compaign from snail mail to email. While this data helped with segmentation it had many limitations, and in an environment where people are always connected and expect real time interaction, the data is just to static and outdated. With the addition of Internet advertising and now social networks and social media as advertising channels the need for data is even higher, but that data cannot be stale and static or it is in effect useless.

The Internet is creating new opportunities in the collection / aggregation and distribution of data. As more business functions look to move to a data driven model, there is a need for many new data types, and for a more rapid way to distribute that data. In other words, the need is growing in business and the Internet is creating the vehicle for meeting that growing need. Marketing is a big consumer of data, but outside that sales, customer service and even product / service development is becoming more data focused. We've already seen that big data, or more specifically smart data can be valuable but only when enough relevant data can be found to create accurate models. Small data, or distributed data sets are also impacted by the need for more relevant data to feed the process and extend the completeness of the data sets.  Data brokers then, can step in to help make the model more complete, but to meet the new business demands, have to become "cloud" enabled.

A new group of data brokers, or maybe more accurately value added content providers are emerging to fill this gap. The new broker uses the Internet and cloud computing to create data marketplaces that can be more time relevant and can provide massive quantities of contextual information / content. In fact this new business model, data as a service (DaaS) could be an opportunity for existing social networks, Internet businesses and other entrants to step in and fill the need. Twitter is already monitizing it's "fire hose" data feed and recently acquied Gnip, a data marketplace. Companies like Uber (although under fire a bit for it's data handling practices currently) or Airbnb, who hold quite a bit of useful data could get into the game int he future. Software vendors like Oracle (Data Cloud product), Microsoft (Azure Data Marketplace), and IBM (Watson Content Store) are growing very competitive offerings. Social media monitoring vendors like Attensity are competing with their own marketplace and Gnip competitors like Datasift are in the game as well. As you can see the business of value added content is exploding with data aggregators, original content publishers, search engines and other brokers all coming at the data problem from different angles.

This new and rapidly growing area is still in it's infancy but is providing a lot of value to the business consumers of data by providing a very robust data set and in a model that is generally offered as a service (subscription) and in a much more timely and contextual Internet delivered model. The next few years will see many more of these services developed as other holes in enterprise data sets will need to be solved. There are still a lot of issues of course, as with any business model that is growing rapidly. Growing pains around privacy, data governance, security and probably a few things we haven't even thought of yet, will need to be addressed quickly to prevent public backlash. I expect that governments will get even more interested in the subject as well, although both the US Government and the EU have already started down that path. It's an interesting area, and one that has a lot of potential to add value as companies struggle to turn data into actionalble strategies and tactics.

This originally appeared on the Michael Fauscette blog

Transforming Data into Action: Part Two

  • Partner: IDC Business Software Group
Mike Fauscette, Chief Research Officer, G2 Crowd
Mike Fauscette
Chief Research Officer
G2 Crowd

IDCThank you to IDC for underwriting CXOTALK.

In part one of this series we looked at big data and transforming it into smart data, or data that is contextual, relevant and delivered to the right people / person at the right time. One of the other interesting and growing use cases in the business use of data is something called small data. In this post we'll take a look at small data and what a business might do to leverage it effectively.

What exactly is small data? That's not the easiest question to answer actually, as there are angles to the definition that add some complexity. The simplest definition is that small data is a data set that can fit on a local / individual computer or device. But data set size doesn't quite get to the heart of it. There are a couple of other dimensions to the concept of small data. One is the process of taking large data sets and distributing them out to nodes that can use them on local devices for some business a distributed computing model of data processing or democratizing information. That really is turning the data into actionable insights derived from big / smart data and / or local data, maybe as a mash up of several sources, and most likely visualized in some way. Small data is also timely, relevant, organized and packaged to support routine decision processes, which sounds a lot like smart data, but is somewhat different because of the other factors mentioned above. I suppose you could think small data as a localized subset of smart data.

