Tag Archives: information technology

Risk, Security and the Internet of Things: Madrid 2015 Preview

By Jim Hietala, Vice President, Business Development & Security, The Open Group

The Internet of Things (IoT) is a fast evolving phenomenon. From smartphones and tablets to connected cars and industrial control systems, the number of IoT devices is continuing to explode. In fact, according to a report by Cisco, the number of connected devices is set to reach 30 billion in 2020, creating a $19 trillion opportunity for businesses around the world.

However as this technology grows, it’s important to consider the potential risks that IoT could introduce to the enterprise and even to society. To put it simply, not much is being done at the moment in terms of IoT security.

The risks brought about by IoT aren’t just restricted to industries handling highly-sensitive personal data, such as Healthcare. Look at industries like energy, transport, manufacturing and mining, which are all starting to report the benefits of IoT ranging from faster time to market, better equipment efficiency and improved productivity. In any industrial setting, if high-value IoT data that gives an organization a competitive advantage was to leave the company, it could have serious consequences.

Arguably there are many vendors producing IoT enabled devices which are not taking risk or basic security mechanisms into account. Vendors are putting Internet Protocols (IPs) onto devices without any consideration about how to properly secure them. It’s fair to say, there are currently more problems than solutions.

This is happening, and it’s happening fast. As IoT technology continues to race way ahead, security standards are trying to catch up. Currently, there isn’t a consensus around the right way to secure the vast number of connected devices.

It’s important that we as an industry get to grips with IoT Security and start to apply a common sense strategy as soon as possible. That’s why we want people to start thinking about the risks and where best practices are lacking, a key issue we’ll be discussing at The Open Group Madrid 2015.

We’ll be exploring the implications of IoT from the standpoint of Security and Risk, looking at the areas where work will need to be done and where The Open Group Security Forum can help. What are the burning issues in each vertical industry – from retail to Healthcare – and what is the best way to identify the key IoT-enabled assets that need securing?

As organizations start to permit IoT-enabled equipment, whether it’s connected cars or factory equipment, IT departments need to consider the Security requirements of those networks. From a Security Architecture point of view, it’s vital that organizations do everything in their power to ensure they meet customers’ needs.

Registration for The Open Group Madrid 2015 is open now and available to members and non-members.  Please visit here.

By Jim Hietala, The Open GroupJim Hietala, Open FAIR, CISSP, GSEC, is Vice President, Business Development and Security for The Open Group, where he manages the business team, as well as Security and Risk Management programs and standards activities,  He has participated in the development of several industry standards including O-ISM3, O-ESA, O-RT (Risk Taxonomy Standard), O-RA (Risk Analysis Standard), and O-ACEML. He also led the development of compliance and audit guidance for the Cloud Security Alliance v2 publication.

Jim is a frequent speaker at industry conferences. He has participated in the SANS Analyst/Expert program, having written several research white papers and participated in several webcasts for SANS. He has also published numerous articles on information security, risk management, and compliance topics in publications including CSO, The ISSA Journal, Bank Accounting & Finance, Risk Factor, SC Magazine, and others.

An IT security industry veteran, he has held leadership roles at several IT security vendors.

Jim holds a B.S. in Marketing from Southern Illinois University.

Join the conversation @theopengroup #ogchat #ogMAD


Filed under Information security, Internet of Things, RISK Management, Security, Security Architecture, Uncategorized

Enabling the Boundaryless Organization the Goal of The Open Group Madrid Summit 2015

The Open Group, the global vendor-neutral IT consortium, is hosting its latest event in Madrid April 20 – 23 2015. The event is set to build on the success of previous events and focus on the challenge of building a Boundaryless Organization in the face of a range of new IT trends. As organizations look to take advantage of trends such as the Internet of Things and Open Platform 3.0™, the Madrid event will be an opportunity for peers to present and discuss and how the Boundaryless Organization can be achieved and what methods are best to do so.

