#eavoices

The Enterprise Architect of Hamelyn

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Stakeholder Concern Enterprise Focus Project Focus
The city of Hamelyn is plagued with rats. This indicates a serious problem with the “Public Health and Hygiene” capability. We just need a quick project to eliminate the rats. So we buy some “Eliminate Creature” capability from an external vendor.
The Pied Piper gets rid of the rats. Real business problem has not been addressed. Let’s now push on with the next phase of solving the problem. Project successful.
The Pied Piper is too expensive. We need a careful transition plan while we build an in-house capability. Let us immediately renegotiate our contract with the vendor.
The Pied Piper gets rid of the children. It turns out that the Pied Piper can reuse his “Eliminate Creature” capability for other purposes. !*!?**!
Which Role? Enterprise Architect?
Strategic Procurement?		 Solution Architect?
Tactical Procurement?

See also my article “Requirements Engineering as if Stakeholders Mattered” (Requirenautics Quarterly, Issue 29, August 2003, pdf)

Spaghetti Grows in System Architectures – not an April Fools’ Day joke

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A replay on breakfast TV this morning of the well known Panarama hoax (1st April 1957) reminded me of the mission we’re on at Bristol to “turn spaghetti into lasagne”. This mission is number 7 on the JISC 10 pointer list for improving organisational efficiency: spaghetti refers to the proliferation of point-to-point (tightly coupled) integrations […]

G-A-M-I-F-Y has (almost) Arrived!

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My new book GAMIFY is about to be released (April 8), but in fact, the hard copy version is already shipping on Amazon.com. To celebrate, I’m offering 20 copies (digital or hardcover) to the first 20 people who post on Twitter with the hashtag #GartnerGamify. After you post your tweet, make sure to follow me […]

The post G-A-M-I-F-Y has (almost) Arrived! appeared first on Brian Burke.

UML for functional programming?

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First of all: UML is not about modelling object-oriented software. But maybe we should go back to what object-orientation is. OO (shorthand for object-orientation) is invented around 1970. Xerox had a group called the Software Research Group which was part of a think tank created to do research into the possible threats of the modern […]

Public Sector Open Data via Information Sharing and Enterprise Architecture

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The title of this article is quite a mouthful, and three very complex and broadly-scoped disciplines mashed together. But that’s what’s happening all over, isn’t it, driven by consumer demand on their iPhones – mashing and manipulating information that’s managed to leak through the risk-adverse, highly-regulated mantle of the government’s secure data cocoon, and instantly sharing it for further rendering, visualization or actual, productive use. Mostly a “pull” style information flow, at best constrained or abstracted by public sector EA methods and models – at worst, simply denied.

This demand for open data, however, is rapidly exposing both opportunities and challenges within government information-sharing environments, behind the firewall – in turn a fantastic opportunity and challenge for the Enterprise Architects and Data Management organizations.

The recent “Open Data Policy” compels US Federal agencies to make as much non-sensitive, government-generated data as possible available to the public, via open standards in data structures (for humans and machine-readable), APIs (application programming interfaces) and browser-accessible functions. The public (including commercial entities) in turn can use this data to create new information packages and applications for all kinds of interesting and sometimes critical uses – from monitoring the health of public parks to predicting the arrival of city buses, or failure of city lights.

But there isn’t an “easy” button. And, given the highly-regulated and tremendously complex nature of integrated, older government systems and their maintenance contracts – significant internal change is very difficult, to meet what amounts to a “suggested” and unfunded (but with long-term ROI) mandate, without much in the way of clear and measurable value objectives.

That doesn’t mean there aren’t whole bunches of citizens and government employees ready, willing and enthusiastic about sharing information and ideas that clearly deliver tangible, touchable public benefit. Witness the recent “Open Data Day DC“, a yearly hackathon in the District of Columbia for collaborating on using open data to solve local DC issues, world poverty, and other open government challenges. Simply sharing information in ways that weren’t part of the original systems integration requirements or objectives has become a very popular – and in fact expected behavior – of the more progressive and (by necessity) collaborative agencies – such as the Department of Homeland Security (DHS).  

The Information Sharing Environment is the nation’s most prominent and perhaps active federal information sharing model – though its mission really generates “open data” products for a closed community (vs. the anonymous public) – i.e. those that deal with sensitive national security challenges. For information sharing purposes, however, it’s a very successful and well-documented, replicable model for any context that includes multiple government entities and stakeholders (whether one agency or department, or a whole city or state). A pragmatic Information Sharing Environment – with enthusiastic, knowledgeable and authoritative champions – is also the first, most important leg of the stool that supports successful Open Data initiatives.

