Complexity

Complexity

Learning as a Network

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Mohamed Amine Chatti extends the framework on personal knowledge networks with his post on Learning as a Network (follow link for graphic):

The Learning as a Network (LaaN) perspective draws together some of the concepts behind double-loop learning and connectivism. It starts from the learner and views learning as the continuous creation of a personal knowledge network (PKN). For each learner, a PKN is a unique adaptive repertoire of:
– One’s theories-in-use. This includes norms for individual performance, strategies for achieving values, and assumptions that bind strategies and values together (conceptual/internal level) Tacit and explicit knowledge nodes (i.e. people and information) (external level

Here is Chris Argyris’ double-loop learning theory in a nutshell:

“There are four basic steps in the action theory learning process: (1) discovery of espoused and theory-in-use, (2) invention of new meanings, (3) production of new actions, and (4) generalization of results. Double loop learning involves applying each of these steps to itself. In double loop learning, assumptions underlying current views are questioned and hypotheses about behavior tested publically. The end result of double loop learning should be increased effectiveness in decision-making and better acceptance of failures and mistakes.”
double-loop

And here is George Siemens’ Connectivism theory:

Connectivism is the integration of principles explored by chaos, network, and complexity and self-organization theories. Learning is a process that occurs within nebulous environments of shifting core elements – not entirely under the control of the individual. Learning (defined as actionable knowledge) can reside outside of ourselves (within an organization or a database), is focused on connecting specialized information sets, and the connections that enable us to learn more are more important than our current state of knowing.

Finally, you can get a quick overview of the Cynefin model and complexity with this video from Anecdote.

So that’s: double-loop learning – connectivism – complexity; three concepts, each requiring some depth of understanding . No wonder this is a hard sell in the boardroom. Many people think of learning as school, training as something that is delivered, and complexity as problems that can be solved with effort and resources.

Like Mohamed, I am interested in these theories but my true passion is in implementing frameworks for the workplace.  I too think that merging learning and knowledge management into our work is a good way to help organizations deal with complexity.

Here’s a possible elevator pitch for learning as a network, or PKM:

Is your work becoming more complex? How much complexity is there in the markets or the environment? Can anyone predict what’s going to happen next? Obviously many of the world’s economists have been wrong about most things. Looking backwards hasn’t helped us much.

In a complex world we cannot predict outcomes but we can engage our environment and learn by doing. That makes constant learning a critical business skill. But how do we help people develop that skill?

Giving tools and teaching by example is a good way to start. People need to make connections and see patterns and then reflect, criticize and detect errors. Only in a trusting, collaborative workplace can this happen.

Want to know more? Well let me you tell a story …

How complex is our work?

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On my recent post, Emergent practices need practice, I looked at how complexity could not be easily addressed through traditional training methods:

But many of the problems we face today are COMPLEX, and methods to solve simple and complicated problems will not work with complex ones. One of the ways we addressed simple & complicated problems was through training. Training works well when you have clear and measurable objectives. However, there are no clear objectives with complex problems. Learning as we probe the problem, we gain insight and our practices are emergent (emerging from our interaction with the changing environment and the problem). Training looks backwards, at what worked in the past (good & best practices), and creates a controlled environment to develop knowledge and skills.

That got me thinking about what the ‘average’ knowledge worker might be expected to do in the course of a week. I think that there is still a fair amount of our work that is based on our existing skills and knowledge (perhaps 50%) and enables us to deal with complicated issues. This could be writing complicated reports or doing some type of trouble-shooting or problem-solving based on processes and knowledge that we have developed in our professional field. I also think that we all have to deal with routine, simple stuff, but we should off-load as much as possible so that we could concentrate on higher value tasks. It would be best to keep this to a minimum; say no more than 10%. We can also be confronted with total chaos or crises from time to time. Dealing with these requires a lot of energy. Keeping chaos to a minimum would be another objective of the organization; once again, say 10%.

Finally, as we understand the complex nature of our environment or the markets, we would want our workers to be able to address complex challenges. I doubt that all of our work is complex and I’m not sure how much complexity one can handle for extended periods of time. We are constantly trying to make sense and bring some order to our work and that takes effort. I think that 30% may be an appropriate amount of our time.
complex work
Does anyone have experience or data in looking at how our work is divided from simple to complex problems? It seems like a very interesting area for further research.

Perpetual Beta

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It hadn’t really occurred to me before that pilots are an almost inextricable aspect of Enterprise 2.0. Of course the ‘iterate and refine’ concept can be implemented in other ways, but I think it’s fair to say that organizations absolutely need to get good at running pilots, if they’re not already there. It is a key facet of the path that leads to improved organizational performance.