Objectives of this year’s conference include:

  • Understanding what role Enterprise Architecture as currently practiced plays in Enterprise Transformation, especially transformations driven by merging and disruptive technologies.
  • Showing the need for Boundaryless Information Flow™, which would result in more interoperable, real-time business processes that span throughout all business ecosystems.
  • Understanding how to develop better interoperability and communication across organizational boundaries and pursue global standards for Enterprise Architecture that are highly relevant to all industries.
  • Showing how organizations can achieve their business objectives by adopting new technologies and processes as part of the Enterprise Transformation management principles – making the whole process more a matter of design than of chance.
  • Examining how the growth of “The Internet of Things” with online currencies and mobile enabled transactions has changed the face of financial services, and poses new threats and opportunities.

Key plenary and track speakers at the event include:

  • Allen Brown, President & CEO, The Open Group
  • Ron Tolido, SVP, Group CTO Office, , Global Insights and Data practice, Capgemini
  • Mariano Arnaiz, CIO, Grupo CESCE
  • Domingo Molina, Director of Information Technology and Communication Management, CNIS

Full details on the event agenda can be found here.

Registration for The Open Group Madrid is open now and available to members and non-members.  Please visit here.

Join the conversation! @theopengroup #ogMAD

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Filed under big data, Boundaryless Information Flow™, Enterprise Architecture, Internet of Things, Interoperability, Open Platform 3.0, OTTF, Professional Development, RISK Management, Standards, Strategy, TOGAF

A World Without IT4IT: Why It’s Time to Run IT Like a Business

By Dave Lounsbury, CTO, The Open Group

IT departments today are under enormous pressure. In the digital world, businesses have become dependent on IT to help them remain competitive. However, traditional IT departments have their roots in skills such as development or operations and have not been set up to handle a business and technology environment that is trying to rapidly adapt to a constantly changing marketplace. As a result, many IT departments today may be headed for a crisis.

At one time, IT departments led technology adoption in support of business. Once a new technology was created—departmental servers, for instance—it took a relatively long time before businesses took advantage of it and even longer before they became dependent on the technology. But once a business did adopt the technology, it became subject to business rules—expectations and parameters for reliability, maintenance and upgrades that kept the technology up to date and allowed the business it supported to keep up with the market.

As IT became more entrenched in organizations throughout the 1980s and 1990s, IT systems increased in size and scope as technology companies fought to keep pace with market forces. In large enterprises, in particular, IT’s function became to maintain large infrastructures, requiring small armies of IT workers to sustain them.

A number of forces have combined to change all that. Today, most businesses do their business operations digitally—what Constellation Research analyst Andy Mulholland calls “Front Office Digital Business.” Technology-as-a-service models have changed how the technologies and applications are delivered and supported, with support and upgrades coming from outsourced vendors, not in-house staff. With Cloud models, an IT department may not even be necessary. Entrepreneurs can spin up a company with a swipe of a credit card and have all the technology they need at their fingertips, hosted remotely in the Cloud.

The Gulf between IT and Business

Although the gap between IT and business is closing, the gulf in how IT is run still remains. In structure, most IT departments today remain close to their technology roots. This is, in part, because IT departments are still run by technologists and engineers whose primary skills lie in the challenge (and excitement) of creating new technologies. Not every skilled engineer makes a good businessperson, but in most organizations, people who are good at their jobs often get promoted into management whether or not they are ready to manage. The Peter Principle is a problem that hinders many organizations, not just IT departments.

What has happened is that IT departments have not traditionally been run as if they were a business. Good business models for how IT should be run have been piecemeal or slow to develop—despite IT’s role in how the rest of the business is run. Although some standards have been developed as guides for how different parts of IT should be run (COBIT for governance, ITIL for service management, TOGAF®, an Open Group standard, for architecture), no overarching standard has been developed that encompasses how to holistically manage all of IT, from systems administration to development to management through governance and, of course, staffing. For all its advances, IT has yet to become a well-oiled business machine.

