Category Archives: Data management

The Open Group Panel: Internet of Things – Opportunities and Obstacles

Below is the transcript of The Open Group podcast exploring the challenges and ramifications of the Internet of Things, as machines and sensors collect vast amounts of data.

Listen to the podcast.

Dana Gardner: Hello, and welcome to a special BriefingsDirect thought leadership interview series coming to you in conjunction with recent The Open Group Boston 2014 on July 21 in Boston.

Dana Gardner I’m Dana Gardner, principal analyst at Interarbor Solutions, and I’ll be your host and moderator throughout these discussions on Open Platform 3.0 and Boundaryless Information Flow.

We’re going to now specifically delve into the Internet of Things with a panel of experts. The conference has examined how Open Platform 3.0™ leverages the combined impacts of cloud, big data, mobile, and social. But to each of these now we can add a new cresting wave of complexity and scale as we consider the rapid explosion of new devices, sensors, and myriad endpoints that will be connected using internet protocols, standards and architectural frameworks.

This means more data, more cloud connectivity and management, and an additional tier of “things” that are going to be part of the mobile edge — and extending that mobile edge ever deeper into even our own bodies.

When we think about inputs to these social networks — that’s going to increase as well. Not only will people be tweeting, your device could be very well tweet, too — using social networks to communicate. Perhaps your toaster will soon be sending you a tweet about your English muffins being ready each morning.

The Internet of Things is more than the “things” – it means a higher order of software platforms. For example, if we are going to operate data centers with new dexterity thanks to software-definited networking (SDN) and storage (SDS) — indeed the entire data center being software-defined (SDDC) — then why not a software-defined automobile, or factory floor, or hospital operating room — or even a software-defined city block or neighborhood?

And so how does this all actually work? Does it easily spin out of control? Or does it remain under proper management and governance? Do we have unknown unknowns about what to expect with this new level of complexity, scale, and volume of input devices?

Will architectures arise that support the numbers involved, interoperability, and provide governance for the Internet of Things — rather than just letting each type of device do its own thing?

To help answer some of these questions, The Open Group assembled a distinguished panel to explore the practical implications and limits of the Internet of Things. So please join me in welcoming Said Tabet, Chief Technology Officer for Governance, Risk and Compliance Strategy at EMC, and a primary representative to the Industrial Internet Consortium; Penelope Gordon, Emerging Technology Strategist at 1Plug Corporation; Jean-Francois Barsoum, Senior Managing Consultant for Smarter Cities, Water and Transportation at IBM, and Dave Lounsbury, Chief Technical Officer at The Open Group.

Jean-Francois, we have heard about this notion of “cities as platforms,” and I think the public sector might offer us some opportunity to look at what is going to happen with the Internet of Things, and then extrapolate from that to understand what might happen in the private sector.

Hypothetically, the public sector has a lot to gain. It doesn’t have to go through the same confines of a commercial market development, profit motive, and that sort of thing. Tell us a little bit about what the opportunity is in the public sector for smart cities.

Barsoum_Jean-FrancoisJean-Francois Barsoum: It’s immense. The first thing I want to do is link to something that Marshall Van Alstyne (Professor at Boston University and Researcher at MIT) had talked about, because I was thinking about his way of approaching platforms and thinking about how cities represent an example of that.

You don’t have customers; you have citizens. Cities are starting to see themselves as platforms, as ways to communicate with their customers, their citizens, to get information from them and to communicate back to them. But the complexity with cities is that as a good a platform as they could be, they’re relatively rigid. They’re legislated into existence and what they’re responsible for is written into law. It’s not really a market.

Chris Harding (Forum Director of The Open Group Open Platform 3.0) earlier mentioned, for example, water and traffic management. Cities could benefit greatly by managing traffic a lot better.

Part of the issue is that you might have a state or provincial government that looks after highways. You might have the central part of the city that looks after arterial networks. You might have a borough that would look after residential streets, and these different platforms end up not talking to each other.

They gather their own data. They put in their own widgets to collect information that concerns them, but do not necessarily share with their neighbor. One of the conditions that Marshall said would favor the emergence of a platform had to do with how much overlap there would be in your constituents and your customers. In this case, there’s perfect overlap. It’s the same citizen, but they have to carry an Android and an iPhone, despite the fact it is not the best way of dealing with the situation.

The complexities are proportional to the amount of benefit you could get if you could solve them.

Gardner: So more interoperability issues?

Barsoum: Yes.

More hurdles

Gardner: More hurdles, and when you say commensurate, you’re saying that the opportunity is huge, but the hurdles are huge and we’re not quite sure how this is going to unfold.

Barsoum: That’s right.

Gardner: Let’s go to an area where the opportunity outstrips the challenge, manufacturing. Said, what is the opportunity for the software-defined factory floor for recognizing huge efficiencies and applying algorithmic benefits to how management occurs across domains of supply-chain, distribution, and logistics. It seems to me that this is a no-brainer. It’s such an opportunity that the solution must be found.

Tabet_SaidSaid Tabet: When it comes to manufacturing, the opportunities are probably much bigger. It’s where we can see a lot of progress that has already been done and still work is going on. There are two ways to look at it.

One is the internal side of it, where you have improvements of business processes. For example, similar to what Jean-Francois said, in a lot of the larger companies that have factories all around the world, you’ll see such improvements on a factory base level. You still have those silos at that level.

Now with this new technology, with this connectedness, those improvements are going to be made across factories, and there’s a learning aspect to it in terms of trying to manage that data. In fact, they do a better job. We still have to deal with interoperability, of course, and additional issues that could be jurisdictional, etc.

However, there is that learning that allows them to improve their processes across factories. Maintenance is one of them, as well as creating new products, and connecting better with their customers. We can see a lot of examples in the marketplace. I won’t mention names, but there are lots of them out there with the large manufacturers.

Gardner: We’ve had just-in-time manufacturing and lean processes for quite some time, trying to compress the supply chain and distribution networks, but these haven’t necessarily been done through public networks, the internet, or standardized approaches.

But if we’re to benefit, we’re going to need to be able to be platform companies, not just product companies. How do you go from being a proprietary set of manufacturing protocols and approaches to this wider, standardized interoperability architecture?

Tabet: That’s a very good question, because now we’re talking about that connection to the customer. With the airline and the jet engine manufacturer, for example, when the plane lands and there has been some monitoring of the activity during the whole flight, at that moment, they’ll get that data made available. There could be improvements and maybe solutions available as soon as the plane lands.

Interoperability

That requires interoperability. It requires Platform 3.0 for example. If you don’t have open platforms, then you’ll deal with the same hurdles in terms of proprietary technologies and integration in a silo-based manner.

Gardner: Penelope, you’ve been writing about the obstacles to decision-making that might become apparent as big data becomes more prolific and people try to capture all the data about all the processes and analyze it. That’s a little bit of a departure from the way we’ve made decisions in organizations, public and private, in the past.

Of course, one of the bigger tenets of Internet of Things is all this great data that will be available to us from so many different points. Is there a conundrum of some sort? Is there an unknown obstacle for how we, as organizations and individuals, can deal with that data? Is this going to be chaos, or is this going to be all the promises many organizations have led us to believe around big data in the Internet of Things?

Gordon_PenelopePenelope Gordon: It’s something that has just been accelerated. This is not a new problem in terms of the decision-making styles not matching the inputs that are being provided into the decision-making process.

Former US President Bill Clinton was known for delaying making decisions. He’s a head-type decision-maker and so he would always want more data and more data. That just gets into a never-ending loop, because as people collect data for him, there is always more data that you can collect, particularly on the quantitative side. Whereas, if it is distilled down and presented very succinctly and then balanced with the qualitative, that allows intuition to come to fore, and you can make optimal decisions in that fashion.

Conversely, if you have someone who is a heart-type or gut-type decision-maker and you present them with a lot of data, their first response is to ignore the data. It’s just too much for them to take in. Then you end up completely going with whatever you feel is correct or whatever you have that instinct that it’s the correct decision. If you’re talking about strategic decisions, where you’re making a decision that’s going to influence your direction five years down the road, that could be a very wrong decision to make, a very expensive decision, and as you said, it could be chaos.

It just brings to mind to me Dr. Suess’s The Cat in the Hat with Thing One and Thing Two. So, as we talk about the Internet of Things, we need to keep in mind that we need to have some sort of structure that we are tying this back to and understanding what are we trying to do with these things.

Gardner: Openness is important, and governance is essential. Then, we can start moving toward higher-order business platform benefits. But, so far, our panel has been a little bit cynical. We’ve heard that the opportunity and the challenges are commensurate in the public sector and that in manufacturing we’re moving into a whole new area of interoperability, when we think about reaching out to customers and having a boundary that is managed between internal processes and external communications.

And we’ve heard that an overload of data could become a very serious problem and that we might not get benefits from big data through the Internet of Things, but perhaps even stumble and have less quality of decisions.

So Dave Lounsbury of The Open Group, will the same level of standardization work? Do we need a new type of standards approach, a different type of framework, or is this a natural path and course what we have done in the past?

Different level

Lounsbury_DaveDave Lounsbury: We need to look at the problem at a different level than we institutionally think about an interoperability problem. Internet of Things is riding two very powerful waves, one of which is Moore’s Law, that these sensors, actuators, and network get smaller and smaller. Now we can put Ethernet in a light switch right, a tag, or something like that.

