Beyond | IT : continuous learning

Computing Is A Liberal Art, Part 2: Knowledge is personal

john.mullinax — Wed, 20 Jun 2007 07:34:00 GMT

Technorati Tags: innovation , systems thinking , complexity science , adaptive , change , learning , Popfly , computing is a liberal art , knowledge , cyborg In the natural world, few (if any) things grow without limits. In the case of information...(read more)

Learning to thrive in times of accelerating change

john.mullinax — Fri, 15 Jun 2007 16:24:00 GMT

Technorati Tags: continuous learning , systems thinking , adaptive , change , learning Over the last couple of years I've often heard about the need for a "sense and respond" capability -- to sense what's happening in our businesses and to respond...(read more)

The Best Payback in Technology History... Think you know what it is???

john.mullinax — Fri, 16 Feb 2007 07:38:44 GMT

Hmmm.... How about a giant ERP system? :-) Nope. Internet Explorer? Windows Mobile? Getting closer, but those are only "honorable mention" in my book. If you're a company with a large investments in ERP and Line of Business (LOB) applications, my vote...(read more)

Why bother with lean? Because it Rocks!!

john.mullinax — Thu, 18 Jan 2007 03:13:00 GMT

My last post left off with the following set of questions:

Why bother with lean? Really, why would we want to imitate an old and slow industry like manufacturing? Especially given it's long and steady decline in the United States. With the acceleating pace of change in the world, we need new ideas that can help us be agile and adaptive, don't we?

While it's not always an easy journey, I find it does have it's rewards. In the manufacturing industry, few if any seriously debate the value of being lean. Basically, everyone wants to be lean and the debates today are around how to best do it. Lean thinking has literally transformed manufacturing around the world. Moreover, other industries support lean as well. For example, retail establishments like Walmart support manufacturers in continuously improving their lean-ness by providing them demand chain visibility. REI uses the principles of "flow" and "evenness" to make optimize their checkout lines, as have most retail financial service operations (i.e., bank branches) -- though lean adopters are not always consciously thinking about lean when they take these actions. In many cases, people are simply copying what has worked elsewhere.

Copying others is definately a low-effort way to make changes. It can work well in the short run, and can be genuinely helpful to long-term learning and oganizational growth. That said, I suspect the consciously early-adopters of lean in a new industry do so because they want to lead their industry. As their successes are copied, competitors may gain as well. But in the long-run, an understanding of the lean principles and a commitment to continuous improvement in a rapidly changing world allow lean thinking companies to generally increase their performance leads over time versus those who blindly copy yesterday’s (or this morning’s) actions without understanding why. I suspect that near the end of the lean adoption cycle in an industry -- for example, where we are now in the Manufacturing industry -- lean adoption and lean thinking get taken up by the last of the "hold outs" as a matter of survival more than a matter of leadership.

The funny thing is that people often view the manufacturing industry as old and slow. In today's vernacular, people want their organizations to be adaptive so they can cope with the ever accelerating pace of change. Fortunately for all of us, a framework for being adaptive already exists -- in fact, it's fundamentally built into lean thinking: understand your environment, experiment, apply improvements, and repeat.

It's worth noting that this core nugget of lean is also the fundamental idea behind the Deming Cycle (Plan-Do-Check-Act), as well as Six Sigma (Define-Measure-Analyze-Improve-Control). Thanks to John Boyd, US Army teaches it's soldiers the OODA Loop (Observe-Orient-Decide-Act) -- essentially the same idea, which Boyd built from Godel's Incompleteness Theorem, Heisenberg's Uncertainty Principle, and the Second Law of Thermodynamics- the entropy of a closed system increases. Not the first to do so, Boyd extended the idea to social evolution, and believed that the decision cycle is the central mechanism of adaptation. Jack Welch said (paraphrasing) that if change on the outside of your organization is faster than change on the inside, you're in trouble.

Though I certainly don't put myself in the same category as the giants above, I've also written about this in a different forum as Respond-Sense-Learn, based onthe ideas of Philosopher Karl Popper, as well as Peter Senge (minimizing Deming's "plan" component as a step toward greater agility).