The business—and technological—climate today is not the same as it was when companies took three years to do a software upgrade. Everything in today’s climate happens nearly instantaneously. “Convergence” technologies like Cloud Computing, Big Data, social media, mobile and the Internet of Things are changing the nature of IT. New technical skills and methodologies are emerging every day, as well. Although languages such as Java or C may remain the top programming languages, new languages like Pig or Hive are emerging everyday, as are new approaches to development, such as Scrum, Agile or DevOps.

The Consequences of IT Business as Usual

With these various forces facing IT, departments will either need to change and adopt a model where IT is managed more effectively or departments may face some impending chaos that ends up hindering their organizations.

Without an effective management model for IT, companies won’t be able to mobilize quickly for a digital age. Even something as simple as an inability to utilize data could result in problems such as investing in a product prototype that customers aren’t interested in. Those are mistakes most companies can’t afford to make these days.

Having an umbrella view of what all of IT does also allows the department to make better decisions. With technology and development trends changing so quickly, how do you know what will fit your organization’s business goals? You want to take advantage of the trends or technologies that make sense for the company and leave behind those that don’t.

For example, in DevOps, one of the core concepts is to bring the development phase into closer alignment with releasing and operating the software. You need to know your business’s operating model to determine whether this approach will actually work or not. Having a sense of that also allows IT to make decisions about whether it’s wise to invest in training or hiring staff skilled in those methods or buying new technologies that will allow you to adopt the model.

Not having that management view can leave companies subject to the whims of technological evolution and also to current IT fads. If you don’t know what’s valuable to your business, you run the risk of chasing every new fad that comes along. There’s nothing worse—as the IT guy—than being the person who comes to the management meeting each month saying you’re trying yet another new approach to solve a problem that never seems to get solved. Business people won’t respond to that and will wonder if you know what you’re doing. IT needs to be decisive and choose wisely.

These issues not only affect the IT department but to trickle up to business operations. Ineffective IT shops will not know when to invest in the correct technologies, and they may miss out on working with new technologies that could benefit the business. Without a framework to plan how technology fits into the business, you could end up in the position of having great IT bows and arrows but when you walk out into the competitive world, you get machine-gunned.

The other side is cost and efficiency—if the entire IT shop isn’t running smoothly throughout then you end up spending too much money on problems, which in turn takes money away from other parts of the business that can keep the organization competitive. Failing to manage IT can lead to competitive loss across numerous areas within a business.

A New Business Model

To help prevent the consequences that may result if IT isn’t run more like a business, industry leaders such as Accenture; Achmea; AT&T; HP IT; ING Bank; Munich RE; PwC; Royal Dutch Shell; and University of South Florida, recently formed a consortium to address how to better run the business of IT. With billions of dollars invested in IT each year, these companies realized their investments must be made wisely and show governable results in order succeed.

The result of their efforts is The Open Group IT4IT™ Forum, which released a Snapshot of its proposed Reference Architecture for running IT more like a business this past November. The Reference Architecture is meant to serve as an operating model for IT, providing the “missing link” that previous IT-function specific models have failed to address. The model allows IT to achieve the same level of business, discipline, predictability and efficiency as other business functions.

The Snapshot includes a four-phase Value Chain for IT that provides both an operating model for an IT business and outlines how value can be added at every stage of the IT process. In addition to providing suggested best practices for delivery, the Snapshot includes technical models for the IT tools that organizations can use, whether for systems monitoring, release monitoring or IT point solutions. Providing guidance around IT tools will allow these tools to become more interoperable so that they can exchange information at the right place at the right time. In addition, it will allow for better control of information flow between various parts of the business through the IT shop, thus saving IT departments the time and hassle of aggregating tools or cobbling together their own tools and solutions. Staffing guidance models are also included in the Reference Architecture.

Why IT4IT now? Digitalization cannot be held back, particularly in an era of Cloud, Big Data and an impending Internet of Things. An IT4IT Reference Architecture provides more than just best practices for IT—it puts IT in the context of a business model that allows IT to be a contributing part of an enterprise, providing a roadmap for digital businesses to compete and thrive for years to come.