The second leg is Enterprise Architecture – thinking of “open data” as the “demand” side of the equation, and “information sharing” as the conduit and source of “authorities” (i.e. policies, rules, governance, roles; internal and external) – EA can represent the “supply”. “Represent” the supply, not “be” the supply; the “supply” are the actual agency assets, including data, budget, contracts, personnel, etc. EA can inform regarding what data is available where and when, with what constraints, in what format or representations, via which IT interfaces, and via which business or technology resources. What can or needs to be changed, or what will be impacted, for the supply to meet the demand? Perhaps reusable IT exists that can be fully leveraged to meet the requirements, perhaps existing Oracle SOA, BPM and WebCenter assets?

The third leg of course is the inventory of data assets available – data assets include not only the raw data, but the metadata and registries, data access functions and APIs, data models and schemas, and the information technologies and systems that produce, manipulate, manage, protect and store the data. Plus really neat, useful commercial and open source open data tools to help. Whether they exist already, or need to be created.

So it conceptually works as follows, very abstractly-mirroring the well-known “People, Process, Technology” business model;

  1. People – An information-sharing environment and culture develops, enabling productive dialogue and guidance about proactively or reactively creating “open data” from enterprise assets to share with the public;
  2. Process – An Enterprise Architecture method and framework is leveraged, to define and scope the “art of the possible” in leveraging enterprise data assets, in terms that enable compliant program and engineering planning; and
  3. Information Technology – Useful, standards-based data products are cataloged and exposed to the public (better with some initial protoyping), meeting requirements and expectations, appropriately constrained by law, policy, regulations and investment controls. 

 Significant open data, and open government initiatives can’t succeed and persist without all three perspectives, all three domains of organizational expertise.

Agile is not Dead, it’s Morphing

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I note healthy discussion around whether Agile is Dead [ref 1]. And while I may sympathize (sic) with many of the comments, particularly the commercial trivialization of education, the core issue must surely be the difficulty of adopting de facto Agile practices to support real world enterprise programs and projects. My experience is most of the advice and guidance out there is predicated on scaling the de facto Agile development methods. And this isn’t the best place to start.

An exception is Dean Leffingwell’s SAFe, [ref 2] which does introduce the idea of portfolio, program and project perspectives and intentional architecture. I recommend this framework as an intelligent set of practices, but for me it doesn’t go far enough because it is still primarily about development practices. This is the core problem – that Agile is development specific and practices only. In the enterprise, Agile development needs to be an integral part of a bigger ecosystem spanning business design, architecture, requirements, modernization and operational transformation practices plus architecture, delivery and modernization disciplines.

I am indebted to Dave Thomas whose recent blog, [ref 1] includes a worthy successor to the Agile Manifesto, reducing the original, development specific values and principles to a minimalist, more generic set. He says; “here is how to do something in an agile fashion”
– Find out where you are
– Take a small step towards your goal
– Adjust your understanding based on what you learned
– Repeat
And this is more useful in the enterprise context because it is relevant to a broader set of activities than purely software development.

The diagram below is an outline maturity model template for Agile in the enterprise. It suggests there are four key views that need to be part of the transformation.  In addition to agile practices we need to be equally focused on what elements of agile architecture are required for an enterprise. What the agile delivery framework is and how the existing application portfolio will be modernized to progressively eliminate the duplication and complexity present in every enterprise on the planet.

People & Process. Much of the dissatisfaction with Agile arises from the limitations of the basic Agile practices, and the need to compromise these in an enterprise context. Both DAD and RUP (yes it’s an iterative method) are examples of extended or hybrid practices that introduce coordination, phasing and other disciplines that are more acceptable in enterprises that require traceability, governance and compliance with pre-existing life cycle practices. Enterprise frameworks such as Leffingwell’s SAFe as discussed and Everware-CBDI’s SOAM are examples of frameworks that adhere more closely to the purity of Agile principles while addressing enterprise specific needs. SAFe provides a framework which is more strongly Lean, coordinating portfolio, program and project activity to meet agile release train demand. SOAM provides a complementary, full life cycle process framework for software service modernization and delivery.

Agile Architecture. There is a requirement to articulate the enterprise requirements for agility as a reference architecture for business agility. In today’s fast moving world core architecture for the business, services, implementations, technology and deployments needs to be:
– under continuous development using Agile principles
– derived from the assessment of business needs for response to change, and constantly updated to reflect competitive and technology opportunities and threats.
– mapped to service architectures, patterns, policies and modernization strategies
– modeled using MDA/MDD to allow delivery as consistent architecture runways for portfolio and demand management, programs and projects.