Also, Metcalfe’s Law that says that the value of all this connectivity goes up with the square of the number of connected points, and that applies to both the connection of the things but more importantly the connection of the data.

The trouble is, as we have said, that there’s so much data here. The question is how do you manage it and how do you keep control over it so that you actually get business value from it. That’s going to require us to have this new concept of a platform to not only to aggregate, but to just connect the data, aggregate it, correlate it as you said, and present it in ways that people can make decisions however they want.

Also, because of the raw volume, we have to start thinking about machine agency. We have to think about the system actually making the routine decisions or giving advice to the humans who are actually doing it. Those are important parts of the solution beyond just a simple “How do we connect all the stuff together?”

Gardner: We might need a higher order of intelligence, now that we have reached this border of what we can do with our conventional approaches to data, information, and process.

Thinking about where this works best first in order to then understand where it might end up later, I was intrigued again this morning by Professor Van Alstyne. He mentioned that in healthcare, we should expect major battles, that there is a turf element to this, that the organization, entity or even commercial corporation that controls and manages certain types of information and access to that information might have some very serious platform benefits.

The openness element now is something to look at, and I’ll come back to the public sector. Is there a degree of openness that we could legislate or regulate to require enough control to prevent the next generation of lock-in, which might not be to a platform to access to data information and endpoints? Where is it in the public sector that we might look to a leadership position to establish needed openness and not just interoperability.

Barsoum: I’m not even sure where to start answering that question. To take healthcare as an example, I certainly didn’t write the bible on healthcare IT systems and if someone did write that, I think they really need to publish it quickly.

We have a single-payer system in Canada, and you would think that would be relatively easy to manage. There is one entity that manages paying the doctors, and everybody gets covered the same way. Therefore, the data should be easily shared among all the players and it should be easy for you to go from your doctor, to your oncologist, to whomever, and maybe to your pharmacy, so that everybody has access to this same information.

We don’t have that and we’re nowhere near having that. If I look to other areas in the public sector, areas where we’re beginning to solve the problem are ones where we face a crisis, and so we need to address that crisis rapidly.

Possibility of improvement

In the transportation infrastructure, we’re getting to that point where the infrastructure we have just doesn’t meet the needs. There’s a constraint in terms of money, and we can’t put much more money into the structure. Then, there are new technologies that are coming in. Chris had talked about driverless cars earlier. They’re essentially throwing a wrench into the works or may be offering the possibility of improvement.

On any given piece of infrastructure, you could fit twice as many driverless cars as cars with human drivers in them. Given that set of circumstances, the governments are going to find they have no choice but to share data in order to be able to manage those. Are there cases where we could go ahead of a crisis in order to manage it? I certainly hope so.

Gardner: How about allowing some of the natural forces of marketplaces, behavior, groups, maybe even chaos theory, where if sufficient openness is maintained there will be some kind of a pattern that will emerge? We need to let this go through its paces, but if we have artificial barriers, that might be thwarted or power could go to places that we would regret later.

Barsoum: I agree. People often focus on structure. So the governance doesn’t work. We should find some way to change the governance of transportation. London has done a very good job of that. They’ve created something called Transport for London that manages everything related to transportation. It doesn’t matter if it’s taxis, bicycles, pedestrians, boats, cargo trains, or whatever, they manage it.

You could do that, but it requires a lot of political effort. The other way to go about doing it is saying, “I’m not going to mess with the structures. I’m just going to require you to open and share all your data.” So, you’re creating a new environment where the governance, the structures, don’t really matter so much anymore. Everybody shares the same data.

Gardner: Said, to the private sector example of manufacturing, you still want to have a global fabric of manufacturing capabilities. This is requiring many partners to work in concert, but with a vast new amount of data and new potential for efficiency.

How do you expect that openness will emerge in the manufacturing sector? How will interoperability play when you don’t have to wait for legislation, but you do need to have cooperation and openness nonetheless?

Tabet: It comes back to the question you asked Dave about standards. I’ll just give you some examples. For example, in the automotive industry, there have been some activities in Europe around specific standards for communication.

The Europeans came to the US and started to have discussions, and the Japanese have interest, as well as the Chinese. That shows, because there is a common interest in creating these new models from a business standpoint, that these challenges they have to be dealt with together.

Managing complexity

When we talk about the amounts of data, what we call now big data, and what we are going to see in about five years or so, you can’t even imagine. How do we manage that complexity, which is multidimensional? We talked about this sort of platform and then further, that capability and the data that will be there. From that point of view, openness is the only way to go.

There’s no way that we can stay away from it and still be able to work in silos in that new environment. There are lots of things that we take for granted today. I invite some of you to go back and read articles from 10 years ago that try to predict the future in technology in the 21st century. Look at your smart phones. Adoption is there, because the business models are there, and we can see that progress moving forward.

Collaboration is a must, because it is a multidimensional level. It’s not just manufacturing like jet engines, car manufacturers, or agriculture, where you have very specific areas. They really they have to work with their customers and the customers of their customers.

Adoption is there, because the business models are there, and we can see that progress moving forward.

Gardner: Dave, I have a question for both you and Penelope. I’ve seen some instances where there has been a cooperative endeavor for accessing data, but then making it available as a service, whether it’s an API, a data set, access to a data library, or even analytics applications set. The Ocean Observatories Initiative is one example, where it has created a sensor network across the oceans and have created data that then they make available.

Do you think we expect to see an intermediary organization level that gets between the sensors and the consumers or even controllers of the processes? Is there’s a model inherent in that that we might look to — something like that cooperative data structure that in some ways creates structure and governance, but also allows for freedom? It’s sort of an entity that we don’t have yet in many organizations or many ecosystems and that needs to evolve.

Lounsbury: We’re already seeing that in the marketplace. If you look at the commercial and social Internet of Things area, we’re starting to see intermediaries or brokers cropping up that will connect the silo of my android ecosystem to the ecosystem of package tracking or something like that. There are dozens and dozens of these cropping up.

In fact, you now see APIs even into a silo of what you might consider a proprietary system and what people are doing is to to build a layer on top of those APIs that intermediate the data.

This is happening on a point-to-point basis now, but you can easily see the path forward. That’s going to expand to large amounts of data that people will share through a third party. I can see this being a whole new emerging market much as what Google did for search. You could see that happening for the Internet of Things.

Gardner: Penelope, do you have any thoughts about how that would work? Is there a mutually assured benefit that would allow people to want to participate and cooperate with that third entity? Should they have governance and rules about good practices, best practices for that intermediary organization? Any thoughts about how data can be managed in this sort of hierarchical model?

Nothing new

Gordon: First, I’ll contradict it a little bit. To me, a lot of this is nothing new, particularly coming from a marketing strategy perspective, with business intelligence (BI). Having various types of intermediaries, who are not only collecting the data, but then doing what we call data hygiene, synthesis, and even correlation of the data has been around for a long time.

It was an interesting, when I looked at recent listing of the big-data companies, that some notable companies were excluded from that list — companies like Nielsen. Nielsen’s been collecting data for a long time. Harte-Hanks is another one that collects a tremendous amount of information and sells that to companies.

That leads into the another part of it that I think there’s going to be. We’re seeing an increasing amount of opportunity that involves taking public sources of data and then providing synthesis on it. What remains to be seen is how much of the output of that is going to be provided for “free”, as opposed to “fee”. We’re going to see a lot more companies figuring out creative ways of extracting more value out of data and then charging directly for that, rather than using that as an indirect way of generating traffic.

Gardner: We’ve seen examples of how this has been in place. Does it scale and does the governance or lack of governance that might be in the market now sustain us through the transition into Platform 3.0 and the Internet of Things.

Gordon: That aspect is the lead-on part of “you get what you pay for”. If you’re using a free source of data, you don’t have any guarantee that it is from authoritative sources of data. Often, what we’re getting now is something somebody put it in a blog post, and then that will get referenced elsewhere, but there was nothing to go back to. It’s the shaky supply chain for data.

You need to think about the data supply and that is where the governance comes in. Having standards is going to increasingly become important, unless we really address a lot of the data illiteracy that we have. A lot of people do not understand how to analyze data.

One aspect of that is a lot of people expect that we have to do full population surveys, as opposed representative sampling to get much more accurate and much more cost-effective collection of data. That’s just one example, and we do need a lot more in governance and standards.

Gardner: What would you like to see changed most in order for the benefits and rewards of the Internet of Things to develop and overcome the drawbacks, the risks, the downside? What, in your opinion, would you like to see happen to make this a positive, rapid outcome? Let’s start with you Jean-Francois.

Barsoum: There are things that I have seen cities start to do now. There are couple of examples: Philadelphia is one and Barcelona does this too. Rather than do the typical request for proposal (RFP), where they say, “This is the kind of solution we’re looking for, and here are our parameters. Can l you tell us how much it is going to cost to build,” they come to you with the problem and they say, “Here is the problem I want to fix. Here are my priorities, and you’re at liberty to decide how best to fix the problem, but tell us how much that would cost.”