So says Ross Dawson in pilots as a key instrument for improving organizational performance in a complex world. If you take the cynefin approach for working in complex environments you first Probe then Sense and then Respond in order to develop emergent practice. There are no good or best practices that will work for  your context in a changing complex environment, so probing (AKA: piloting or Beta releases) is necessary to see what works. However, changing from a highly designed approach to an agile method is difficult. I previously recommended that instructional design adopt agile methods but even in the programming world, letting go of old ways is difficult as Sara Ford at Microsoft explains in how I learned to program manage an agile team after six years of waterfall.

There is no silver bullet solution to running the human performance side of an organization in the complexity of a highly networked economy with ubiquitous access to information and people. New tools keep being developed that can change the way we work and learn. Today it’s Twitter and tomorrow it will be something else. Approaching enterprise performance from the perspective of perpetual Beta is a way to maintain your sanity in all of this change. The values and culture can remain stable while the tools and practices keep evolving to take advantage of the situation.

Pilots are key to improving organizational performance but the culture of perpetual Beta is critical. Perpetual Beta is my attitude toward learning – I’ll never get to the final release and my learning will never stabilize. I’ve also realized that organizations with a similar attitude are much easier to work with than those that believe that we will reach some future point where everything stabilizes and we don’t need to learn or do anything new. I think that point is called death.

Emergent complexity from social networks

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If I was an employee, I’d want to have someone like Ross Mayfield as my boss. He really understands the way that work is changing. I came across this good (but too short) ZD Net interview on Web 2.0 for the enterprise via Jay Cross.

In a panel interview, Ross Mayfield starts by saying that collaborative work tools must be simple to be effective. The real complexity comes out of the emergent social network, not in the software on which it’s based. Over-engineering for complex social (work) environments seems to be counterproductive. Ross also says that automating processes won’t give you any sustainable competitive advantages either, because others will be able to replicate these processes just as well. Where social tools, like wikis, have an impact is in changing the corporate culture. In a more transparent and collaborative work environment, powered by collaborative web-based tools, information hoarding is punished and sharing is rewarded. The workplace changes.

The most memorable line is when Ross shows the disconnect between the new world of work and the old world of education; “These are the people who did their homework on MySpace, and it was called cheating, and then they come to the enterprise and it’s called collaboration”.

The times they are a changin’

Here are Ross Mayfield’s own words, following up from the ZD Net “sound bite”:

Blogs and Wikis are inherently more transparent than email, where 90% of collaboration occurs.  Users are first gaining exposure to these tools as consumers, within consumer culture.  The default in that culture with these tools is transparency and sharing.  Corporate cultures vary. I can say that we see earlier adoption by corporations with healthy cultures and management practices such as 360 degree reviews, and adoption practices matter.  But it should be noted that consumer culture spills over to corporate culture.  And because this culture shift aids practice building, I’d assert that these tools will trend us towards transparency.

The Six Nations Model

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I’ve mentioned the Six Nations governance model before, as described in the book, Systems Thinking: Managing Chaos and Complexity, and am trying to align this with industrial-age corporations. Basically, I’m wondering how this pre-industrial governance structure could be used today. The author describes how it recently worked for the Oneida Nation. Could it be used elsewhere, or does it need a certain culture?

The Six Nations culture had given specific roles to its member tribes, namely Wolves (Pathfinders); Turtles (Problem Formulators); Bears (Problem Solvers). Solving problems (AKA governance) went like this:

  1. Wolves – Set direction, and identify relevant issues
  2. Turtles – Define the problems
  3. Bears – Generate alternatives and recommend solutions
  4. Turtles – Check on the potency of the recommended solutions
  5. Wolves – Integrate the solutions, keep the records, communicate the decisions

six-nations-governance.jpg

Could this be incorporated into a legal corporate structure (for profit or non-profit) and if so, would it differ from a governance structure with a Board of Directors, CEO and various executives?

The advantages I see with this governance model is that power is distributed but the roles are clear. It also builds in peer reflection through the process.

Systems Thinking

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I’m working on a couple of projects where I wanted to review some thoughts on systems design so I went to my bookshelf and re-read sections of Jamshid Gharajedaghi’s book, Systems Thinking: Managing Chaos and Complexity: A Platform for Designing Business Architecture.

In both hindsight (evaluation) and foresight (analysis), this advice resonated with me:

There is a need to deal with the problem independent of the solutions at hand. We have a tendency to define the problem in terms of the solutions we already have. We fail most often not because we fail to solve the problem we face, but because we fail to face the right problem. Rather than doing what we should, we do what we can. In the systems view, it is the solution that has to fit the problem, not vice versa.

This book can be a tough slog because it breaks new ground on almost every page, but after three years I still value the methods and the case studies contained within it.