I hadn't realised Sketchcast had gone down - what a pity, it was a lovely idea.

How did you actually create the video? I'm guessing a screen-capture programme capturing something like PowerPoint? I wonder if you could combine that with something like PowerPoint's 'live draw on the screen' function to re-create a sketchcast.

Cheers,
Stuart

Very good explanation.
Is it OK for you if I make a similar one in Swedish, mentioning the original source, of course?

Romi R.

Great job Shawn - one of the clearest explanations I've seen. Like the format too...
Chris

Thank you Shawn for restoring this highly praised resource.
Stephane

A useful explanation of the Cynefin network but I think that only exposes its weaknesses. For example, there is no indication given of how to detect which quadrant you are in and no explanation why an action (i.e. a cause) in a chaotic system may change the state of that system. I find Pine's Mass Customization model more rigorous and more applicable.

Thanks for this Shaun. I have used your approach, and even your words at times, to explain to people how relationships and CoPs and the use of stories naturally influence behavior patterns.

Nice one Shawn - a simple and effective overview (not complex or complicated at all!)

Thanks for bringing Pine's model to my attention. What is the best source to learn about it?

Hi Romi, yes, please create on in Swedish and if you wouldn't mind, just pop a comment here too pointing to is. cheers.

I learnt about Pine's model from the original HBR review article http://tinyurl.com/d3m3eq. Sadly the wikipedia entry is almost blank, I may have to change that!

You can see an example of where I have used in relation to KM towards the end of this presentation http://tinyurl.com/5smlcf, though I have changed the terminology a little to suit local government, e.g. Pine's "mass customization" becomes "service improvement".

Thanks for posting this Shawn. Nice clear explanation.

It seems my trackback ping never made it around the globe to you. But I picked your video up and blogged. URL is linked via my name in this comment.

Great. Very much in line with how I have heard Dave Snowden talk about this framework.

My question is similar to that of Matthew. Now that I know how Cynefin conceptualizes these terms, what do I do with it? Besides that everyone thinks their situation is "complex," what if you find that it is actually chaotic or complicated instead?

Hi Jack, the main thing I use the Cynefin framework is to get a group of decision makers to agree what issues are simple, complicated, complex and chaotic and then help them design initiatives appropriate for the domain they are considering.

It's amazing how many times the leaders recognise that the issues they are facing are complex (culture, leadership, innovation etc) but they are implementing initiatives best suited for complicated issues (based on the Cynefin framework).

This understanding provides a rationale for people to try new approaches, such as narrative insight techniques.

I'd love to hear how other people use the framework. There are lots of possibilities.

The Theory of Constraints community suggests that most systems have an "inherent simplicity," even when they appear to be quite complicated or complex on the surface. The central idea is that simplicity means there is one leverage point that will affect the entire system - or that there are very few degrees of freedom. If you seem to have multiple levers, then these are either separate systems OR there is a bigger leverage point somewhere else. (I haven't gotten this completely right, but this is the gist.)

Hi Jack, complexifiers would say that a complex system has so many interacting parts that while there might be a one simple thing that could be the tipping point, there is no way to work it out before hand. I said this once to a group of engineers and one fellow popped his hand up and said, "If we can work out al the connections and likely moves in the system, then we could work out where to intervene." I then told him about some research that was done by the famous information scientist, Claude Shannon, who once estimated the number of moves on a chess board. This is simple and constrained system. Well, he estimated there were more moves than there are milliseconds since the Earth formed. So imagine the computing power needed to predict a human system.