If you do that and you combine it with access to the public data that is available — if public sector opens up its data — you end up with a very powerful combination that liberates a lot of creativity. You can create a lot of new business models. We need to see much more of that. That’s where I would start.

More education

Tabet: I agree with Jean-Francois on that. What I’d like to add is that I think we need to push the relation a little further. We need more education, to your point earlier, around the data and the capabilities.

We need these platforms that we can leverage a little bit further with the analytics, with machine learning, and with all of these capabilities that are out there. We have to also remember, when we talk about the Internet of Things, it is things talking to each other.

So it is not human-machine communication. Machine-to-machine automation will be further than that, and we need more innovation and more work in this area, particularly more activity from the governments. We’ve seen that, but it is a little bit frail from that point of view right now.

Gardner: Dave Lounsbury, thoughts about what need to happen in order to keep this on the tracks?

Lounsbury: We’ve touched on lot of them already. Thank you for mentioning the machine-to-machine part, because there are plenty of projections that show that it’s going to be the dominant form of Internet communication, probably within the next four years.

So we need to start thinking of that and moving beyond our traditional models of humans talking through interfaces to set of services. We need to identify the building blocks of capability that you need to manage, not only the information flow and the skilled person that is going to produce it, but also how you manage the machine-to-machine interactions.

Gordon: I’d like to see not so much focus on data management, but focus on what is the data managing and helping us to do. Focusing on the machine-to-machine and the devices is great, but it should be not on the devices or on the machines… it should be on what can they accomplish by communicating; what can you accomplish with the devices and then have a reverse engineer from that.

Gardner: Let’s go to some questions from the audience. The first one asks about a high order of intelligence which we mentioned earlier. It could be artificial intelligence, perhaps, but they ask whether that’s really the issue. Is the nature of the data substantially different, or we are just creating more of the same, so that it is a storage, plumbing, and processing problem? What, if anything, are we lacking in our current analytics capabilities that are holding us back from exploiting the Internet of Things?

Gordon: I’ve definitely seen that. That has a lot to do with not setting your decision objectives and your decision criteria ahead of time so that you end up collecting a whole bunch of data, and the important data gets lost in the mix. There is a term “data smog.”

Most important

The solution is to figure out, before you go collecting data, what data is most important to you. If you can’t collect certain kinds of data that are important to you directly, then think about how to indirectly collect that data and how to get proxies. But don’t try to go and collect all the data for that. Narrow in on what is going to be most important and most representative of what you’re trying to accomplish.

Gardner: Does anyone want to add to this idea of understanding what current analytics capabilities are lacking, if we have to adopt and absorb the Internet of Things?

Barsoum: There is one element around projection into the future. We’ve been very good at analyzing historical information to understand what’s been happening in the past. We need to become better at projecting into the future, and obviously we’ve been doing that for some time already.

But so many variables are changing. Just to take the driverless car as an example. We’ve been collecting data from loop detectors, radar detectors, and even Bluetooth antennas to understand how traffic moves in the city. But we need to think harder about what that means and how we understand the city of tomorrow is going to work. That requires more thinking about the data, a little bit like what Penelope mentioned, how we interpret that, and how we push that out into the future.

Lounsbury: I have to agree with both. It’s not about statistics. We can use historical data. It helps with lot of things, but one of the major issues we still deal with today is the question of semantics, the meaning of the data. This goes back to your point, Penelope, around the relevance and the context of that information – how you get what you need when you need it, so you can make the right decisions.

Gardner: Our last question from the audience goes back to Jean-Francois’s comments about the Canadian healthcare system. I imagine it applies to almost any healthcare system around the world. But it asks why interoperability is so difficult to achieve, when we have the power of the purse, that is the market. We also supposedly have the power of the legislation and regulation. You would think between one or the other or both that interoperability, because the stakes are so high, would happen. What’s holding it up?

Barsoum: There are a couple of reasons. One, in the particular case of healthcare, is privacy, but that is one that you could see going elsewhere. As soon as you talk about interoperability in the health sector, people start wondering where is their data going to go and how accessible is it going to be and to whom.

You need to put a certain number of controls over top of that. What is happening in parallel is that you have people who own some data, who believe they have some power from owning that data, and that they will lose that power if they share it. That can come from doctors, hospitals, anywhere.

So there’s a certain amount of change management you have to get beyond. Everybody has to focus on the welfare of the patient. They have to understand that there has to be a priority, but you also have to understand the welfare of the different stakeholders in the system and make sure that you do not forget about them, because if you forget about them they will find some way to slow you down.

Use of an ecosystem

Lounsbury: To me, that’s a perfect example of what Marshall Van Alstyne talked about this morning. It’s the change from focus on product to a focus on an ecosystem. Healthcare traditionally has been very focused on a doctor providing product to patient, or a caregiver providing a product to a patient. Now, we’re actually starting to see that the only way we’re able to do this is through use of an ecosystem.

That’s a hard transition. It’s a business-model transition. I will put in a plug here for The Open Group Healthcare vertical, which is looking at that from architecture perspective. I see that our Forum Director Jason Lee is over here. So if you want to explore that more, please see him.

Gardner: I’m afraid we will have to leave it there. We’ve been discussing the practical implications of the Internet of Things and how it is now set to add a new dimension to Open Platform 3.0 and Boundaryless Information Flow.

We’ve heard how new thinking about interoperability will be needed to extract the value and orchestrate out the chaos with such vast new scales of inputs and a whole new categories of information.

So with that, a big thank you to our guests: Said Tabet, Chief Technology Officer for Governance, Risk and Compliance Strategy at EMC; Penelope Gordon, Emerging Technology Strategist at 1Plug Corp.; Jean-Francois Barsoum, Senior Managing Consultant for Smarter Cities, Water and Transportation at IBM, and Dave Lounsbury, Chief Technology Officer at The Open Group.

This is Dana Gardner, Principal Analyst at Interarbor Solutions, your host and moderator throughout these discussions on Open Platform 3.0 and Boundaryless Information Flow at The Open Group Conference, recently held in Boston. Thanks again for listening, and come back next time.

Listen to the podcast. Find it on iTunes. Download the transcript.

Transcript of The Open Group podcast exploring the challenges and ramifications of the Internet of Things, as machines and sensors collect vast amounts of data. Copyright The Open Group and Interarbor Solutions, LLC, 2005-2014. All rights reserved.

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Q&A with Marshall Van Alstyne, Professor, Boston University School of Management and Research Scientist MIT Center for Digital Business

By The Open Group

The word “platform” has become a nearly ubiquitous term in the tech and business worlds these days. From “Platform as a Service” (PaaS) to IDC’s Third Platform to The Open Group Open Platform 3.0™ Forum, the concept of platforms and building technology frames and applications on top of them has become the next “big thing.”

Although the technology industry tends to conceive of “platforms” as the vehicle that is driving trends such as mobile, social networking, the Cloud and Big Data, Marshall Van Alstyne, Professor at Boston University’s School of Management and a Research Scientist at the MIT Center for Digital Business, believes that the radical shifts that platforms bring are not just technological.

We spoke with Van Alstyne prior to The Open Group Boston 2014, where he presented a keynote, about platforms, how they have shifted traditional business models and how they are impacting industries everywhere.

The title of your session at the Boston conference was “Platform Shift – How New Open Business Models are Changing the Shape of Industry.” How would you define both “platform” and “open business model”?

I think of “platform” as a combination of two things. One, a set of standards or components that folks can take up and use for production of goods and services. The second thing is the rules of play, or the governance model – who has the ability to participate, how do you resolve conflict, and how do you divide up the royalty streams, or who gets what? You can think of it as the two components of the platform—the open standard together with the governance model. The technologists usually get the technology portion of it, and the economists usually get the governance and legal portions of it, but you really need both of them to understand what a ‘platform’ is.

What is the platform allowing then and how is that different from a regular business model?

The platform allows third parties to conduct business using system resources so they can actually meet and exchange goods across the platform. Wonderful examples of that include AirBnB where you can rent rooms or you can post rooms, or eBay, where you can sell goods or exchange goods, or iTunes where you can go find music, videos, apps and games provided by others, or Amazon where third parties are even allowed to set up shop on top of Amazon. They have moved to a business model where they can take control of the books in addition to allowing third parties to sell their own books and music and products and services through the Amazon platform. So by opening it up to allow third parties to participate, you facilitate exchange and grow a market by helping that exchange.

How does this relate to the concept of the technology industry is defining the “third platform”?

I think of it slightly differently. The tech industry uses mobile and social and cloud and data to characterize it. In some sense this view offers those as the attributes that characterize platforms or the knowledge base that enable platforms. But we would add to that the economic forces that actually shape platforms. What we want to do is give you some of the strategic tools, the incentives, the rules that will actually help you control their trajectory by helping you improve who participates and then measure and improve the value they contribute to the platform. So a full ecosystem view is not just the technology and the data, it also measures the value and how you divide that value. The rules of play really become important.

I think the “third platform” offers marvelous concepts and attributes but you also need to add the economics to it: Why do you participate, who gets what portions of the value, and who ultimately owns control.

Who does control the platform then?

A platform has multiple parts. Determining who controls what part is the art and design of the governance model. You have to set up control in the right way to motivate people to participate. But before we get to that, let’s go back and complete the idea of what’s an ‘open platform.’