Join the conversation! @theopengroup #ogchat

By The Open GroupDavid is Chief Technical Officer (CTO) and Vice President, Services for The Open Group. As CTO, he ensures that The Open Group’s people and IT resources are effectively used to implement the organization’s strategy and mission.  As VP of Services, David leads the delivery of The Open Group’s proven collaboration processes for collaboration and certification both within the organization and in support of third-party consortia.

David holds a degree in Electrical Engineering from Worcester Polytechnic Institute, and is holder of three U.S. patents.


Filed under Cloud, digital technologies, Enterprise Transformation, Internet of Things, IT, IT4IT, TOGAF, TOGAF®

Putting Information Technology at the Heart of the Business: The Open Group San Diego 2015

By The Open Group

The Open Group is hosting the “Enabling Boundaryless Information Flow™” event February 2 – 5, 2015 in San Diego, CA at the Westin San Diego Gaslamp Quarter. The event is set to focus on the changing role of IT within the enterprise and how new IT trends are empowering improvements in businesses and facilitating Enterprise Transformation. Key themes include Dependability through Assuredness™ (The Cybersecurity Connection) and The Synergy of Enterprise Architecture Frameworks. Particular attention throughout the event will be paid to the need for continued development of an open TOGAF® Architecture Development Method and its importance and value to the wider business architecture community. The goal of Boundaryless Information Flow will be featured prominently in a number of tracks throughout the event.

Key objectives for this year’s event include:

  • Explore how Cybersecurity and dependability issues are threatening business enterprises and critical infrastructure from an integrity and a Security perspective
  • Show the need for Boundaryless Information Flow™, which would result in more interoperable, real-time business processes throughout all business ecosystems
  • Outline current challenges in securing the Internet of Things, and about work ongoing in the Security Forum and elsewhere that will help to address the issues
  • Reinforce the importance of architecture methodologies to assure your enterprise is transforming its approach along with the ever-changing threat landscape
  • Discuss the key drivers and enablers of social business technologies in large organizations which play an important role in the co-creation of business value, and discuss the key building blocks of social business transformation program

Plenary speakers at the event include:

  • Chris Forde, General Manager, Asia Pacific Region & VP, Enterprise Architecture, The Open Group
  • John A. Zachman, Founder & Chairman, Zachman International, and Executive Director of FEAC Institute

Full details on the range of track speakers at the event can be found here, with the following (among many others) contributing:

  • Dawn C. Meyerriecks, Deputy Director for Science and Technology, CIA
  • Charles Betz, Founder, Digital Management Academy
  • Leonard Fehskens. Chief Editor, Journal of Enterprise Architecture, AEA

Registration for The Open Group San Diego 2015 is open and available to members and non-members. Please register here.

Join the conversation via Twitter – @theopengroup #ogSAN



Filed under Boundaryless Information Flow™, Dependability through Assuredness™, Internet of Things, Professional Development, Security, Standards, TOGAF®, Uncategorized

Business Benefit from Public Data

By Dr. Chris Harding, Director for Interoperability, The Open Group

Public bodies worldwide are making a wealth of information available, and encouraging its commercial exploitation. This sounds like a bonanza for the private sector at the public expense, but entrepreneurs are holding back. A healthy market for products and services that use public-sector information would provide real benefits for everyone. What can we do to bring it about?

Why Governments Give Away Data

The EU directive of 2003 on the reuse of public sector information encourages the Member States to make as much information available for reuse as possible. This directive was revised and strengthened in 2013. The U.S. Open Government Directive of 2009 provides similar encouragement, requiring US government agencies to post at least three high-value data sets online and register them on its data.gov portal. Other countries have taken similar measures to make public data publicly available.

Why are governments doing this? There are two main reasons.

One is that it improves the societies that they serve and the governments themselves. Free availability of information about society and government makes people more effective citizens and makes government more efficient. It illuminates discussion of civic issues, and points a searchlight at corruption.