So why is small data so interesting? First the concept or approach itself provides the widest distribution of data, putting the potential of data driven decisions in many more hands. Big data is the purview of a few with high power computing resources, small data is the distributed model that creates many opportunities. Besides the fundamental difference though, there are some other important opportunities presented with small data:

  • One of the biggest opportunities for changing business today is by shifting to a data driven decision model. This may sound obvious but in reality it's just hard. Getting the "right" data to the "right" person or people at the "right" time and work context is a critical function. The nature of the small data approach seems to more fully support this process with it's distributed versus  centralized models fueling collaboration over control. Getting the data out of the hands of the data scientists / analysts and into the hands of the front line employees directly supports this data driven decision model.
  • Data driven customer experience (CX) has great potential to support modern CX strategies and help companies deliver experiences that are more likely to meet customer expectations. Meeting expectations in a repeatable and reasonably accurate process is only possible with a deeper understanding of your prospect / customer. There are many data sources that could help build out this robust model and many of them are small, local, personal and social. The mash up of social data with transactional data and web analytics can build out very rich profiles that can be used to understand expectations and predict outcomes. Marketing, sales, customer service and product/service design and development all need small data to transform the customer experience across a wide variety of processes.
  • Big data can seem daunting for many companies, I mean, just the name sounds scary. The resources needed to deal with data in the big form is also daunting. The issue though, is that for many use cases the value is at the other end of the process, that is, in the hands of the employees who need to execute a process, make a decision, deal with an exception, etc. not with the "big" resources. So there is a need to simplifying the data process, and distribute insight, not big data. The small data approach helps close the gap from the big to the actionable.
  • Healthcare and wearables is another example of the value of small data. The current trend for smart devices to help with fitness and weight loss is only the beginning of the health wearable opportunity. The wearable can revolutionaize diagnostics by providing small data to help doctors and cognitive systems understand and treat a variety of diseases and conditions.

Big data in itself doesn't solve problems (some might even argue that it causes some problems, especially in storage and compute resources). We saw in post one that smart data is the real opportunity to make data actionable, or at least a part of the opportunity.  Making better business decisions is really about people with the right data in the right context taking some action. The democratisation of storing, processing and finding data is a powerful way to support this new decision process. ESN's can form the backbone for the distribution of data and the connecting of people. This new data rich ecosystem is the support structure for the sense and respond business model and is built on the distributed data concept, or small data, that brings the actionable, contextual insight to the right people when it's needed.

In post three I will look specifically at data sources, data marketplaces and the emerging data as a service business.

This originally appeared on the Michael Fauscette blog

Transforming Data Into Action: Part One

  • Partner: IDC Business Software Group
Mike Fauscette, Chief Research Officer, G2 Crowd
Mike Fauscette
Chief Research Officer
G2 Crowd

IDCThank you to IDC for underwriting CXOTALK.

Everywhere you look in tech today you'll read / hear about big data and all the many uses businesses could get from it. Businesses do certainly need to become more data driven and in fact the business model for the Information Age is something we've referred to as "sense and respond". Moving from the old "make - sell" business model to the new sense and respond model requires data across all your business functions. On the other end of that requirement we're creating massive amounts of data every second so you'd think that it would be a simple matter to implement the sense and respond model. The problem though. is that having lot's of data and needing lot's of data leaves out an important part of this equation...the process of turning mountains of data into actionable information is just not simple. 

I've written about smart data before (here), and I still think this is an important part of the key to unlocking the value of the ever growing mountain of data. I've started to think though, that there is still something missing from the picture when you think about, and implement ways to use the data to run your business. Part of this relates to the way the big data problem is being addressed and part of it is, I think, using the wrong approach for some of the problems that we need the data to solve.

Big data, when in the big data /non-smart form, is useless, or even more than useless because it can distract businesses and consume a lot of resources for no value return. The problem with the approach, I think, is that big data is the kind of problem technology loves to solve in "big" ways. It needs big resources like really fast servers and multiple kinds of databases and memory and data scientists and analytics engines, not to mention centralized control. Big data is in many ways, the holy grail of IT problems to solve, one that puts lot's of budget and control right in the IT organization. Now don't get me wrong here, there are some major, amazing things that can be done with the data, once it's turned from it's big state to the smart state. Smart data is data in context, in the "right hands" and relevant to some issues, activity, problem, etc. Once the data is transformed and processed and delivered to the right person / people in the business that need it to do something of value, it can be an important part of the sense and respond model. Just know that the process of transformation is not so easy or cheap. In the end, if it delivers the right return, or value to the business then great. Smart data is broad though, shows trends and benchmarks and at best can move from reactive to predictive given the right models and context. In other words, it is generally applied broadly, not individually. Here are a few examples of using smart data to return huge business value:

  • Banking payment fraud detection and investigation
  • Public sector assigning law enforcement based on predicting where / when crimes are likely to happen
  • Retail optimizing merchandise placement in stores
  • Asset intensive industries monitor and analyze real time machine sensor data to predict and correct failures before they happen
  • Insurance claims fraud detection
  • Retail making purchase suggestions based on previous transactions and macro buying trends (although that has issues, see the next paragraph)
  • Healthcare evidence based medicine

Smart data though, doesn't provide all the insight that the business needs. Some of the functions are actually tied to individual insight. Part of the beauty of the new world is the capability to be specific and individual. This is very important in marketing, sales, service, and HR, where individualization is a key part of the experiences strategy. Unfortunately many businesses continue to personalize, not individualize. This is the part that many businesses struggle with the most right now. Just think of marketing for example. Most / many of you probably do business with Amazon. I do, and in fact do quite a lot of business with Amazon. Now because of that, I expect Amazon to know my buying habits, interests and some of my needs fairly well. The problem is, they don't, which is interesting because they get high praise over their personalization system. They're applying personalization data to a problem that needs more individualization. The special offers, recommendation, etc. that pop up online and show up in my inbox are ridiculously wrong 99% of the time. Why? Well, first let me say I don't have any inside knowledge of the Amazon commerce and CRM systems so I may be off base with this analysis, but I suspect that I will be close to the issue. The problem is that Amazon is using my personal transaction data in conjunction with other smart trend data to build the recommendation and offers. They are looking at the micro experience and rationalizing it to the macro level. Other people "who did this will do that" type of analysis. It's a reasonable approach but unfortunately, at least in this case, it does not provide the level of individualization that is desired. It is tied to extrapolation of my specific transactions / behaviors into a broad population model of "popular" or the "everyman" average. Now that probably works for commodities like say toothpaste, I'm looking for toothpaste I might be likely to appreciate the "popular" brand recommendation. It does not work on higher end goods though. This is especially true when brand identity plays heavily into the decision.

This idea of mass profiling is interesting, but it has to move beyond the personalization paradigm and stop classifying you into a segment. Segmentation is very popular but is an old concept that misses the mark in a world where my expectation is individualized. It actually is missing the missing the level of relevance that I expect now. With the growth of social web there's a lot more individual data available and in many cases you have permission to use it. Socialytics is rapidly growing and providing some interesting tools to pull out that individual data. On the other side though, it's not necessarily getting mapped into the transaction data and other "big data" that would provide a complete picture of my actions and beyond actions, into my behavior and wants / desires.  The capability to move beyond personalization and into individualization is critical for building out experiences that meet expectations.

In the next post, I will look at a newish concept called small data. I think that perhaps the big data movement distracts us in some ways from what might be a much bigger revolution around mass democratization of data access and processing. Building out an ecosystem of data and people, or expanding the definition of the enterprise social network (ESN), may be the biggest win for companies.

This originally appeared on the Michael Fauscette blog

Cloud Software and Business Modernization Part Two: Customer Experience

  • Partner: IDC Business Software Group
Mike Fauscette, Chief Research Officer, G2 Crowd
Mike Fauscette
Chief Research Officer
G2 Crowd

IDCThank you to IDC for underwriting CXOTALK.

Building and executing on a customer experience (CX) strategy is one of the most pressing areas of business modernization. The Internet has created new interaction models and channels, as well as created an expectation of immediacy. Companies are struggling to keep up with the expectations and new interaction models. The explosion of new and changing communication channels and methods adds to the complexity and makes consistent response to customers challenging. 

It's not all negative though, there are a lot of interesting opportunities for businesses that sort out these changes quickly and can become a source of competitive advantage. When surveyed businesses report that consistency of message is one of the biggest challenges. The only way to get to consistency is to operate in a way that creates enough transparency and connectedness that employees can see and understand what is being and has been said to a customer. This is vey different from the silo'ed and hierarchical approach that most businesses use today. In that sense the business modernization efforts in CX are interrelated to many of the other areas, particularly workforce transformation. 
I’ve written about CX quite a bit over the past few years, here are a few of those posts and presentations (strategy, data and CX, CX and transformation, customer service, collaboration and CX - only a small sample) for reference. In building a comprehensive CX strategy I think it’s critical to start with the data and then work through people, process and technology. That will probably be common advice through the whole series, but with CX, it really is the foundation for the strategy. So what are the most common data issues? Here are  a few:

  • Data is silo’ed / not integrated. This can be the result of applications that are not integrated, particularly in organizations where the business units have purchased specialty systems as point solutions to business issues. Not that this isn’t an understandable situation, it’s just that integration is a critical part of system management and often can’t be done without the participation of the IT organization. 
  • Incomplete data
  • Data quality
  • Customer identity

Data sources:

  • Listening tools
  • Transaction systems
  • Engagement or interaction systems
  • Mobile applications / devices
  • Customer community
  • Data clouds / external providers

What to do to address data issues:

  • Comprehensive integration approach
  • SMM tools
  • Purchase data to complete picture
  • Engage IT

Once you have worked through the data issues it’s useful to do an exercise that I’ve called CX modeling. This is a modification to the traditional customer journey mapping exercise that many marketing organizations have undertaken. The key difference is in identifying both the potential interaction points and triggers and the potential engagement actions that might drive the intended outcomes. For more on this process you can refer to this post (part series). In post two of that series I talked about building the model, I'll repost that here since it's extremely relevant to this conversation.

Generally building the model uses this process:

  1. Define stakeholders

  2. Define data sources (really critical to make the model data driven. Collecting as much social and transaction data about your customers to use a basis for the model is critical)

  3. Data collection

  4. Data analysis

  5. Output / fill in detail tactics in the matrix

  6. Continuous feedback and refinement

One of the biggest pitfalls of mapping or modeling exercises is the porblem of projecting. We all have the tendency to project our own understanding or bias onto any analysis. In may types of analysis this is very useful but in this particular instance it is problematic. You'll notice the model process is ripe with data steps and this is really the underpinning of and the key driver of a successful model. Basing the model on customer data or "fact" will minimize the problem of projecting and instead help the team to build the model from the customer perspective. The data leads you to identifying and understanding the customer behavior that will trigger a specific set of actions (or action choices) and hopefully drive outcomes that are favorable to your business.

The second type of silo that is a road block to successful CX strategies are organizational. Organizational silos create collaboration and communication issues for customers by restricting interaction between employees and partners. In other words employees (and partners) don't have the capability to see across all customer communications and interactions so they cannot help ensure consistency. Inconsistent communication and actions is one of the biggest problems reported by customers (and by companies building a CX strategy) according to the IDC CXIT survey conducted earlier this year. Breaking down organizational silos is cultural and administrative but can also be assisted by transparent collaboration tools like enterprise social networks (ESN). Collaboration needs to be baked into everything from management and executive messaging to pay and incentives.

The other big employee / partner barrier to effective CX strategies is training. All employees and partners need to be educated on the CX model (the appropriate parts for their specific role that is) and understand their role in executing on providing a good CX. Customer "facing" isn't just in sales, customer service and marketing but reaches throughout the company. One approach that can help reinforce that new CX role is bringing the voice of the customer into the ESN via the customer community. In fact the customer community can play several important roles in the execution of a comprehensive CX program, including:

  • Provide visibility for employees and partners into customer opinions, ideas (existing and new product and features), and issues
  • Provide a convenient place to introduce prospects where existing customers can share experiences and information (part of the prospect education process)
  • Help fill in missing customer profile data
  • Capture useful product / service content for reuse
  • Provide peer to peer support to improve CX and help existing company support processes
  • Provide direct marketing and product feedback

A CX strategy impacts a wide variety of business processes across the company. A part of building the strategy (and part of implementing the technology solutions that support it) is integrating processes across business functions. In particular the traditional "front office" processes like marketing, sales and support have to be tied into "back office" functions like finance, operations, product development, logistics, etc.

