The Context For EA Success Is Changing – Are You Changing For This New Context?

Alex Cullen

As architects, we all know the importance of context. The right architecture for one context – say, an organically growing company – doesn’t work for a company growing by acquisition. The right technology strategy for a medium-size American company doesn’t work for a China-based one. 

Well, the context for enterprise architecture itself is changing. We’ve got The Age Of The Customer forcing companies to transform outside-in. We have what is called technology consumerization – our business users have access to ever more powerful technology solutions independent of IT. We have digital-fueled business disruption, as described in James McQuivey’s book, Digital Disruption. And all this is driving the demand for greater business agility – the ability to quickly sense and adeptly respond to new opportunities and threats in their context.   

What a great opportunity for enterprise architecture programs! But this is only possible if they shift from a focus on cost to a focus on opportunity, change from controlling to enabling technology, and adapt their practices to the need for quickness with “just enough insight.”

If your EA program has seized these opportunities, made the changes, and is helping your business thrive, I’d like to invite you to submit your story for the InfoWorld/Forrester Enterprise Architecture Award.

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The Evolving Role Of Business Architecture

Derek Miers

Business architecture has become a bit of a watchword for organizations thinking about their future. It’s about all sorts of things – the “what” we do and “why” we do it. It’s about the “who with”, or more importantly “who for.” But it’s also about the “how we do it”, and “how we build engagement” to ensure we “do the right things,” rather than just “doing things right.”

Given that I focus on the methods and techniques that help organizations translate strategy into action (business architecture, process architecture, business engagement, etc.), I want to talk a little about the trends, methods and approaches that we see in the practice of business architecture.

I have to say recent engagements have been a real eye opener … some folks are very advanced in some areas – say capturing strategic intent, but then struggle to translate that into meaningful plans that energize colleagues in the business. Some are talking a good story of target operating models – focused around the experiences they deliver to their customers, but then miss the link to current day project portfolio that’s singularly focused on reducing the employee headcount. And as we saw in our recent BPM Suites Wave, business architecture principles are becoming more important at the process execution layer too.

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Avoid Becoming A One-trick Pony: Embrace Your Business' Need For Real-time

Brian  Hopkins

 

The term “one-trick pony” allegedly originated back in the 19th-century days of the traveling circus, where low-end ones were sarcastically called “dog and pony shows.” The really bad ones got the reputation of having a pony that only knew one trick. Today many IT shops are in danger of becoming like those sad circuses, having one or at least a very limited set of technology tricks to help their firms seize opportunities quickly. For example, I routinely talk to business people who say they avoid IT at all costs when they have new analytic needs; at these firms, IT has only one response to all new requests for data – update the data warehouse or a data mart in a slow and expensive waterfall development process.

One term keeps occurring, as I talk to businesses about this issue — they want to be real-time.  We’ve been using the term for years to talk about a wide range of things, from embedded C to extreme, low-latency analytics. I think all of these miss what the business is really after — the ability to use more information more quickly to take rapid action in response to unanticipated changes in their environment. Five-year technology strategies are out; but many can’t get their head around this new world, which is why a recent Forrester study showed that IT is increasingly losing control of technology spend. How do we get back in the game?

Companies like Barclays Wealth Management, Sears, and USAA are redefining their architecture with new tricks to be responsive in real-time by:

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Forrester Wave™: BPM Suites Grow Up And Move Beyond The Culture Wars

Clay Richardson

As some of you know, I’m a bit of a political junkie. I believe I picked up the political bug from years of riding shotgun with my dad as he listened to Rush Limbaugh blaring on the car radio. As a kid, I loved listening to Rush and trying to understand where he was coming from, trying to understand his perspective, trying to understand his ideology. The term “culture wars” in U.S. politics is used to define a clash between two different political ideologies – conservatism and liberalism.

Over the past few years, I’ve also started using the term “culture wars” to describe the clash and fragmentation we’ve seen in the BPM market. In the BPM space, the clash has primarily been around dynamic case management (DCM), human-centric workflow, and straight-through processing ideologies.

I’m the first to admit that fragmentation and categorization is not always a bad thing, since it can help software buyers and decision-makers better understand which solutions best match their business requirements and desired business outcomes. However, the fragmentation in BPM sometimes overlooks the primary purpose and value proposition of BPM – to help support creating a sustainable business change program.

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The Outcome Focus Of World Class EA Programs

Alex Cullen

I recently had a conversation with a new EA practice leaders in the investment management business unit of a large multi-line insurance company.  They wanted to hear my perspectives on what a world-class EA program should look like.  They knew of all the traditional EA building blocks: standards and roadmaps, architecture domains, methodologies like TOGAF.  They had a long list of things to do, but were uncertain about which to tackle first, and had a nagging feeling that these had little to do with world-class EA programs.  We touched on EA maturity models, but quickly concluded that there isn’t an obvious and compelling business value proposition to simply ‘being mature’. 

The conversation shifted to outcomes – what are the outcomes of a world-class EA program?  IT cost reduction could be an outcome, and has been the raison d’etre of EA for years.  IT solution design quality could be an outcome, and has been the justification for architects for longer than EA has been around.  But these are all IT-centric outcomes.

We all know the world is changing.  Digital capabilities are radically impacting our customers, the competitive landscape, the regulatory context, and the operating models of businesses.  Kyle McNabb summarizes this very well in his blog post.  The mantra today is business agility in the face of all these radical changes.  Because of this, being IT-centric is no longer the hallmark of a world class EA program. 

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Don't Establish Data Management Standards

Michele Goetz

A recent survey of Enterprise Architects showed a lack of standards for data management.* Best practices has always been about the creation of standards for IT, which would lead us to think that lack of standards for data management is a gap.