To define an open platform, consider both the right of access and the right to manipulate platform resources, then consider granting those rights to four different parties. One is the user—can they access one another, can they access data, can they access system resources? Another group is developers—can they manipulate system resources, can they add new features to it, can they sell through the platform? The third group is the platform providers. You often think of them as those folks that facilitate access across the platform. To give you an example, iTunes is a single monolithic store, so the provider is simply Apple, but Android, in contrast, allows multiple providers, so there’s a Samsung Android store, an LTC Android store, a Google Android store, there’s even an Amazon version that uses a different version of Android. So that platform has multiple providers each with rights to access users. The fourth group is the party that controls the underlying property rights, who owns the IP. The ability modify the underlying standard and also the rights of access for other parties is the bottom-most layer.

So to answer the question of what is ‘open,’ you have to consider the rights of access of all four groups—the users, developers, the providers and IP rights holders, or sponsors, underneath.

Popping back up a level, we’re trying to motivate different parties to participate in the ecosystem. So what do you give the users? Usually it’s some kind of value. What do you give developers? Usually it’s some set of SDKs and APIs, but also some level of royalties. It’s fascinating. If you look back historically, Amazon initially tried a publishing royalty where they took 70% and gave a minority 30% back to developers. They found that didn’t fly very well and they had to fall back to the app store or software-style royalty, where they’re taking a lower percentage. I think Apple, for example, takes 30 percent, and Amazon is now close to that. You see ranges of royalties going anywhere from a few percent—an example is credit cards—all the way up to iStock photo where they take roughly 70 percent. That’s an extremely high rate, and one that I don’t recommend. We were just contracting for designs at 99Designs and they take a 20 percent cut. That’s probably more realistic, but lower might perhaps even be better—you can create stronger network effect if that’s the case.

Again, the real question of control is how you motivate third parties to participate and add value? If you are allowing them to use resources to create value and keep a lot of that value, then they’re more motivated to participate, to invest, to bring their resources to your platform. If you take most of the value they create, they won’t participate. They won’t add value. One of the biggest challenges for open platforms—what you might call the ‘Field of Dreams’ approach—is that most folks open their platform and assume ‘if you build it, they will come,’ but you really need to reward them to do so. Why would they want to come build with you? There are numerous instances of platforms that opened but no developer chooses to add value—the ecosystem is too small. You have to solve the chicken and egg problem where if you don’t have users, developers don’t want to build for you, but if you don’t have developer apps, then why do users participate? So you’ve got a huge feedback problem. And those are where the economics become critical, you must solve the chicken and egg problem to build and roll out platforms.

It’s not just a technology question; it’s also an economics and rewards question.

Then who is controlling the platform?

The answer depends on the type of platform. Giving different groups a different set of rights creates different types of platform. Consider the four different parties: users, developers, providers, and sponsors. At one extreme, the Apple Mac platform of the 1980s reserved most rights for development, for producing hardware (the provider layer), and for modifying the IP (the sponsor layer) all to Apple. Apple controlled the platform and it remained closed. In contrast, Microsoft relaxed platform control in specific ways. It licensed to multiple providers, enabling Dell, HP, Compaq and others to sell the platform. It gave developers rights of access to SDKs and APIs, enabling them to extend the platform. These control choices gave Microsoft more than six times the number of developers and more than twenty times the market share of Apple at the high point of Microsoft’s dominance of desktop operating systems. Microsoft gave up some control in order to create a more inclusive platform and a much bigger market.

Control is not a single concept. There are many different control rights you can grant to different parties. For example, you often want to give users an ability to control their own data. You often want to give developers intellectual property rights for the apps that they create and often over the data that their users create. You may want to give them some protections against platform misappropriation. Developers resent it if you take their ideas. So if the platform sees a really clever app that’s been built on top of its platform, what’s the guarantee that the platform simply doesn’t take it or build a competing app? You need to protect your developers in that case. Same thing’s true of the platform provider—what guarantees do they provide users for the quality of content provided on their ecosystem? For example, the Android ecosystem is much more open than the iPhone ecosystem, which means you have more folks offering stores. Simultaneously, that means that there are more viruses and more malware in Android, so what rights and guarantees do you require of the platform providers to protect the users in order that they want to participate? And then at the bottom, what rights do other participants have to control the direction of the platform growth? In the Visa model, for example, there are multiple member banks that help to influence the general direction of that credit card standard. Usually the most successful platforms have a single IP rights holder, but there are several examples of that have multiple IP rights holders.

So, in the end control defines the platform as much as the platform defines control.

What is the “secret” of the Internet-driven marketplace? Is that indeed the platform?

The secret is that, in effect, the goal of the platform is to increase transaction volume and value. If you can do that—and we can give you techniques for doing it—then you can create massive scale. Increasing the transaction value and transactions volume across your platform means that the owner of the platform doesn’t have to be the sole source of content and new ideas provided on the platform. If the platform owner is the only source of value then the owner is also the bottleneck. The goal is to consummate matches between producers and consumers of value. You want to help users find the content, find the resources, find the other people that they want to meet across your platform. In Apple’s case, you’re helping them find the music, the video, the games, and the apps that they want. In AirBnB’s case, you’re helping them find the rooms that they want, or Uber, you’re helping them find a driver. On Amazon, the book recommendations help you find the content that you want. In all the truly successful platforms, the owner of the platform is not providing all of that value. They’re enabling third parties to add that value, and that’s one reasy why The Open Group’s ideas are so important—you need open systems for this to happen.

What’s wrong with current linear business models? Why is a network-driven approach superior?

The fundamental reason why the linear business model no longer works is that it does not manage network effects. Network effects allow you to build platforms where users attract other users and you get feedback that grows your system. As more users join your platform, more developers join your platform, which attracts more users, which attracts more developers. You can see it on any of the major platforms. This is also true of Google. As advertisers use Google Search, the algorithms get better, people find the content that they want, so more advertisers use it. As more drivers join Uber, more people are happier passengers, which attracts more drivers. The more merchants accept Visa, the more consumers are willing to carry it, which attracts more merchants, which attracts more consumers. You get positive feedback.

The consequence of that is that you tend to get market concentration—you get winner take all markets. That’s where platforms dominate. So you have a few large firms within a given category, whether this is rides or books or hotels or auctions. Further, once you get network effects changing your business model, the linear insights into pricing, into inventory management, into innovation, into strategy breakdown.

When you have these multi-sided markets, pricing breaks down because you often price differently to one side than another because one side attracts the other. Inventory management practices breakdown because you’re selling inventory that you don’t even own. Your R&D strategies breakdown because now you’re motivating innovation and research outside the boundaries of the firm, as opposed to inside the internal R&D group. And your strategies breakdown because you’re not just looking for cost leadership or product differentiation, now you’re looking to shape the network effects as you create barriers to entry.

One of the things that I really want to argue strenuously is that in markets where platforms will emerge, platforms beat product every time. So the platform business model will inevitably beat the linear, product-based business model. Because you’re harnessing new forces in order to develop a different kind of business model.

Think of it the following way–imagine that value is growing as users consume your product. Think of any of the major platforms, as more folks use Google, search gets better, the more recommendations improve on Amazon, and the easier it is to find a ride on Uber, so more folks want to be on there. It is easier to scale network effects outside your business than inside your business. There’s simply more people outside than inside. The moment that happens, the locus control, the locus of innovation, moves from inside the firm to outside the firm. So the rules change. Pricing changes, your innovation strategies change, your inventory policies change, your R&D changes. You’re now managing resources outside the firm, rather than inside, in order to capture scale. This is different than the traditional industrial supply economies of scale.

Old systems are giving away to new systems. It’s not that the whole system breaks down, it’s simply that you’re looking to manage network effects and manage new business models. Another way to see this is that previously you were managing capital. In the industrial era, you were managing steel, you were managing large amounts of finance in banking, you were managing auto parts—huge supply economies of scale. In telecommunications, you were managing infrastructure. Now, you’re managing communities and these are managed outside the firm. The value that’s been created at Facebook or WhatsApp or Instagram or any of the new acquisitions, it’s not the capital that’s critical, it’s the communities that are critical, and these are built outside the firm.

There is a lot of talk in the industry about the Nexus of Forces as Gartner calls it, or Third Platform (IDC). The Open Group calls it Open Platform 3.0. Your concept goes well beyond technology—how does Open Platform 3.0 enable new business models?

Those are the enablers—they’re shall we say necessary, but they’re not sufficient. You really must harness the economic forces in addition to those enablers—mobile, social, Cloud, data. You must manage communities outside the firm, that’s the mobile and the social element of it. But this also involves designing governance and setting incentives. How are you capturing users outside the organization, how are they contributing, how are they being motivated to participate, why are they spreading your products to their peers? The Cloud allows it to scale—so Instagram and What’s App and others scale. Data allows you to “consummate the match.” You use that data to help people find what they need, to add value, so all of those things are the enablers. Then you have to harness the economics of the enablers to encourage people to do the right thing. You can see the correct intuition if you simply ask what happens if all you offer is a Cloud service and nothing more. Why will anyone use it? What’s the value to that system? If you open APIs to it, again, if you don’t have a user base, why are developers going to contribute? Developers want to reach users. Users want valuable functionality.