There are many technologies that can be a part of an effective CX strategy. Probably the most important technology is integrating systems across the company to eliminate data silos and communication silos. In addition companies can incorporate technologies like:

  • Community platform(s)
  • Social media monitoring and management
  • Integration / social network management with customer service systems
  • ESN
  • Social marketing automation
  • Sales intelligence and enablement tools to get contextual information to sales in real time
  • Learning and training for onboarding and ongoing employee education
  • Talent and performance management that includes CX defined role definitions, position descriptions, and competencies as well as collaboration and CX driven incentives
  • Embedded analytics tools, particularly enabling real time mobile analysis of a broad set of customer and company data
  • Mobile CX applications that provide a specific CX strategy defined set of customer capabilities (these mobile apps are very specific to each industry and individual business)

What can you do now? Well, there's no magic recipe for building out a complete strategy. The hardest thing is to get goals established that support the effort of building a strategy that is far reaching enough to really make a difference. If you have organizational support for the effort it will take (no small task, but absolutely essential) then there are a few obvious places to start:

  1. Do an overall and quick assessment to determine any critical failure areas taht could dramatically improve CX in the short term while building and implementing a more comprehensive strategy (which needs to be, and most likely would have to be rolled out in phases over time). These quick fixes might be communication channels, support focused, implementing a customer community and peer to peer support process, using an ESN to "integrate" people and/or data across current silos, etc.
  2. Usually the best place to start the more strategic CX process is to focus on a few types of data: a. complete customer profile and data model, b. collecting "as is" data to use as a baseline for defining the improvements including current processes, customer satisfaction (or dissatisfaction), c. employee and partner satisfaction data, d. business and market benchmarks
  3. Analyze collected data and build a team and plan to use that data as the foundation of the CX strategy. The team must be cross-organizational and cross-functional. 

From these three "simple" steps (which honestly will take quite a bit of effort and time), you will have a plan to start executing. I won't go through all the project management how-to's, that's not the point of this post, but suffice it to say that this is a big, and important project that deserves the support (people, capital, technology, etc.) and formal project process that will ensure its success. In post three I'll look at commerce.

This originally appeared on the Michael Fauscette blog

Mike Fauscette, Group VP, IDC

  • Episode: 14
  • |
  • Partner: IDC Business Software Group
Mike Fauscette, Chief Research Officer, G2 Crowd
Mike Fauscette
Chief Research Officer
G2 Crowd

Mike Fauscette is the leader of IDC’s Software Business Solutions Group which encompasses research and consulting in enterprise software applications including ERP, SCM, CRM, PLM, collaboration and social applications, software partner and alliance ecosystems, open source software, software vendor business models, SaaS and cloud computing, and software pricing and licensing.

Crawford Del Prete, Executive Vice President, IDC

  • Episode: 66
  • |
  • Partner: IDC Business Software Group
Crawford Del Prete, Executive Vice President, IDC
Crawford Del Prete
Executive Vice President

Crawford Del Prete, Executive Vice President, Worldwide Products and Chief Research Officer, manages IDC's WW research and consulting businesses.  This includes IDC's Enterprise Computing, Storage, Networking, Integration, Development and Application Software, Professional Services, Telecommunications, Personal Computing, Mobility, Consumer, Digital Marketplace, SMB, Vertical Markets, Consulting and WW Tracker research practices. Mr. Del Prete is also responsible for IDC's Industry Insights Companies, which specifically target the needs of end users in six vertical segments.  Mr. Del Prete serves on the operating review boards of PC World and Macworld.

Mr. Del Prete is a leading authority on the IT industry and has completed extensive research on the structure and evolution of the information technology industry. In 2001, Mr. Del Prete forged IDC's partnership with Innosight, the consultancy founded by Harvard Business School Professor Clayton Christensen. Together, the companies have created a body of work to understand and predict trends in disruptive innovation. Mr. Del Prete also serves as IDC's lead analyst covering Hewlett Packard.

Mr. Del Prete joined IDC in 1989. At that time he initiated coverage of the Winchester Disk Drive market, and was a founder of IDC's European and Asia Pacific storage research programs. In 1997, Mr. Del Prete founded IDC's coverage of the Semiconductor marketplace. In 1995, Mr. Del Prete was honored with IDC's James Peacock award for research excellence, IDC's highest honor. That same year he was voted "most valuable" storage analyst by an outside panel of his peers from the International Disk Equipment Manufacturers Association. Mr. Del Prete is a member of the United States Computer History Museum Storage Committee.

Prior to IDC, Mr. Del Prete worked in marketing at Installed Technology International. Before this, he was with Paine Webber Jackson and Curtis in New York in the government securities and commercial lending sectors. Mr. Del Prete holds a B.A. from Michigan State University and in 2012 was named a Distinguished Alumni of the University, the highest award given to graduates.