In my experience large bureaucracies often have high staff turnover and internal movement across silos. Most often this is because they are hierarchical organisations, and movement is necessary to obtain a promotion. But it also occurs because people are dissatisfied and moving to another job at the same level in a different part of the organisation is relatively easy. The problem with bureaucracies is the need for individuals to leave their mark in order to progress. Often this creates white knights and one-man bands. What do I mean?

White knights have been in the organisation before and have done a good job. They have been away for a while and their work has been largely invisible to their previous organisation. Now they come back and they believe they have sufficient authority and experience to fix problems as they saw them previously, and many in the organisation see them as the agent who can fix their existing problems. The trouble is the problems are different. White knights often don’t have situational awareness, and they don’t know what has changed in their absence. Worse still they don’t know why something was changed. They charge in with good intent to save the day, but create havoc all around them, and that havoc creates disillusion.

White knights are often one-man bands. Now I don’t know if you have ever heard a live one-man band. I have at a circus performance and it was terrible. White knights who are one-man bands think they can solve everything and have the where with all to do so, but of course they don’t. They take on more and more work and become less and less effective, and then they become disillusioned themselves.

So what I hear you say? Well the point is it is quite easy to identify the bottlenecks in an organisation using business network analysis™ techniques, and in particular social network analysis techniques. Bottlenecks are often one-man bands, with too much on their plate. It would also be quite easy to attribute data to identify traits, like the white knight or the black leader . And dare I say it an archetype network analysis could be very interesting.

It's very easy to become enamoured with the visualisations and potential of network analysis, and see it as an end unto itself. This is one reason why I think that network analysis is a diagnostic methodology. It can aid understanding, but there are obvious limitations. For example any visualisation is a representation, or report of, data collected at particular time in a particular place. We all know human systems are dynamic, so it's reasonable to assume data will degrade and the network will change.

It is also a common mistake to think the visualisation, or the data matrix, represent analysis: they do not! I think Drew Conway , who is a political scientist, makes the point very well when he says:

"Simply because your data links people and you can visualize that, it does not mean you have performed network analysis. This is akin to displaying a line plot of some stock's price over a quarter and claiming you have performed statistical analysis-no-you have reported data. As with all other statistical processes, network analysis is meant to draw meaning and inference from the structure, which requires an understanding of these methodologies, their strengths and limitations".