As you can see I have explored my HTML guide, consulted our web master and I can now load images: expect a colourful new year in consequence! This post is designed for those who found (or may find) my post of yesterday on identity a bit too metaphysical for a first reading; i.e. those who are primarily interested in how natural numbers apply to communities and networks. It is designed to give some practical guide lines to community/network development and use of tools and updates my 2002 article on knowledge management which was one of the earliest outings for the Cynefin framework in an application context.
Now in the early days of knowledge management if one was to be cynical, there were two rules in operation:
Firstly, install an intranet/portal, create a taxonomy and wonder (with increasing despair) how to motivate people to codify their knowledge.
Secondly, design a standard approach to building a community of practice, with roll out plans, templates, process etc etc. Then, after the novely has worn off, wonder (with increasing despair) how to motivate people to engage.
Both of these approaches represent an ideal not a naturalising approach. I have previously discussed this but I will summarise the essential difference. In an ideal approach you define how things should be and attempt to achieve it; in a naturalising approach you introduce technologies and practices on a safe-fail basis and see what works. Amplification of good patterns, damping of bad patterns allows something to emerge that is more resilient and risk free, not to mention a lower cost, solution. What I want to do here, linking to natural numbers, is to outline a naturalistic approach to simulating network/community formation.
Please note – this blog entry was updated with corrections on 4th January 2006 my apologies for the lack of proof reading in the earlier version
—– Informal communities —–
When I wrote the 2002 article I had just gathered some data on number of on line communities within IBM Global Services, both formal and informal. Like most other service/consultancy organisations IBM had rolled out the approach to communities of practice. One look at the one on knowledge management and I never went back, all information management based on formal process and an over structured taxonomy. Some worked, mostly those in engineering communities which seems to be a wider pattern around the world. It also makes sense, the early work on CoP all studied engineering communities who understand codification and sharing within limits. The urge to share knowledge however is not confined to Engineers. Others also will do so, but the form will be particular to the group.
Let me continue my story. in parallel to the formal CoP program, IBM had stripped down a Lotus product (team room) to a basic, easy to set up utility called a Work Room. These were ad hoc, set up as needed without any real process. They were often unstructured and critically participation was a voluntary act. When they fell over (well it was stripped down system) people just fixed it and moved on. In the formal system they blamed the company for system failure.Checking the figures we discovered that the ration between formal and informal communities was around 1:1000 and the number of the informal virtual communities was around half the number of staff. Subsequent work in other companies validated those rations as reasonable heuristics. One scary happening however. I presented this at a conference where on the senior IBM knowledge management staff was present. Her response to the news was to start a process to bring the informal communities under control …….
Now this was four years ago, pre-blog and pre any wide-scale adoption of social computing. What we witnessed then has been validated in other environments and by the growth of blogs, wikis etc. Give people simple tools with no formal process or designed taxonomy and they will naturally find ways to share and create knowledge. This type of activity is complex, it is not structured and cannot and should not be controlled.
At the same time as we were making those observations in IBM, list serves also started to gain mass use. In knowlege management actKM was one of the most successful, although it seems to have dried up recently (hopefully that is just the Christmas break). List serves allowed people simply to say what they thought, comment and link to other people. Again they were voluntary in nature and allow for threads to be taken up, dropped, diverted without central control. I think there is now some evidence that the growth of blogs is starting to hit the list serves, but its early days yet. Add in the growth of public wikis, and the development of wiki’s that look like word processes rather than a motley collection of HTML, and you have a significant increase in infrastructure and tool capability. People are responding to, and using that capability. The critical point is that informal ecologies of knowledge exchange work, they are also critically and wonderfully messy, human systems not a nightmare of structure and process, as such they are not stable, but they are resilient.
—– A naturalising approach —–
Now of course, it was this phenomena that the early researchers in knowledge management had found. One thinks of Etienne Wenger’s pioneering work in observing naturally occurring use of virtual environments by engineers. The problem was when people went from a researchers description of what had grown naturally in the past, to a prescriptive recipe things went wrong. People never accurately report all the factors which led to the success or failure of a project, retrospective coherence clicks in. A researcher, now matter how gifted tends to pay attention to data that appears causal and which fits their emerging hypothesis. Also the fact that something worked once in a specific context does not mean that it will work again even in the same conditions, or that you can accurately replicate the starting conditions.
So lets look at an alternative naturalising approach to building communities for knowledge flow, organised in seven steps (so the median of the readers short term memory):
—– The dynamic learning cycle —–
Now the shifts between domains are illustrated above. The dynamic learning cycle starts with the informal, looks to shift some knowledge from there to fthe domain of experts on a just in time basis. That knowledge is either stabilised into the formal (although links are maintained) or cyclically disrupted to prevent entrainment and ossification.
Now we can look at natural numbers. Again this is illustrated in the picture. Informal communities link back to natural levels of trust, they need to be less than 15. For expert communities some degree of knowledge of the other participants is necessary, but deep trust is not. SItuation trust, contextual and professional trust all come into play. The 150 limit therefore cuts in here. For a formal community it does not matter, you have enough structure, and the material is at a low enough level of abstraction that anyone can use the material. For a crisis you need very small focused teams which is where the 5 limit fits in.
Now a critical qualification here. The numbers can relate to individuals,and they are good guidelines as such. However given the way social computing works we don’t have to restrict participation in this way if instead we think about identities or coalescences. Provided the central actors are limited by the numbers, the number of actual people can be large. Look at the number of lurkers in any virtual community, while the active participants tend to be about 15 overall, 5 in any particular thread. By observing natural clusters in the use of social computing tools, those clusters can be given roles or functions in wider groups. In effect this is a nodal network. The nodes stabilise their linkages and act as a focus for activity. By using simple analysis software you can not only monitor those patterns, but you can also measure and target their connectivity.
One final point here. All communities are networks, in so far as they are linked, but not all networks are communities. A community has a common purpose, it may not be stated, but it is known. It is the way we do things around here, which is not a bad definition of culture.