The second reason is that it has a positive effect on the wealth of nations and their citizens. The EU directive highlights the ability of European companies to exploit the potential of public-sector information, and contribute to economic growth and job creation. Information is not just the currency of democracy. It is also the lubricant of a successful economy.

Success Stories

There are some big success stories.

If you drive a car, you probably use satellite navigation to find your way about, and this may use public-sector information. In the UK, for example, map data that can be used by sat-nav systems is supplied for commercial use by a government agency, the Ordnance Survey.

When you order something over the web for delivery to your house, you often enter a postal code and see most of the address auto-completed by the website. Postcode databases are maintained by national postal authorities, which are generally either government departments or regulated private corporations, and made available by them for commercial use. Here, the information is not directly supporting a market, but is contributing to the sale of a range of unrelated products and services.

The data may not be free. There are commercial arrangements for supply of map and postcode data. But it is available, and is the basis for profitable products and for features that make products more competitive.

The Bonanza that Isn’t

These successes are, so far, few in number. The economic benefits of open government data could be huge. The McKinsey Global Institute estimates a potential of between 3 and 5 trillion dollars annually. Yet the direct impact of Open Data on the EU economy in 2010, seven years after the directive was issued, is estimated by Capgemini at only about 1% of that, although the EU accounts for nearly a quarter of world GDP.

The business benefits to be gained from using map and postcode data are obvious. There are other kinds of public sector data, where the business benefits may be substantial, but they are not easy to see. For example, data is or could be available about public transport schedules and availability, about population densities, characteristics and trends, and about real estate and land use. These are all areas that support substantial business activity, but businesses in these areas seldom make use of public sector information today.

Where are the Products?

Why are entrepreneurs not creating these potentially profitable products and services? There is one obvious reason. The data they are interested in is not always available and, where it is available, it is provided in different ways, and comes in different formats. Instead of a single large market, the entrepreneur sees a number of small markets, none of which is worth tackling. For example, the market for an application that plans public transport journeys across a single town is not big enough to justify substantial investment in product development. An application that could plan journeys across any town in Europe would certainly be worthwhile, but is not possible unless all the towns make this data available in a common format.

Public sector information providers often do not know what value their data has, or understand its applications. Working within tight budgets, they cannot afford to spend large amounts of effort on assembling and publishing data that will not be used. They follow the directives but, without common guidelines, they simply publish whatever is readily to hand, in whatever form it happens to be.

The data that could support viable products is not available everywhere and, where it is available, it comes in different formats. (One that is often used is PDF, which is particularly difficult to process as an information source.) The result is that the cost of product development is high, and the expected return is low.

Where is the Market?

There is a second reason why entrepreneurs hesitate. The shape of the market is unclear. In a mature market, everyone knows who the key players are, understands their motivations, and can predict to some extent how they will behave. The market for products and services based on public sector information is still taking shape. No one is even sure what kinds of organization will take part, or what they will do. How far, for example, will public-sector bodies go in providing free applications? Can large corporations buy future dominance with loss-leader products? Will some unknown company become an overnight success, like Facebook? With these unknowns, the risks are very high.

Finding the Answers

Public sector information providers and standards bodies are tackling these problems. The Open Group participates in SHARE-PSI, the European network for the exchange of experience and ideas around implementing open data policies in the public sector. The experience gained by SHARE-PSI will be used by the World-Wide Web Consortium as a basis for standards and guidelines for publication of public sector information. These standards and guidelines may be used, not just by the public sector, but by not-for-profit bodies and even commercial corporations, many of which have information that they want to make freely available.

The Open Group is making a key contribution by helping to map the shape of the market. It is using the Business Scenario technique from its well-known Enterprise Architecture methodology TOGAF® to identify the kinds of organization that will take part, and their objectives and concerns.

