Are You An Enterprise Architecture Success Story?

Alex Cullen

Some enterprise architecture programs become a key capability for the success of their business: ensuring aligned plans, shaping business transformations, or boosting the business value of IT. But other EA programs struggle, with nebulous missions, immature practices, and limited impact.

If the first statement describes your EA program, I’d like to invite you to submit your story for the InfoWorld/Forrester Enterprise Architecture Award.InfoWorld/Forrester Enterprise Architecture Award image

This will be the third year of the awards program. Past winners have ranged from global banks to government ministries, from American Express to USAA, and from Singapore to Switzerland. These organizations have become a rich source of best practices and a demonstration of what a high-performance EA program is capable of.

We have a theme for the 2012 awards: EA programs that are business-focused, strategic, and pragmatic — and demonstrate this through their practices and the value they deliver. There are many ways in which EA can show this: partnering with business transformation efforts, developing business-relevant road maps, orchestrating their business’s information assets, increasing business agility — the list is long. As with past years, submissions will be judged by your peers — heads of successful EA programs, including previous winners.

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Starving People Will Find Food

Brian  Hopkins

In our Forrsights Business Decision-Makers Survey, Q4 2011, 79% of business executive respondents said that technology will be a key source of innovation for their company, while 71% said that it will be a competitive differentiator. So how well positioned is IT to help firms meet these expectations? Forty-six percent thought that their current IT organization was not well positioned to meet these needs, and 41% thought IT was overly bureaucratic.

I could go on with more data, but the message is clear — business is starving for technology to help it be more innovative, create market differentiation, and lower costs. In the midst of this, IT is mired in a technology mess created by years of underinvestment and business growth by acquisition. What’s going to happen?

The thing I want you to remember is something a client said to me not too long ago that stuck with me, “Starving people will find food.” So the question is: do we feed our starving business or tell them to stay on a diet? And if the latter, what will be the impact if they go scavenging the countryside? We think the answer involves flexibly and rapidly introducing new technology to take advantage of strategic opportunities, while still protecting data, mission-critical applications, and our most precious TCO reduction goals.

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Semantic Technology In The Enterprise

Leslie Owens

Remember The Jetsons? The flying cars and the automated kitchen and the food pills? Sometimes modern life can feel like that futuristic utopia. We've got robots in the home and a speech-recognition personal assistant named Siri built in the iPhone in our bag. IBM Watson, a supercomputer, beat its human competition in the TV game show Jeopardy! last year. How? By translating corny, nuanced questions into a format it could understand and compute.

But for most of us, our digital experiences at work feel like we're stuck in The Flintstones.

We wonder: "How can Amazon.com monitor my customer data so closely that it knows what book I want next, but after five years of daily use, my enterprise search engine doesn't get that I work in HR in the Chicago office?" We need to dig into our enterprise information so it is more rich and useful. Hal Varian, Google's Chief Economist, explained in the McKinsey Quarterly that "We have free and ubiquitous data, so the complementary scarce factor is the ability to understand that data and extract value from it." (He even goes so far as to say that statisticians will be the sexy job in the next 10 years!)

It's understandable to be cynical about semantic processing, especially if you've been told it relies on manually entered metadata.

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Big Data Ain't Worth Diddly Without Big Process

Clay Richardson

Nowadays, there are two topics that I’m very passionate about. The first is the fact that spring is finally here and it’s time to dust off my clubs to take in my few first few rounds of golf. The second topic that I’m currently passionate about is the research I’ve been doing around the connection between big data and big process.

While most enterprise architects are familiar with the promise — and, unfortunately, the hype — of big data, very few are familiar with the newer concept of “big process.” Forrester first coined this term back in August of 2011 to describe the shift we see in organizations moving from siloed approaches to BPM and process improvement to more holistic approaches that stitch all the pieces together to drive business transformation.

Our working definition for big process is:

“Methods and techniques that provide a more holistic approach to process improvement and process transformation initiatives.”

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Agility And What's Keeping You From It

Brian  Hopkins

In our Forrsights Business Decision-Makers Survey, Q4 2011, we asked business technology leaders to rate IT’s ability to establish an architecture that can accommodate changes to business strategy. While 45% of IT rated its ability positively, only 30% of business respondents did. Clearly, both think there is room for improvement, but business is more concerned about it.

So are we agile? Only 21% of enterprise architects in our September 2011 Global State Of Enterprise Architecture Online Survey reported being even modestly agile, so I think we all know the answer.

What do we do about it? Continue to focus on technology standardization and cost reduction? Give up on that and focus on tactical business needs? Gridlock in the middle because we can’t make the business case to invest in agility? This is the struggle EA organizations face today.

To act with agility, firms must create a foundation for it, and three barriers can get in the way:

  • Brittle processes and legacy systems. We all know it this one; the current state mess of processes that cannot adapt to change and legacy systems where everything is connected to everything else, so even the smallest changes have broad impacts. Techniques to overcome this barrier include partitioning the problem into digestible pieces to show incremental progress and short-term payoff.
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New Focus Of EA: Preparing For An "Age Of Agility"

Alex Cullen

 

    I just recently had a conversation with Peter Hinssen, one of our keynote speakers at Forrester’s colocated CIO Forum and EA Forum in Las Vegas (May 3-4) and our EMEA CIO Forum and EA Forum in Paris (June 19-20). 

   Peter is both a dynamic speaker and a provocative thought-leader on the rapidly changing relationship of technology, business, and “the business function called IT.” Here’s a short summary of this conversation — and a preview of what he will be talking about at our forums.