You must manage the motives and the value-add on the platform. New business models come from orchestrating not just the technology but also the third party sources of value. One of the biggest challenges is to grow these businesses from scratch—you’ve got the cold start chicken and egg problem. You don’t have network effects if you don’t have a user base, if you don’t have users, you don’t have network effects.

Do companies need to transform themselves into a “business platform” to succeed in this new marketplace? Are there industries immune to this shift?

There is a continuum of companies that are going to be affected. It starts at one end with companies that are highly information intense—anything that’s an information intensive business will be dramatically affected, anything that’s community or fashion-based business will be dramatically affected. Those include companies involved in media and news, songs, music, video; all of those are going to be the canaries in the coalmine that see this first. Moving farther along will be those industries that require some sort of certification—those include law and medicine and education—those, too, will also be platformized, so the services industries will become platforms. Farther down that are the ones that are heavily, heavily capital intensive where control of physical capital is paramount, those include trains and oil rigs and telecommunications infrastructure—eventually those will be affected by platform business models to the extent that data helps them gain efficiencies or add value, but they will in some sense be the last to be affected by platform business models. Look for the businesses where the cost side is shrinking in proportion to the delivery of value and where the network effects are rising as a proportional increase in value. Those forces will help you predict which industries will be transformed.

How can Enterprise Architecture be a part of this and how do open standards play a role?

The second part of that question is actually much easier. How do open standards play a role? The open standards make it much easier for third parties to attach and incorporate technology and features such that they can in turn add value. Open standards are essential to that happening. You do need to ask the question as to who controls those standards—is it completely open or is it a proprietary standard, a published standard but it’s not manipulable by a third party.

There will be at least two or three different things that Enterprise Architects need to do. One of these is to design modular components that are swappable, so as better systems become available, the better systems can be swapped in. The second element will be to watch for components of value that should be absorbed into the platform itself. As an example, in operating systems, web browsing has effectively been absorbed into the platform, streaming has been absorbed into the platform so that they become aware of how that actually works. A third thing they need to do is talk to the legal team to see where it is that the third parties property rights can be protected so that they invest. One of the biggest mistakes that firms make is to simply assume that because they own the platform, because they have the rights of control, that they can do what they please. If they do that, they risk alienating their ecosystems. So they should talk to their potential developers to incorporate developer concerns. One of my favorite examples is the Intel Architecture Lab which has done a beautiful job of articulating the voices of developers in their own architectural plans. A fourth thing that can be done is an idea borrowed from SAP, that builds Enterprise Architecture—they articulate an 18-24 month roadmap where they say these are the features that are coming, so you can anticipate and build on those. Also it gives you an idea of what features will be safe to build on so you won’t lose the value you’ve created.

What can companies do to begin opening their business models and more easily architect that?

What they should do is to consider four groups articulated earlier— those are the users, the providers, the developers and the sponsors—each serve a different role. Firms need to understand what their own role will be in order that they can open and architect the other roles within their ecosystem. They’ll also need to choose what levels of exclusivity they need to give their ecosystem partners in a different slice of the business. They should also figure out which of those components they prefer to offer themselves as unique competencies and where they need to seek third party assistance, either in new ideas or new resources or even new marketplaces. Those factors will help guide businesses toward different kinds of partnerships, and they’ll have to be open to those kinds of partners. In particular, they should think about where are they most likely to be missing ideas or missing opportunities. Those technical and business areas should open in order that third parties can take advantage of those opportunities and add value.

 

vanalstynemarshallProfessor Van Alstyne is one of the leading experts in network business models. He conducts research on information economics, covering such topics as communications markets, the economics of networks, intellectual property, social effects of technology, and productivity effects of information. As co-developer of the concept of “two sided networks” he has been a major contributor to the theory of network effects, a set of ideas now taught in more than 50 business schools worldwide.

Awards include two patents, National Science Foundation IOC, SGER, SBIR, iCorp and Career Awards, and six best paper awards. Articles or commentary have appeared in Science, Nature, Management Science, Harvard Business Review, Strategic Management Journal, The New York Times, and The Wall Street Journal.

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Discussing Enterprise Decision-Making with Penelope Everall Gordon

By The Open Group

Most enterprises today are in the process of jumping onto the Big Data bandwagon. The promise of Big Data, as we’re told, is that if every company collects as much data as they can—about everything from their customers to sales transactions to their social media feeds—executives will have “the data they need” to make important decisions that can make or break the company. Not collecting and using your data, as the conventional wisdom has it, can have deadly consequences for any business.

As is often the case with industry trends, the hype around Big Data contains both a fair amount of truth and a fair amount of fuzz. The problem is that within most organizations, that conventional wisdom about the power of data for decision-making is usually just the tip of the iceberg when it comes to how and why organizational decisions are made.

According to Penelope Gordon, a consultant for 1Plug Corporation who was recently a Cloud Strategist at Verizon and was formerly a Service Product Strategist at IBM, that’s why big “D” (Data) needs to be put back into the context of enterprise decision-making. Gordon, who spoke at The Open Group Boston 2014, in the session titled “Putting the D Back in Decision” with Jean-Francois Barsoum of IBM, argues that a focus on collecting a lot of data has the potential to get in the way of making quality decisions. This is, in part, due to the overabundance of data that’s being collected under the assumption that you never know where there’s gold to be mined in your data, so if you don’t have all of it at hand, you may just miss something.

Gordon says that assuming the data will make decisions obvious also ignores the fact that ultimately decisions are made by people—and people usually make decisions based on their own biases. According to Gordon, there are three types of natural decision making styles—heart, head and gut styles—corresponding to different personality types, she said; the greater the amount of data the more likely that it will not balance the natural decision-making style.

Head types, Gordon says, naturally make decisions based on quantitative evidence. But what often happens is that head types often put off making a decision until more data can be collected, wanting more and more data so that they can make the best decision based on the facts. She cites former President Bill Clinton as a classic example of this type. During his presidency, he was famous for putting off decision-making in favor of gathering more and more data before making the decision, she says. Relying solely on quantitative data also can mean you may miss out on other important factors in making optimal decisions based on either heart (qualitative) or instinct. Conversely, a gut-type presented with too much data will likely just end up ignoring data and acting on instinct, much like former President George W. Bush, Gordon says.

Gordon believes part of the reason that data and decisions are more disconnected than one might think is because IT and Marketing departments have become overly enamored with what technology can offer. These data providers need to step back and first examine the decision objectives as well as the governance behind those decisions. Without understanding the organization’s decision-making processes and the dynamics of the decision-makers, it can be difficult to make optimal and effective strategic recommendations, she says, because you don’t have the full picture of what the stakeholders will or will not accept in terms of a recommendation, data or no data.

Ideally, Gordon says, you want to get to a point where you can get to the best decision outcome possible by first figuring out the personal and organizational dynamics driving decisions within the organization, shifting the focus from the data to the decision for which the data is an input.

“…what you’re trying to do is get the optimal outcome, so your focus needs to be on the outcome, so when you’re collecting the data and assessing the data, you also need to be thinking about ‘how am I going to present this data in a way that it is going to be impactful in improving the decision outcomes?’ And that’s where the governance comes into play,” she said.

Governance is of particular importance now, Gordon says, because decisions are increasingly being made by individual departments, such as when departments buy their own cloud-enabled services, such as sales force automation. In that case, an organization needs to have a roadmap in place with compensation to incent decision-makers to adhere to that roadmap and decision criteria for buying decisions, she said.

Gordon recommends that companies put in place 3-5 top criteria for each decision that needs to be made so that you can ensure that the decision objectives are met. This distillation of the metrics gives decision-makers a more comprehensible picture of their data so that their decisions don’t become either too subjective or disconnected from the data. Lower levels of metrics can be used underneath each of those top-level criteria to facilitate a more nuanced valuation. For example, if an organization needing to find good partner candidates scored and ranked (preferably in tiers) potential partners using decision criteria based on the characteristics of the most attractive partner, rather than just assuming that companies with the best reputation or biggest brands will be the best, then they will expeditiously identify the optimal partner candidates.

One of the reasons that companies have gotten so concerned with collecting and storing data rather than just making better decisions, Gordon believes, is that business decisions have become inherently more risky. The required size of investment is increasing in tandem with an increase in the time to return; time to return is a key determinant of risk. Data helps people feel like they are making competent decisions but in reality does little to reduce risk.

“If you’ve got lots of data, then the thinking is, ‘well, I did the best that I could because I got all of this data.’ People are worried that they might miss something,“ she said. “But that’s where I’m trying to come around and say, ‘yeah, but going and collecting more data, if you’ve got somebody like President Clinton, you’re just feeding into their tendency to put off making decisions. If you’ve got somebody like President Bush and you’re feeding into their tendency to ignore it, then there may be some really good information, good recommendations they’re ignoring.”

Gordon also says that having all the data possible to work with isn’t usually necessary—generally a representative sample will do. For example, she says the U.S Census Bureau takes the approach where it tries to count every citizen; consequently certain populations are chronically undercounted and inaccuracies pass undetected. The Canadian census, on the other hand, uses representative samples and thus tends to be much more accurate—and much less expensive to conduct. Organizations should also think about how they can find representative or “proxy” data in cases where collecting data that directly addresses a top-level decision criteria isn’t really practical.