There will be a preview of this on October 22 at The Open Group event in London which will feature a workshop session on Open Public Sector Data. This workshop will look at how Open Data can help business, present a draft of the Business Scenario, and take input from participants to help develop its conclusions.

The developed Business Scenario will be presented at the SHARE-PSI workshop in Lisbon on December 3-4. The theme of this workshop is encouraging open data usage by commercial developers. It will bring a wide variety of stakeholders together to discuss and build the relationship between the public and private sectors. It will also address, through collaboration with the EU LAPSI project, the legal framework for use of open public sector data.

Benefit from Participation!

If you are thinking about publishing or using public-sector data, you can benefit from these workshops by gaining an insight into the way that the market is developing. In the long term, you can influence the common standards and guidelines that are being developed. In the short term, you can find out what is happening and network with others who are interested.

The social and commercial benefits of open public-sector data are not being realized today. They can be realized through a healthy market in products and services that process the data and make it useful to citizens. That market will emerge when public bodies and businesses clearly understand the roles that they can play. Now is the time to develop that understanding and begin to profit from it.

Register for The Open Group London 2014 event at http://www.opengroup.org/london2014/registration.

Find out how to participate in the Lisbon SHARE-PSI workshop at http://www.w3.org/2013/share-psi/workshop/lisbon/#Participation


Chris HardingDr. Chris Harding is Director for Interoperability at The Open Group. He has been with The Open Group for more than ten years, and is currently responsible for managing and supporting its work on interoperability, including SOA and interoperability aspects of Cloud Computing, and the Open Platform 3.0™ Forum. He is a member of the BCS, the IEEE and the AEA, and is a certified TOGAF® practitioner.

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Filed under big data, Cloud, digital technologies, Enterprise Architecture, Open Platform 3.0, TOGAF®, Uncategorized

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.


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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Filed under Boundaryless Information Flow™, Business Architecture, Cloud, Cloud/SOA, Data management, digital technologies, Enterprise Architecture, Future Technologies, Information security, Internet of Things, Interoperability, Open Platform 3.0, Service Oriented Architecture, Standards, Strategy, Supply chain risk, Uncategorized

Enterprise Architecture: A Practitioner View

By Prasad Palli and Dr. Gopala Krishna Behara, Wipro

Overview of Enterprise Architecture

IT organizations as usual are always ready to take challenges and start the journey in defining/refining their IT strategies and aligning with business strategies. During this journey, enterprises adopt a framework / methodology / best-practice / pattern / process called “Enterprise Architecture” which will help them to structure their processes and address growth together.

The effective management and exploitation of information through IT is a key factor to business success, and an indispensable means to achieving competitive advantage. Enterprise Architecture addresses this need, by providing a strategic context for the evolution of the IT system in response to the constantly changing needs of the business environment.

Without Enterprise Architecture

Based on our experience in Enterprise Architecture consulting, we highlight the common mistakes/frequent issues faced by the organizations in the absence of Enterprise Architecture.


  • No link to business strategic planning and budget process
  • Slow and ineffective decision-making
  • Inability to rapidly respond to changes driven by business challenges
  • Lack of focus on enterprise requirements
  • Lack of common direction and synergies
  • Focusing on the art or language of EA rather than outcomes
  • Incomplete visibility of the current and future target Enterprise Architecture vision


  • Inability to predict impacts of future changes
  • Confusing “IT Architecture” With “Enterprise Architecture”
  • Lack of governance
  • Strict following of EA frameworks
  • “Ivory Tower” approach
  • Lack of communication and feedback
  • Limiting the EA team to IT resources
  • Lack of performance measures
  • No measurement criteria for EA metrics
  • Picking a tool before understanding your business needs


  • Increased gaps and architecture conflicts
  • Lack of commonality and consistency due to the absence of standards
  • Dilution and dissipation of critical information and knowledge of the deployed solutions
  • Rigidity, redundancy and lack of scalability and flexibility in the deployed solutions
  • Over-standardization
  • Non-adoption of Next Generation Technologies
  • Lack of integration, compatibility and interoperability between applications
  • Complex, fragile and costly interfaces between incongruent application