 

On “The New Normal”:

Technology has stopped being “technology,” and digital has just become “normal”: We’ve entered the world of the “New Normal.” The rate of change of the technology world has become the beat to which markets transform. But the rate of change “outside” companies is now faster than the internal velocity of organizations. But how will companies evolve to cope with the changes as a result of the New Normal? How will organizations evolve to respond quickly enough when markets turn into networks of intelligence?

What this means for IT:

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Dynamic Case Management — Do Enterprise Architectures Realize The Potential?

Craig Le Clair

The answer is a simply no. I’m finding that enterprise architectures are not well-grounded in this emerging area. Many enterprise architects, and particularly those who focus on business architecture, think that dynamic case management (DCM) is a newfangled marketing term to describe an old, worn-out idea — a glorified electronic file folder with workflow. Yes, enterprise architects can be a cynical bunch. But DCM goes far beyond a simplistic technology marketing term — it’s a new way of thinking about how complex work gets done, and often enterprise architects are so consumed with technology planning that they may not see new patterns of work emerging in the business that require new ways of thinking.

“Dynamic” describes the reality of how organizations serve customers and build products in a world that is changing constantly. If you doubt that assertion, think about volcanoes disrupting airlines, oil rigs exploding, product recalls, executives being investigated for fraud, new healthcare legislation, or more common events such as mergers and acquisitions. Most knowledge work requires unique processing, and processes need to adapt to situations — not the other way around. For enterprises, DCM provides a transformational opportunity to take the drudgery out of work and enable high-value, ad hoc knowledge work — much as enterprise resource planning (ERP) did for transactional processes. And, in fact, our research points to a growing use of DCM to add agility to systems of record including packaged apps and legacy transaction systems.

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Organizations Creating An Information Governance Program Are Often Entering Virgin Territory

Alan Weintraub

Creating governance programs that separately address structured (data) or unstructured (content) can be a daunting task for any organization. Most organizations are just now addressing the governance issues that help ensure that their information, both data and content, is trustworthy and reliable. If creating separate governance programs is such a challenge, then why I am advocating the creation of a combined program for information governance? The challenges of governing structured data differ from the problems governing unstructured content, due to different goals, stakeholders, roles, and processes. The result is that governance of these areas involves completely separate endeavors.

But must they be wholly separate? Isn't there enough common ground? Creating an information governance framework that will address both their structured and unstructured information requires that the appropriate IT and business roles and responsibilities are clearly defined and that stakeholders from both IT and business are in agreement with the design and implementation efforts for an effective information governance strategy. Is this task too daunting for an organization to overcome? As more decisions are made using both data and content, it becomes increasingly important that all information used in the decision process is trustworthy and reliable. Agility in decision-making is dependent upon the right information at the right time. So my contention is that we should not wait for our data and content governance program to mature before implementing an overall information governance program. We should look at the similarities in the two governance programs to create a common framework that can be leveraged to create commonality and consistency in the information architecture.

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Big Data, Analytics, And Hospital Readmission Rates

Craig Le Clair

The US government will start tracking hospital readmission rates. Why? Because we spend some $15B each year treating returning patients. Many of these would not need to return if they followed instructions — which involve meds, follow up out patient visits, diet, and you get the picture. To be fair, it's sometimes not the patient's fault. They often do not get a proper discharge summary and in some cases they are just not together enough to comply. They may lack transportation, communication skills, or the ability to follow instructions. Doesn't it make sense to figure out those at-risk patients and do something a little extra? It does. No question. And translates to real money and better care, and this is where big data comes in — and it's nice to see some real use cases that do not involve monitoring our behavior to sell something. Turns out — no surprise here — the structured EMR patient record, if one exists, is full of holes and gaps — including missing treatments from other providers, billing history, or indicators of personal behavior — that may provide a clue to readmission potential. The larger picture of information —mostly unstructured —can now be accessed and analyzed, and high-risk patients can have mini workflows or case management apps to be sure they are following instructions. IBM is doing some great work in this area with the analytics engine Watson and partners such as Seton. Take a few minutes to read this article.

Centralized, Federated, Or Virtualized: What Works For Organizing The EA Practice?

Gene Leganza

If you’re trying to build an effective EA program, you’re in trouble from the get-go. I’d like to paint a rosier picture for anyone involved in this strategic, potentially very high-impact practice, but consider the fact that one of our more frequent client inquiries is about how to communicate EA’s value to non-EAers. How can I not say you’re in trouble if so many people doing EA look for outside help to explain to their own stakeholders that what they’re doing on a daily basis is worthwhile? There’s clearly something wrong with this picture.

So, OK, let’s say you want to build an EA practice anyway, despite the poorly understood value proposition — who should you staff it with? Misguided people with a desire to labor away in obscurity? Actually, no, you want your best and brightest. Those few very smart people who know your business very well, have both deep and broad knowledge and great analytical skills, and who display the potential for strategic-, system-, and design-thinking. That's a little challenging.

And then, when you find these people and attract them to your program, how best to organize them for effectiveness? Centralizing EA resources gives you the most control and makes it more likely that EA can deliver on its strategic value proposition. Decentralizing or federating EA resources puts the architects where the action is, making it more likely business and BT stakeholders will perceive value from the effort. But then those federated resources sometimes get so involved with their local — and usually tactical — issues that they go native and they’re not really working on the “E” in EA anymore.

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