To begin shifting the focus from collecting data inputs to improving decision outcomes, Gordon recommends clearly stating the decision objectives for each major decision and then identifying and defining the 3-5 criteria that are most important for achieving the decision objectives. She also recommends ensuring that there is sufficient governance and a process in place for making decisions including mechanisms for measuring the performance of the decision-making process and the outcomes resulting from the execution of that process. In addition, companies need to consider whether their decisions are made in a centralized or decentralized manner and then adapt decision governance accordingly.

One way that Enterprise Architects can help to encourage better decision-making within the organizations in which they work is to help in developing that governance rather than just providing data or data architectures, Gordon says. They should help stakeholders identify and define the important decision criteria, determine when full population rather than representative sampling is justified, recognize better methods for data analysis, and form decision recommendations based on that analysis. By gauging the appropriate blend of quantitative and qualitative data for a particular decision maker, an Architect can moderate gut types’ reliance on instinct and stimulate head and heart types’ intuition – thereby producing an optimally balanced decision. Architects should help lead and facilitate execution of the decision process, as well as help determine how data is presented within organizations in order to support the recommendations with the highest potential for meeting the decision objectives.

Join the conversation – #ogchat

penelopegordonPenelope Gordon recently led the expansion of the channel and service packaging strategies for Verizon’s cloud network products. Previously she was an IBM Strategist and Product Manager bringing emerging technologies such as predictive analytics to market. She helped to develop one of the world’s first public clouds.

 

 

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The Open Group Boston 2014 – Day Two Highlights

By Loren K. Bayes, Director, Global Marketing Communications

Enabling Boundaryless Information Flow™  continued in Boston on Tuesday, July 22Allen Brown, CEO and President of The Open Group welcomed attendees with an overview of the company’s second quarter results.

The Open Group membership is at 459 organizations in 39 countries, including 16 new membership agreements in 2Q 2014.

Membership value is highlighted by the collaboration Open Group members experience. For example, over 4,000 individuals attended Open Group events (physically and virtually whether at member meetings, webinars, podcasts, tweet jams). The Open Group website had more than 1 million page views and over 105,000 publication items were downloaded by members in 80 countries.

Brown also shared highlights from The Open Group Forums which featured status on many upcoming white papers, snapshots, reference models and standards, as well as individiual Forum Roadmaps. The Forums are busy developing and reviewing projects such as the Next Version of TOGAF®, an Open Group standard, an ArchiMate® white paper, The Open Group Healthcare Forum charter and treatise, Standard Mils™ APIs and Open Fair. Many publications are translated into multiple languages including Chinese and Portuguese. Also, a new Forum will be announced in the third quarter at The Open Group London 2014 so stay tuned for that launch news!

Our first keynote of the day was Making Health Addictive by Joseph Kvedar, MD, Partners HealthCare, Center for Connected Health.

Dr. Kvedar described how Healthcare delivery is changing, with mobile technology being a big part. Other factors pushing changes are reimbursement paradigms and caregivers being paid to be more efficient and interested in keeping people healthy and out of hospitals. The goal of Healthcare providers is to integrate care into the day-to-day lives of patients. Healthcare also aims for better technologies and architecture.

Mobile is a game-changer in Healthcare because people are “always on and connected”. Mobile technology allows for in-the-moment messaging, ability to capture health data (GPS, accelerator, etc.) and display information in real time as needed. Bottom-line, smartphones are addictive so they are excellent tools for communication and engagement.

But there is a need to understand and address the implications of automating Healthcare: security, privacy, accountability, economics.

The plenary continued with Proteus Duxbury, CTO, Connect for Health Colorado, who presented From Build to Run at the Colorado Health Insurance Exchange – Achieving Long-term Sustainability through Better Architecture.

Duxbury stated the keys to successes of his organization are the leadership and team’s shared vision, a flexible vendor being agile with rapidly changing regulatory requirements, and COTS solution which provided minimal customization and custom development, resilient architecture and security. Connect for Health experiences many challenges including budget restraints, regulation and operating in a “fish bowl”. Yet, they are on-track with their three-year ‘build to run’ roadmap, stabilizing their foundation and gaining efficiencies.

During the Q&A with Allen Brown following each presentation, both speakers emphasized the need for standards, architecture and data security.

Brown and DuxburyAllen Brown and Proteus Duxbury

During the afternoon, track sessions consisted of Healthcare, Enterprise Architecture (EA) & Business Value, Service-Oriented Architecture (SOA), Security & Risk Management, Professional Development and ArchiMate Tutorials. Chris Armstrong, President, Armstrong Process Group, Inc. discussed Architecture Value Chain and Capability Model. Laura Heritage, Principal Solution Architect / Enterprise API Platform, SOA Software, presented Protecting your APIs from Threats and Hacks.

The evening culminated with a reception at the historic Old South Meeting House, where the Boston Tea Party began in 1773.

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IMG_2814Networking Reception at Old South Meeting House

A special thank you to our sponsors and exhibitors at The Open Group Boston 2014: BiZZdesign, Black Duck, Corso, Good e-Learning, Orbus and AEA.

Join the conversation #ogBOS!

Loren K. BaynesLoren K. Baynes, Director, Global Marketing Communications, joined The Open Group in 2013 and spearheads corporate marketing initiatives, primarily the website, blog and media relations. Loren has over 20 years experience in brand marketing and public relations and, prior to The Open Group, was with The Walt Disney Company for over 10 years. Loren holds a Bachelor of Business Administration from Texas A&M University. She is based in the US.

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The Open Group Boston 2014 – Day One Highlights

By Loren K. Baynes, Director, Global Marketing Communications

The Open Group kicked off Enabling Boundaryless Information Flow™  July 21 at the spectacular setting of the Hyatt Boston Harbor. Allen Brown, CEO and President of The Open Group, welcomed over 150 people from 20 countries, including as far away as Australia, Japan, Saudi Arabia and India.

The first keynote speaker was Marshall Van Alstyne, Professor at Boston University School of Management & Researcher at MIT Center for Digital Business, known as a leading expert in business models. His presentation entitled Platform Shift – How New Open Business Models are Changing the Shape of Industry posed the questions “What does ‘openness’ mean? Why do platforms beat products every time?”.

Van AlstyneMarshall Van Alstyne

According to “InterBrand: 2014 Best Global Brands”, 13 of the top 31 companies are “platform companies”. To be a ‘platform’, a company needs embeddable functions or service and allow 3rd party access. Alystyne noted, “products have features, platforms have communities”. Great standalone products are not sufficient. Positive changes experienced by a platform company include pricing/profitability, supply chains, internal organization, innovation, decreased industry bottlenecks and strategy.

Platforms benefit from broad contributions, as long as there is control of the top several complements. Alstyne commented, “If you believe in the power of community, you need to embrace the platform.”

The next presentation was Open Platform 3.0™ – An Integrated Approach to the Convergence of Technology Platforms, by Dr. Chris Harding, Director for Interoperability, The Open Group. Dr. Harding discussed how society has developed a digital society.

1970 was considered the dawn of an epoch which saw the First RAM chip, IBM introduction of System/370 and a new operating system – UNIX®. Examples of digital progress since that era include driverless cars and Smart Cities (management of traffic, energy, water, communication).

Digital society enablers are digital structural change and corporate social media. The benefits are open innovation, open access, open culture, open government and delivering more business value.

Dr. Harding also noted, standards are essential to innovation and enable markets based on integration. The Open Group Open Platform 3.0™ is using ArchiMate®, an Open Group standard, to analyze the 30+ business use cases produced by the Forum. The development cycle is understanding, analysis, specification, iteration.

Dr. Harding emphasized the importance of Boundaryless Information Flow™, as an enabler of business objectives and efficiency through IT standards in the era of digital technology, and designed for today’s agile enterprise with direct involvement of business users.

Both sessions concluded with an interactive audience Q&A hosted by Allen Brown.

The last session of the morning’s plenary was a panel: The Internet of Things and Interoperability. Dana Gardner, Principal Analyst at Interarbor Solutions, moderated the panel. Participating in the panel were Said Tabet, CTO for Governance, Risk and Compliance Strategy, EMC; Penelope Gordon, Emerging Technology Strategist, 1Plug Corporation; Jean-Francois Barsoum, Senior Managing Consultant, Smarter Cities, Water & Transportation, IBM; and Dave Lounsbury, CTO, The Open Group.

IoT PanelIoT Panel – Gardner, Barsoum, Tabet, Lounsbury, Gordon

The panel explored the practical limits and opportunities of Internet of Things (IoT). The different areas discussed include obstacles to decision-making as big data becomes more prolific, openness, governance and connectivity of things, data and people which pertain to many industries such as smart cities, manufacturing and healthcare.

How do industries, organizations and individuals deal with IoT? This is not necessarily a new problem, but an accelerated one. There are new areas of interoperability but where does the data go and who owns the data? Openness is important and governance is essential.

What needs to change most to see the benefits of the IoT? The panel agreed there needs to be a push for innovation, increased education, move beyond models of humans managing the interface (i.e. machine-to-machine) and determine what data is most important, not always collecting all the data.