Not so fast.

Standards can help control cost. Standards can help reduce complexity. But, in an age when a data management architecture needs to flex and meet the business need for agility, standards are a barrier. The emphasis on standards is what keeps IT in a mode of constant foundation building, playing the role of deli counter, and focused on cost management.

In contrast, when companies throw off the straight jacket of data management standards the are no longer challenged by the foundation. These organizations are challenged by ceilings. Top performing organizations, those that have had annual growth above 15%, are working to keep the dam open and letting more data in and managing more variety. They are pushing the envelope on the technology that is available.

Think about this. Overall, organizations have made similar data management technology purchases. What has separated top performers from the rest of organizations is by not being constrained. Top performers maximize and master the technology they invest in. They are now better positioned to do more, expand their architecture, and ultimately grow data value. For big data, they have or are getting ready to step out of the sandbox. Other organizations have not seen enough value to invest more. They are in the sand trap.

Standards can help structure decisions and strategy, but they should never be barriers to innovation.

 

*203 Enterprise Architecture Professionals, State of Enterprise Architecture Global Survey Month,2012

**Top performer organization analysis based on data from Forrsights Strategy Spotlight BI And Big Data, Q4 2012

Don't Establish Data Management Standards

Michele Goetz

A recent survey of Enterprise Architects showed a lack of standards for data management.* Best practices has always been about the creation of standards for IT, which would lead us to think that lack of standards for data management is a gap.

Not so fast.

Standards can help control cost. Standards can help reduce complexity. But, in an age when a data management architecture needs to flex and meet the business need for agility, standards are a barrier. The emphasis on standards is what keeps IT in a mode of constant foundation building, playing the role of deli counter, and focused on cost management.

In contrast, when companies throw off the straight jacket of data management standards the are no longer challenged by the foundation. These organizations are challenged by ceilings. Top performing organizations, those that have had annual growth above 15%, are working to keep the dam open and letting more data in and managing more variety. They are pushing the envelope on the technology that is available.

Think about this. Overall, organizations have made similar data management technology purchases. What has separated top performers from the rest of organizations is by not being constrained. Top performers maximize and master the technology they invest in. They are now better positioned to do more, expand their architecture, and ultimately grow data value. For big data, they have or are getting ready to step out of the sandbox. Other organizations have not seen enough value to invest more. They are in the sand trap.

Standards can help structure decisions and strategy, but they should never be barriers to innovation.

 

*203 Enterprise Architecture Professionals, State of Enterprise Architecture Global Survey Month,2012

**Top performer organization analysis based on data from Forrsights Strategy Spotlight BI And Big Data, Q4 2012

What Master Data Management Metrics Matter?

Michele Goetz

I recently had a client ask about MDM measurement for their customer master.  In many cases, the discussions I have about measurement is how to show that MDM has "solved world hunger" for the organization.  In fact, a lot of the research and content out there focused on just that.  Great to create a business case for investment.  Not so good in helping with the daily management of master data and data governance.  This client question is more practical, touching upon:

  • what about the data do you measure?
  • how do you calculate?
  • how frequently do you report and show trends?
  • how do you link the calculation to something the business understands?
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Chief Data Officers Are A Good Idea -- But How Is That Going To Work?

Gene Leganza

It seems to be popular these days amongst industry pundits to recommend that organizations add a new Cxx role: the Chief Data Officer (CDO). The arguments in favor of this move are exactly what you'd think: the rapidly accelerating importance of information in the enterprise, and, as important, the heightened perception of the importance of information by business executives. The attention on information comes from all the rich new data that simply didn't exist before: sensor data from the Internet Of Things, social media, process data -- really just the enormous volume of data resulting from the digitization of everything. Add to all that: new technology to handle big data in a reasonable time frame, user-friendly mobile computing in the form of tablets, data virtualization software and data warehouse appliances that significantly accelerate the process of getting at the information for analysis, and the promise of predictive analytics, and there's plenty of cause for an information management rennaisance out there. With a little luck, the activity it catalyzes will also improve enterprises' ability to manage the data and content that's not so new but also very important that we've been struggling with for the last decade or so. 

The only argument against creating this role that I've run across is that if CIOs and CTOs did their jobs right, we wouldn't need this new role. That's pretty feeble since we're not just talking about IT's history of relative ineffectiveness in managing information outside of application silos (and don't get me started about content management) -- we're adding to that a significant increase in the value of information and a significant increase in the amount of available information. And then there's the fact that the data could be in the cloud and not managed by IT, and there's also a changing picture regarding risk that suggests a new approach.

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The Great Divide: MDM and Data Quality Solution Selection

Michele Goetz

I just came back from a Product Information Management (PIM) event this week had had a lot of discussions about how to evaluate vendors and their solutions.  I also get a lot of inquiries on vendor selection and while a lot of the questions center around the functionality itself, how to evaluate is also a key point of discussion.  What peaked my interest on this subject is that IT and the Business have very different objectives in selecting a solution for MDM, PIM, and data quality.  In fact, it can often get contentious when IT and the Business don't agree on the best solution. 

General steps to purchase a solution seem pretty consistent: create a short list based on the Forrester Wave and research, conduct an RFI, narrow down to 2-3 vendors for an RFP, make a decision.  But, the devil seems to be in the details.  

  • Is a proof of concept required?
  • How do you make a decision when vendors solutions appear the same? Are they really the same?
  • How do you put pricing into context? Is lowest really better?
  • What is required to know before engaging with vendors to identify fit and differentiation? 
  • When does meeting business objectives win out over fit in IT skills and platform consistency?
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