Enterprise Architecture Perspective

The main drivers of Enterprise Architecture of the enterprise are:

  • Highly optimized and flexible processes (Business & IT)
  • Ability to integrate seamlessly with systems within the enterprise and partners
  • Highly optimized and shared IT infrastructure
  • Loosely coupled systems to quickly respond to new processes or new product or new channel – Business value generation
  • Well mapping of business processes to application to information to technology
  • Strict adherence to regulatory and compliance factors

This article highlights our framework of Enterprise Architecture and its roadmap for the development and management of various components. It depicts how these components work together, what are the various measures of business units, enterprise and their outcome. The framework includes putting in place the proper organizational structure and hybrid business/IT roles, consolidating and standardizing information and data stores, and integrating applications and infrastructure to support the right business processes across the enterprise.

The key Components of Enterprise Architecture are depicted below.


EA – Practical Experience

Enterprise Architecture is not a one-time event, nor limited to specific projects or business units. EA is an on-going, iterative process that provides:

  • A common vision of the future shared by business and IT; business aware of IT and vice-versa
  • Guidance in the selection, creation and implementation of solutions driven by business requirements
  • Support for the various enterprise business lines through improved information sharing – provides plan for the integration of information and services at the design level across business lines
  • A means to control growing complexities of technology by setting enterprise-wide, leverageable standards for information technology
  • Defines an approach for the evaluation, consideration and assimilation of new and emerging technology innovations to meet business requirements

Some of the key aspects that teams will come across during EA execution:

  • EA is NOT a project: This is one of common mistake that most enterprises do. Enterprise Architecture is NOT a project, which can be delivered within specified timeframe. Enterprise Architecture is more of a culture that enterprises must adopt like SDLC process.
  • EA is NOT about review : Generally, people tend to think that EA is always for review and do policing team/individual performance and provide review reports to higher management. Instead EA is of bringing standards and making enterprise flexible to address changes as needed for business growth.
  • EA is NOT a one-time activity: The success of EA is possible only when enterprises will adopt it as part of their culture. For this to happen, Enterprise Architecture should execute as an iterative and on-going process and educate all stakeholders (business, portfolio managers, architects, program/project managers, designers, developers, operations, partners etc.) about the initiative and make them responsible for EA success.
  • EA is NOT for IT: Most of the times Enterprise Architecture initiative is driven by IT organizations without much involvement from Business. This is the first step towards a big failure. Depending upon the approach (whether it is top-down or bottom-up), business should be aware of what’s happening in the Enterprise Architecture initiative and be actively participating in the program when needed. Business is as equally responsible as IT for the success of an EA initiative.
  • EA is NOT a strategy: There is a common view across organizations that Enterprise Architecture is more of a strategy and teams like solution architecture, portfolio management and design & development and operations streams doesn’t have a role to play. In fact, the aforementioned teams are key contributors to Enterprise Architecture definition and its success by inculcating EA standards and best practices in their day-to-day activities.
  • EA is NOT all about cost-reduction: Most of the enterprises will look at EA from cost savings perspective that puts lot of pressure on IT to show some immediate benefits in terms of savings. With this kind of pressure, EA will get off track and be seen as more of a tactical initiative rather than strategic. Enterprises should start looking at EA more from Business-IT alignment, agility, innovation etc. which are strategic in nature along with cost savings.
  • EA is NOT one-man show: Enterprise Architecture is neither a CIO job or CFO or any CXO. It’s everybody’s job within an enterprise. During the EA strategy definition phase, probably more leadership involvement is needed and at EA implementation stage all the stakeholders will have a role to play and contribute one way or another.
  • EA is all about communication: One of the common mistakes that most enterprises do during the EA program is the team will work in silos and build huge pile of documents without having proper communication sessions within enterprise. At a minimum, the EA team should spend 50% of efforts towards communicating EA artifacts with the team and successful medium is through meetings rather than sending over emails or website.
  • Measure EA: During the initial stages of an EA program, the team should define measuring criteria/factors of EA (for ex: customer satisfaction, time to market, agility, cost savings, standardization, resources skills, trainings/certification etc.). Without these factors defined, EA will end up in ad-hoc planning which leads to chaos and frustrates leadership.
  • Adoption of Latest Technology Trends on EA: Traditional EA is more of the “Ivory Tower” approach which is modeled as framework-centered and tool-driven. Most of the EA function is technology-centric and defined as a one-time initiative. Application built on Traditional EA principles are business-constraint before they are completed. The Next Generation Enterprise Architecture (NGEA) is business-centric, global, agile, continuous and social digital network. Also, the organizations adopt latest digital capabilities like social web, SOA, big data analytics, omni channel customer management, cloud computing, virtualization, Internet of Things and so on. These technologies are interrelated and fit together to define Next Generation Enterprise Architecture for an organization.