A podcast and transcript of the Internet of Things and Interoperability panel will be posted soon.

The afternoon was divided into several tracks: Boundaryless Information Flow™, Open Platform 3.0™ and Enterprise Architecture (EA) & Enterprise Transformation. Best Practices for Enabling Boundaryless Information Flow across the Government was presented by Syed Husain, Consultant Enterprise Architecture, Saudi Arabia E-government Authority. Robert K. Pucci, CTO, Communications Practice, Cognizant Technology Solutions discussed Business Transformation Justification Leveraging Business and Enterprise Architecture.

The evening concluded with a lively networking reception at the hotel.

Join the conversation #ogBOS!

Loren K. BaynesLoren K. Baynes, Director, Global Marketing Communications, joined The Open Group in 2013 and spearheads corporate marketing initiatives, primarily the website, blog and media relations. Loren has over 20 years experience in brand marketing and public relations and, prior to The Open Group, was with The Walt Disney Company for over 10 years. Loren holds a Bachelor of Business Administration from Texas A&M University. She is based in the US.

 

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New Health Data Deluges Require Secure Information Flow Enablement Via Standards, Says The Open Group’s New Healthcare Director

By The Open Group

Below is the transcript of The Open Group podcast on how new devices and practices have the potential to expand the information available to Healthcare providers and facilities.

Listen to the podcast here.

Dana Gardner: Hello, and welcome to a special BriefingsDirect Thought Leadership Interview coming to you in conjunction with The Open Group’s upcoming event, Enabling Boundaryless Information Flow™ July 21-22, 2014 in Boston.

GardnerI’m Dana Gardner, Principal Analyst at Interarbor Solutions and I’ll be your host and moderator for the series of discussions from the conference on Boundaryless Information Flow, Open Platform 3.0™, Healthcare, and Security issues.

One area of special interest is the Healthcare arena, and Boston is a hotbed of innovation and adaption for how technology, Enterprise Architecture, and standards can improve the communication and collaboration among Healthcare ecosystem players.

And so, we’re joined by a new Forum Director at The Open Group to learn how an expected continued deluge of data and information about patients, providers, outcomes, and efficiencies is pushing the Healthcare industry to rapid change.

WJason Lee headshotith that, please join me now in welcoming our guest. We’re here with Jason Lee, Healthcare and Security Forums Director at The Open Group. Welcome, Jason.

Jason Lee: Thank you so much, Dana. Good to be here.

Gardner: Great to have you. I’m looking forward to the Boston conference and want to remind our listeners and readers that it’s not too late to sign up. You can learn more at http://www.opengroup.org.

Jason, let’s start by talking about the relationship between Boundaryless Information Flow, which is a major theme of the conference, and healthcare. Healthcare perhaps is the killer application for Boundaryless Information Flow.

Lee: Interesting, I haven’t heard it referred to that way, but healthcare is 17 percent of the US economy. It’s upwards of $3 trillion. The costs of healthcare are a problem, not just in the United States, but all over the world, and there are a great number of inefficiencies in the way we practice healthcare.

We don’t necessarily intend to be inefficient, but there are so many places and people involved in healthcare, it’s very difficult to get them to speak the same language. It’s almost as if you’re in a large house with lots of different rooms, and every room you walk into they speak a different language. To get information to flow from one room to the other requires some active efforts and that’s what we’re undertaking here at The Open Group.

Gardner: What is it about the current collaboration approaches that don’t work? Obviously, healthcare has been around for a long time and there have been different players involved. What’s the hurdle? What prevents a nice, seamless, easy flow and collaboration in information that gets better outcomes? What’s the holdup?

Lee: There are many ways to answer that question, because there are many barriers. Perhaps the simplest is the transformation of healthcare from a paper-based industry to a digital industry. Everyone has walked into an office, looked behind the people at the front desk, and seen file upon file and row upon row of folders, information that’s kept in a written format.

When there’s been movement toward digitizing that information, not everyone has used the same system. It’s almost like trains running on a different gauge track. Obviously if the track going east to west is a different gauge than going north to south, then trains aren’t going to be able to travel on those same tracks. In the same way, healthcare information does not flow easily from one office to another or from one provider to another.

Gardner: So not only do we have disparate strategies for collecting and communicating health data, but we’re also seeing much larger amounts of data coming from a variety of new and different places. Some of them now even involve sensors inside of patients themselves or devices that people will wear. So is the data deluge, the volume, also an issue here?

Lee: Certainly. I heard recently that an integrated health plan, which has multiple hospitals involved, contains more elements of data than the Library of Congress. As information is collected at multiple points in time, over a relatively short period of time, you really do have a data deluge. Figuring out how to find your way through all the data and look at the most relevant for the patient is a great challenge.

Gardner: I suppose the bad news is that there is this deluge of data, but it’s also good news, because more data means more opportunity for analysis, a better ability to predict and determine best practices, and also provide overall lower costs with better patient care.

So it seems like the stakes are rather high here to get this right, to not just crumble under a volume or an avalanche of data, but to master it, because it’s perhaps the future. The solution is somewhere in there too.

Lee: No question about it. At The Open Group, our focus is on solutions. We, like others, put a great deal of effort into describing the problems, but figuring out how to bring IT technologies to bear on business problems, how to encourage different parts of organizations to speak to one another and across organizations to speak the same language, and to operate using common standards and language. That’s really what we’re all about.

And it is, in a large sense, part of the process of helping to bring healthcare into the 21st Century. A number of industries are a couple of decades ahead of healthcare in the way they use large datasets — big data, some people refer to it as. I’m talking about companies like big department stores and large online retailers. They really have stepped up to the plate and are using that deluge of data in ways that are very beneficial to them, and healthcare can do the same. We’re just not quite at the same level of evolution.

Gardner: And to your point, the stakes are so much higher. Retail is, of course, a big deal in the economy, but as you pointed out, healthcare is such a much larger segment and portion. So just making modest improvements in communication, collaboration, or data analysis can reap huge rewards.

Lee: Absolutely true. There is the cost side of things, but there is also the quality side. So there are many ways in which healthcare can improve through standardization and coordinated development, using modern technology that cannot just reduce cost, but improve quality at the same time.

Gardner: I’d like to get into a few of the hotter trends, but before we do, it seems that The Open Group has recognized the importance here by devoting the entire second day of their conference in Boston, that will be on July 22, to Healthcare.

Maybe you could give us a brief overview of what participants, and even those who come in online and view recorded sessions of the conference at http://new.livestream.com/opengroup should expect? What’s going to go on July 22nd?

Lee: We have a packed day. We’re very excited to have Dr. Joe Kvedar, a physician at Partners HealthCare and Founding Director of the Center for Connected Health, as our first plenary speaker. The title of his presentation is “Making Health Additive.” Dr. Kvedar is a widely respected expert on mobile health, which is currently the Healthcare Forum’s top work priority. As mobile medical devices become ever more available and diversified, they will enable consumers to know more about their own health and wellness. A great deal of data of potentially useful health data will be generated. How this information can be used–not just by consumers but also by the healthcare establishment that takes care of them as patients, will become a question of increasing importance. It will become an area where standards development and The Open Group can be very helpful.

Our second plenary speaker, Proteus Duxbury, Chief Technology Officer at Connect for Health Colorado,will discuss a major feature of the Affordable Care Act—the health insurance exchanges–which are designed to bring health insurance to tens of millions of people who previously did not have access to it. Mr. Duxbury is going to talk about how Enterprise Architecture–which is really about getting to solutions by helping the IT folks talk to the business folks and vice versa–has helped the State of Colorado develop their Health Insurance Exchange.

After the plenaries, we will break up into 3 tracks, one of which is Healthcare-focused. In this track there will be three presentations, all of which discuss how Enterprise Architecture and the approach to Boundaryless Information Flow can help healthcare and healthcare decision-makers become more effective and efficient.

One presentation will focus on the transformation of care delivery at the Visiting Nurse Service of New York. Another will address stewarding healthcare transformation using Enterprise Architecture, focusing on one of our Platinum members, Oracle, and a company called Intelligent Medical Objects, and how they’re working together in a productive way, bringing IT and healthcare decision-making together.

Then, the final presentation in this track will focus on the development of an Enterprise Architecture-based solution at an insurance company. The payers, or the insurers–the big companies that are responsible for paying bills and collecting premiums–have a very important role in the healthcare system that extends beyond administration of benefits. Yet, payers are not always recognized for their key responsibilities and capabilities in the area of clinical improvements and cost improvements.

With the increase in payer data brought on in large part by the adoption of a new coding system–the ICD-10–which will come online this year, there will be a huge amount of additional data, including clinical data, that become available. At The Open Group, we consider payers—health insurance companies (some of which are integrated with providers)–as very important stakeholders in the big picture..

In the afternoon, we’re going to switch gears a bit and have a speaker talk about the challenges, the barriers, the “pain points” in introducing new technology into the healthcare systems. The focus will return to remote or mobile medical devices and the predictable but challenging barriers to getting newly generated health information to flow to doctors’ offices and into patients records, electronic health records, and hospitals data keeping and data sharing systems.

We’ll have a panel of experts that responds to these pain points, these challenges, and then we’ll draw heavily from the audience, who we believe will be very, very helpful, because they bring a great deal of expertise in guiding us in our work. So we’re very much looking forward to the afternoon as well.