Agile Delivery Framework. Most enterprises have a well-defined delivery framework of tools, repositories, templates etc that are designed to support well established QA and delivery policies. This is one of the most common inhibitors that Agile projects in the enterprise have to  overcome. In an enterprise Agile context that framework must be realigned to provide maximum automation of life cycle management and governance so that key enterprise requirements for integrity can be met without loss of productivity. Similarly the development  activity must be structured so that developers can extend the architecture runway with business solution specific rules and behaviors in a managed fashion which preserves the integrity of the architecture. Everware-CBDI has pioneered this runway extension capability implemented as a model driven (MDA/MDD) capability in which the runway code is generated and provided to developers enabling very significant productivity gains in both forward engineering and even more so in iteration.

Agile Modernization.  Finally in an enterprise context the elephant in the room is the existing or legacy portfolio. Unless this elephant is addressed, the enterprise will continue to create more and more complexity, increase costs and reduce response times to change. What’s required is a discipline of continuous, Agile modernization. That means, using Dave Thomas’s minimalist manifesto [above] every portfolio item, program and project must include steps to find out the current situation and address minimum goals that reduce complexity and support a progressive modernization strategy. Without that, all enterprise Agile projects will remain narrow focus and simply add technical debt.

I suggest that while Agile is not dead in the enterprise it is certainly struggling to survive. This is because Agile practices alone will be suffocated at birth by enterprise realities of consistency and integrity; or turned into narrow focus, standalone projects; or morphed into BAU. I really don’t want to enter into a debate about nouns or verbs, life is too short.  IMO Agile has considerable momentum and it can be morphed into a ground breaking concept that delivers enterprise business agility.

References
1 Agile is Dead (Long Live Agility)
2 Dean Leffingwell SAFe

Whole-Brained Business Analysis – New Metaphor Required

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I’ve been guilty using the much debated ‘Left vs Right brain’ metaphor to explain what I believe is needed. By way of example, Alec Sharp (@alecsharp), Sally Bean  (@Cybersal), Roy Grubb  (@roygrubb) and I have been Tweeting about Concept Modeling vs Concept Mapping. Alec is keen to get Data Modelers to abstract their thinking up from physical Data Models by thinking conceptually and I have been encouraging Business Analysts to think similarly when gathering requirements. This has meant that we both find that we need to introduce a different mindset: one that encourages more creative & inclusive discussion atthe initial   discovery and play-back stage of the Requirements-Solution Design journey. I expect the Agile/XP community will declare this to be their philosophy (and nothing new) and they’re probably right. But rather than get caught-up in ‘IT-centric’ methods, I’d rather think of it as a way to better understand any requirements for change – regardless of the Software Development Life-Cycle. I’d rather see such thinking applied to all aspects of business change – people, process, practice, policy and … technology.


Tried-and-tested analytical techniques should not be abandoned, they just need to be augmented with others that, in my experience, help expand ideas and produce resilient, coherent and business-value-creating solutions.  Both side of the equation are equally important. However, I’m finding (through experiment) that the more creative techniques are more engaging – simply more fun and inclusive – and, this alone, can, in my recent experience, dramatically improve business outcomes. 

In attempts to explain the need for a more ‘whole-brained’ approach, I’ve been following the lead of the ‘Design Thinking’ community in referring to both Theory X and Theory Y from MIT Sloan and the Left-brain Right-brain metaphor. This, however, is fraught with problems due, in large part to the findings of the University of Utah who debunk such binary thinking (as I was reminded by Rob England – @theitskeptic).

So I’m in a quandary: on the one hand I find that an X-Y, Left-Right, metaphor is a simple way to convey the difference between, say, Analysis vs. Synthesis, on the other hand, however, I run the risk of aligning with outdated concepts being fundamental reconsidered by neuroscientists. 

I guess the Complexity Science community might say that I’m talking about the difference between ‘Complex Adaptive’  vs. ‘Complicated’ systems, but, again, academic debate makes coming up with a simple metaphor next to impossible.

Has anyone found an alternative metaphor for a more balanced approach to Business Analysis and Enterprise Architecture?

Importantly, I’m keen to avoid the impression that people are to be seen as fundamentally one way or another. My observation is that it is the practice of Business Analysis/Enterprise Architecture that needs to be more ‘Whole-brained’ – not the individuals per se.

To get the discussion rolling, I’d like to hear views on:
  • A good Business Analyst or Enterprise Architecture must be a balance of Left-X(Reliability – Doing-things-Right) and Right-Y (Validity – Doing-the-right-thing)
  • We’ve spent to much time of methods that attempt to industrialise EA (the TOGAF 9.0 manual runs to around 800 pages in the attempt) and BAs are too often focused on methods focus on an ‘IT solution’ rather that the Whys and Whats of the current or desired business behavior
  • We need to spend more time on developing pattern-based storytelling skills in BAs and EAs to deliver break-through changes and allow for innovation in TO-BE models.
  • Economic churn and environmental challenges warrant more Y-minded thinking (with appropriate X-controls)
  • The world can’t be fully explained or governed algorithmically (thank god!)– not while values and trust dominate the way organisations function.