Finally, what does any of this have to do with Microsoft? Well, quite a bit, actually. Taken together, Microsoft technologies provide an outstanding platform to help you build an adaptive organization. For example:

Bringing business intelligence to all parts of the enterprise so that workers up, down, and throughout the organization can make faster, more insightful decisions with higher success rates at each of the multiple decision events they face during a typical day.
Sharing that information with people in the flow and context of their business processes, be they structured or semi-structured/unstructured -- as so many business processes actually are.
Sharing information with visualizations that actually inspire insights, and within tools people already know and that enable immediate actions to be taken.
Rapid and easy business process composition, prototyping, experimentation, and implementation, including tools to monitor and assess the performance and "fitness" of specific business process variations against measures that matter to you.
The capability to use that same data about business process "trials" -- and potentially every prototype and production implementation is also a trial -- to build and execute simulation models that create even greater insight about your business so you can understand what truly drives the results you care about.
Ironically, the deep understanding of what drives your results that can come from enabling business intelligence throughout your organization, business process experimentation, and business simulation is actually the key to reducing information overload and controlling the flood of data that threatens to drown people's ability to do productive work. By understanding the things that really drive results, we can target our activities and only report, share, and analyze the things that actually matter.
And if you find yourself in an environment of ontological uncertainty, the collaboration and communication platform provides a wide variety of communication channels to ensure folks understand the organizational principles that will enable them, as individuals and team members, to drive in a common direction toward an uncertain future.

I believe in Boyd's idea that decision making is the primary mechanism for adaptation. The reality is that, whether we realize it or not, we all live in a world where the ability to make better decisions faster about the things that truly matter will ultimately determine our success. Many folks will make speedy, apparently "effective" decisions about things that appear to matter -- but really don't drive desired results because they are themselves driven by other "confounding" variables. Perhaps even more people will make slow, ponderous decisions on topics that may or may not drive results -- but cause opportunity and value to slip through their fingers. And a comparatively small group of people will make rapid, insightful decisions about things that truly do drive results. Over time, these people will work for the leading companies in their respective fields, because they will have created that success.

Whatever the labels you decide to use, I invite you to join me on the journey!

Ontological Uncertainty and Innovation

john.mullinax — Tue, 28 Nov 2006 01:28:00 GMT

Thought folks might find this 2004 working paper from David A. Lane and Robert Maxfield at the Sante Fe Institute of interest: http://www.santafe.edu/research/publications/workingpapers/04-06-014.pdf. It’s a little dense, to say the least, so I posted this brief summary of which elements caught my attention....

As I read it (I'm simplifying, and the authors don't explicitly reference systems thinking), “ontological uncertainty” is essentially uncertainty actors in a system (as in systems thinking or systems dynamics, see The Fifth Discipline by Peter Senge for more) face when the impacts of their actions last beyond the stable structure of a system itself. In other words, whether they know it or not, when a knowledge of the existing system would still not allow them to predict the impacts of their actions.

One of the things I like about this article is that it provides a larger theoretical underpinning to the advice we sometimes give ourselves in times of uncertainty and rapid change – namely, to focus on “enduring” principles. I think the authors of the linked article would argue that these principles are essentially part of a larger story we tell ourselves about the world. In fact, the principles seem to me to be especially connected to the part of our “larger story” of the world that is most *about ourselves*.

The authors argue that actors use a narrative, or series of stories about themselves and the system they are in to keep making decisions during periods of high uncertainty and that this is can inspire a confidence which can increase actor effectiveness. While the narrative can enable “effective” action, it also constrains actors to decisions that make narrative sense at decision-time. The process may not be even be conscious to actors, but by embedding narratives into their perceptions of their world, actors can make sense of context they may literally act out their (somewhat) self-“assigned roles”. In this way, actors may “back in to the future”.

The connection to innovation is summed up here:

“…[A]gents facing ontological uncertainty can enter into and nurture relationships with generative potential; and … generative potential may be realized through the discovery of semantic uncertainty, whose exploration may lead to new attributions that may then be instantiated in new kinds of artifacts or agents…. [O]ntological and semantic uncertainty lead to more ontological and semantic uncertainty, as efforts to resolve them also uncover further entities, relations and concepts that must be interpreted in their turn. The locus of these transformations can shift from one set of actors to another, from one generative relationship to another. The story is long, because the processes it is intended to illustrate are subtle and highly context dependent, but its moral is simple: novelty often arises from relationships and context, not only in flashes of inspiration in individual brains.” (p. 24).

Especially so, when actors have aligned interests but different views that they are capable of exploring with each other.

This theory also offers an interesting lens to view scenario planning, as scenario planning is essentially a mechanism for us to consciously tell ourselves more than one "story" at a time about the world we live in -- thereby giving ourselves a vehicle to individually and collectively explore different views inside our heads.

Not for the faint of heart, but insightful.

The question for you: do you believe this is insight is actionable in your enviroment?