Gardner: It’s really interesting. A couple of these different plenaries and discussions in the afternoon come back to this user-generated data. Jason, we really seem to be on the cusp of a whole new level of information that people will be able to develop from themselves through their lifestyle, new devices that are connected.

We hear from folks like Apple, Samsung, Google, and Microsoft. They’re all pulling together information and making it easier for people to not only monitor their exercise, but their diet, and maybe even start to use sensors to keep track of blood sugar levels, for example.

In fact, a new Flurry Analytics survey showed 62 percent increase in the use of health and fitness application over the last six months on the popular mobile devices. This compares to a 33 percent increase in other applications in general. So there’s an 87 percent faster uptick in the use of health and fitness applications.

Tell me a little bit how you see this factoring in. Is this a mixed blessing? Will so much data generated from people in addition to the electronic medical records, for example, be a bad thing? Is this going to be a garbage in, garbage out, or is this something that could potentially be a game-changer in terms of how people react to their own data and then bring more data into the interactions they have with care providers?

Lee: It’s always a challenge to predict what the market is going to do, but I think that’s a remarkable statistic that you cited. My prediction is that the increased volume of person- generated data from mobile health devices is going to be a game-changer. This view also reflects how the Healthcare Forum members (which includes members from Capgemini, Philips, IBM, Oracle and HP) view the future.

The commercial demand for mobile medical devices, things that can be worn, embedded, or swallowed, as in pills, as you mentioned, is growing ever more. The software and the applications that will be developed to be used with the devices is going to grow by leaps and bounds. As you say, there are big players getting involved. Already some of the pedometer type devices that measure the number of steps taken in a day have captured the interest of many, many people. Even David Sedaris, serious guy that he is, was writing about it recently in ‘The New Yorker’.

What we will find is that many of the health indicators that we used to have to go to the doctor or nurse or lab to get information on will become available to us through these remote devices.

There will be a question, of course, as to reliability and validity of the information, to your point about garbage in, garbage out, but I think standards development will help here This, again, is where The Open Group comes in. We might also see the FDA exercising its role in ensuring safety here, as well as other organizations, in determining which devices are reliable.

The Open Group is working in the area of mobile data and information systems that are developed around them, and their ability to (a) talk to one another and (b) talk to the data devices/infrastructure used in doctors’ offices and in hospitals. This is called interoperability and it’s certainly lacking in the country.

There are already problems around interoperability and connectivity of information in the healthcare establishment as it is now. When patients and consumers start collecting their own data, and the patient is put at the center of the nexus of healthcare, then the question becomes how does that information that patients collect get back to the doctor/clinician in ways in which the data can be trusted and where the data are helpful?

After all, if a patient is wearing a medical device, there is the opportunity to collect data, about blood sugar level let’s say, throughout the day. And this is really taking healthcare outside of the four walls of the clinic and bringing information to bear that can be very, very useful to clinicians and beneficial to patients.

In short, the rapid market dynamic in mobile medical devices and in the software and hardware that facilitates interoperability begs for standards-based solutions that reduce costs and improve quality, and all of which puts the patient at the center. This is The Open Group’s Healthcare Forum’s sweet spot.

Gardner: It seems to me a real potential game-changer as well, and that something like Boundaryless Information Flow and standards will play an essential role. Because one of the big question marks with many of the ailments in a modern society has to do with lifestyle and behavior.

So often, the providers of the care only really have the patient’s responses to questions, but imagine having a trove of data at their disposal, a 360-degree view of the patient to then further the cause of understanding what’s really going on, on a day-to-day basis.

But then, it’s also having a two-way street, being able to deliver perhaps in an automated fashion reinforcements and incentives, information back to the patient in real-time about behavior and lifestyles. So it strikes me as something quite promising, and I look forward to hearing more about it at the Boston conference.

Any other thoughts on this issue about patient flow of data, not just among and between providers and payers, for example, or providers in an ecosystem of care, but with the patient as the center of it all, as you said?

Lee: As more mobile medical devices come to the market, we’ll find that consumers own multiple types of devices at least some of which collect multiple types of data. So even for the patient, being at the center of their own healthcare information collection, there can be barriers to having one device talk to the other. If a patient wants to keep their own personal health record, there may be difficulties in bringing all that information into one place.

So the interoperability issue, the need for standards, guidelines, and voluntary consensus among stakeholders about how information is represented becomes an issue, not just between patients and their providers, but for individual consumers as well.

Gardner: And also the cloud providers. There will be a variety of large organizations with cloud-modeled services, and they are going to need to be, in some fashion, brought together, so that a complete 360-degree view of the patient is available when needed. It’s going to be an interesting time.

Of course, we’ve also looked at many other industries and tried to have a cloud synergy, a cloud-of-clouds approach to data and also the transaction. So it’s interesting how what’s going on in multiple industries is common, but it strikes me that, again, the scale and the impact of the healthcare industry makes it a leader now, and perhaps a driver for some of these long overdue structured and standardized activities.

Lee: It could become a leader. There is no question about it. Moreover, there is a lot Healthcare can learn from other companies, from mistakes that other companies have made, from lessons they have learned, from best practices they have developed (both on the content and process side). And there are issues, around security in particular, where Healthcare will be at the leading edge in trying to figure out how much is enough, how much is too much, and what kinds of solutions work.

There’s a great future ahead here. It’s not going to be without bumps in the road, but organizations like The Open Group are designed and experienced to help multiple stakeholders come together and have the conversations that they need to have in order to push forward and solve some of these problems.

Gardner: Well, great. I’m sure there will be a lot more about how to actually implement some of those activities at the conference. Again, that’s going to be in Boston, beginning on July 21, 2014.

We’ll have to leave it there. We’re about out of time. We’ve been talking with a new Director at The Open Group to learn how an expected continued deluge of data and information about patients and providers, outcomes and efficiencies are all working together to push the Healthcare industry to rapid change. And, as we’ve heard, that might very well spill over into other industries as well.

So we’ve seen how innovation and adaptation around technology, Enterprise Architecture and standards can improve the communication and collaboration among Healthcare ecosystem players.

It’s not too late to register for The Open Group Boston 2014 (http://www.opengroup.org/boston2014) and join the conversation via Twitter #ogchat #ogBOS, where you will be able to learn more about Boundaryless Information Flow, Open Platform 3.0, Healthcare and other relevant topics.

So a big thank you to our guest. We’ve been joined by Jason Lee, Healthcare and Security Forums Director at The Open Group. Thanks so much, Jason.

Lee: Thank you very much.

 

 

 

 

 

 

 

 

 

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The Power of APIs – Join The Open Group Tweet Jam on Wednesday, July 9th

By Loren K. Baynes, Director, Global Marketing Communications, The Open Group

The face of technology is evolving at breakneck speed, driven by demand from consumers and businesses alike for more robust, intuitive and integrated service offerings. APIs (application programming interfaces) have made this possible by offering greater interoperability between otherwise disparate software and hardware systems. While there are clear benefits to their use, how do today’s security and value-conscious enterprises take advantage of this new interoperability without exposing them themselves?

On Wednesday, July 9th at 9:00 am PT/12:00 pm ET/5:00 pm GMT, please join us for a tweet jam that will explore how APIs are changing the face of business today, and how to prepare for their implementation in your enterprise.

APIs are at the heart of how today’s technology communicates with one another, and have been influential in enabling new levels of development for social, mobility and beyond. The business benefits of APIs are endless, as are the opportunities to explore how they can be effectively used and developed.

There is reason to maintain a certain level of caution, however, as recent security issues involving open APIs have impacted overall confidence and sustainability.

This tweet jam will look at the business benefits of APIs, as well as potential vulnerabilities and weak points that you should be wary of when integrating them into your Enterprise Architecture.

We welcome The Open Group members and interested participants from all backgrounds to join the discussion and interact with our panel of thought-leaders from The Open Group including Jason Lee, Healthcare and Security Forums Director; Jim Hietala, Vice President of Security; David Lounsbury, CTO; and Dr. Chris Harding, Director for Interoperability and Open Platform 3.0™ Forum Director. To access the discussion, please follow the hashtag #ogchat during the allotted discussion time.

Interested in joining The Open Group Security Forum? Register your interest, here.

What Is a Tweet Jam?

A tweet jam is a 45 minute “discussion” hosted on Twitter. The purpose of the tweet jam is to share knowledge and answer questions on relevant and thought-provoking issues. Each tweet jam is led by a moderator and a dedicated group of experts to keep the discussion flowing. The public (or anyone using Twitter interested in the topic) is encouraged to join the discussion.

Participation Guidance

Here are some helpful guidelines for taking part in the tweet jam:

  • Please introduce yourself (name, title and organization)
  • Use the hashtag #ogchat following each of your tweets
  • Begin your tweets with the question number to which you are responding
  • Please refrain from individual product/service promotions – the goal of the tweet jam is to foster an open and informative dialogue
  • Keep your commentary focused, thoughtful and on-topic

If you have any questions prior to the event or would like to join as a participant, please contact George Morin (@GMorin81 or george.morin@hotwirepr.com).

We look forward to a spirited discussion and hope you will be able to join!

 

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