The vision of an enterprise is shifting from Traditional EA to Digital Architecture which addresses Networked Community Capabilities (interacting with users through social media), globalization (Borderless Enterprise), innovation of products and services (open, closed & virtual innovation), collaboration (enable employees in decision-making, location flexibility, schedule flexibility), flexibility (flexibility to choose the technologies, infrastructure, applications).

The following diagram shows the Next Generation EA Model.


  • Network-centric enterprise: Online communities, workforce (network/social collaboration), business partners, customers and the marketplace
  • Enterprise resources: Teams, project-centric, process-based work conducted by communities
  • Business partners: Strategic partners and suppliers can be engaged together in operations
  • Customers: Customer care communities
  • Outside enterprise: Regulators, influencers, crowdsourcing participants, software developers and other interested parties
  • Third party vendors: Packaged vendors like SAP, Oracle ERP etc.
  • New channels: Web, mobile devices, Social business environments (communities of all functional types and audiences) and CRM


This article attempts to demonstrate practical views of an Enterprise Architect in improving the success rate of EA across the organizations. There is no hard and fast rule that enterprises should adopt to one particular framework or standard or approach. They can choose to adopt any industry specific framework, however it can be customized as per the needs of the enterprise. It does not force fit EA programs to any industry framework. The deliverables of EA should integrate with business planning, focus on business architecture and defining/streamlining business outcome metrics.

EA program definition should not span for years. It should deliver business value in months or weeks. Also, the program output should be actionable. Always measure impact but not activity.

Apart from these steps, enterprise should think about following other key aspects like:

  • Should have strong leadership commitments
  • Not always as-Is instead it can start with defining future state
  • Start with the highest-priority business outcomes

Use the right diagnostic tools — EAs must have a broad set of tools to choose from:

  • Ensure the program outputs are actionable
  • Measure impact, not activity
  • Adopt Next Generation Enterprise Architecture patterns
  • Socialize, listen, crowd source and be transparent
  • Do not re-architect legacy systems for the sake of re-architecting: most old systems should be wrapped, then replaced
  • Prepare to measure degree of success before starting on with the new architecture initiative
  • Do not over-design your systems of innovation or under-design the systems of differentiation or record




The authors would like to thank Hari Kishan Burle, Raju Alluri of Architecture Group of Wipro Technologies for giving us the required time and support in many ways in bringing this article as part of Enterprise Architecture Practice efforts.


PalliPrasad Palli is a Practice Partner in the Enterprise Architecture division of Wipro. He has a total of 17 years of IT experience. He can be reached at prasad.palli@wipro.com


BeharaDr. Gopala Krishna Behara is a Senior Enterprise Architect in the Enterprise Architecture division of Wipro. He has a total of 18 years of IT experience. He can be reached at gopalkrishna.behra@wipro.com



The views expressed in this article/presentation are that of authors and Wipro does not subscribe to the substance, veracity or truthfulness of the said opinion.

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Filed under Enterprise Architecture, Enterprise Transformation, Governance, IT, Standards