Knowledge mapping 2 of 3

My last post linked to some of my prior work on knowledge management (KM) but I resisted a link to knowledge mapping as I wanted to update the material. That will also involve revising some of the charts and material so I decided to simply write it up again as a process, stage by stage, without first rereading my original material.  I suspect it won’t be much different, but if it is that will be interesting; anyone who spots anything let me know.

Now auditing knowledge was common practice back in the 1990s when KM became a thing and it linked with the idea of knowledge as an asset that I referenced in my last post.  That people wanted to catalogue knowledge which resulted in taxonomies and a focus on what could be made explicit.  Anything other than explicit was cast into social interaction within communities of practice.  In fact, it was even more restricted because the explicit was limited to what could be written down, with a keyboard, in a database.  I don’t have the reference to hand, but I remember reading an article which demonstrated that doctors writing notes by hand paid more attention to patients than those typing into a computer.  I also still write notes using four different colour pens (blue and black alternating for what I hear or read, green for what I think, and red for things I have to do) which can include squiggles and other material.  I mark up textbooks the same way.  You will find key text marked as follows  ⌜text⌟ and then make notes in the margin, including a system of stars and ticks that I can understand but I’m not sure I can explain.  I also put key page numbers on the blank page you get at the start of the book with notes as to why.  I also read books by scanning (my dyslexia) rather than reading a line at a time.  Overall that encourages sense-making, my focus is not on being able to write a history of a subject but to contribute to moving the field forwards.  It is also far more efficient in search.  A few weeks ago I half-remembered something I needed to use and I suspected it was in Benn & Peters Social Principles and the Democratic State.   It was, it took less than a minute to find it and that was a result of said system.  It would not work with an e-reader.  In one of my pioneering projects using field ethnography with Thames Water, and in another project with Yorkshire Water, I found that engineers had maintained and updated record cards and books even post-computerisation because they had (sic) utility in practice.

Now that was a little bit of a diversion, but it makes the point that I was challenging orthodoxy in KM practice, and within my Christmas theme was even then arguing for Renaissance over Enlightenment; revel in the new, respect and don’t abandon the past.  The idea of knowledge as a flow, as well as a thing, was a part of that but it made me very resistant to the idea that you could catalogue the range of knowledge that was present or could be instantiated in the future.  The other issue for me related to the standard consultancy approach to auditing knowledge, namely conducting interviews to get people to list what they know.  For me, this was asking a meaningless set of questions in a meaningless context.

So that gave rise to two questions namely how do we ask a meaningful question and how do we create/understand what is a meaningful context?  That latter question divides into two, namely the context in which you ask a meaningful question and then how you understand, navigate and direct the flow of knowledge in use.   That meant that I started to talk about knowledge mapping not knowledge auditing.   I know that is a little unfair to progressive views of audit, but KM’s use of the word was not progressive.  I will make a note of one honourable exception to that, namely my friend  Patrick Lambe, although I do think he has yet to take the last steps away from convention; I live in hope.

So let me summarise how I addressed the question of meaningful questions and context.  Then tomorrow,  in the final post in this series I will outline the process step by step and remember that we have a Quickstart which will allow you to run the whole process (or parts of the process) with mentoring with a wider group of practitioners.

Creating a meaningful context to ask what people know is what started me into working with anecdotal narratives that in turn, combined with early work on ethnographic research, produced SenseMaker®.   We knew from experience that workshops and interviews were problematic in knowledge recall.  I now know much more about why from a theoretical perspective.  We’d also done a fully funded research programme on IBM Outsourcing contracts for Jan; I wish I could remember his name as he was one of the great senior leaders in IBM who had the courage to think differently.  That had shown that winning or losing a bid radically changed people’s memories.  All of that meant we started to focus on lessons learning rather than lessons learnt.  This a lesson that modern knowledge management has failed to learn, many like the idea but in practice they really want to run workshops as that gives a more controlled and politically safe response.  So we started to realise that we needed to ask questions as close as possible to the point of action, or if it was a matter of recall to work more indirectly to stimulate people to recall the past differently.  That focused us pretty quickly on decisions and for me, that was an easy step – most of my early work had been in decision support and that had taught me a lot about the differences between reality and textbooks.  So we started to collect and cluster decisions, and we found the best way to do that was to get people to tell stories about projects using timelines, and alternative timelines.  The side-casting method  Future Backwards was born from that work and it is still applicable here.   From that we moved on to gather decisions as they were made in diary form, often using apprentices.  For example, engineering students interview experienced engineers on oil rigs.  They knew enough not to be dismissed but were too early in their career to be treated as fellow experts which meant the stories were structured (without the need for promoting) to their level of abstraction which was much more useful.  Gathering those narratives, abstracting and clustering the decisions gave us the context we needed and also meant that we started to develop decision mapping as a supporting technique something that is now also made easier with SenseMaker® Genba, but more of that in the next post.

Asking a meaningful question triggered the development and refinement of the ASHEN typology and I linked to the material on that in my last post so I won’t repeat it here.  But that could be done at the post of capture, in workshops working with decision clusters or by online discussions.  Once complete we could recombine the material into knowledge objects, things that were coherent enough to be managed.  They could also be assessed based on the consequences of loss.  Key knowledge towards the EN end of ASHEN was a strategic issue if towards the AS end far less so.  Interestingly a lot of discoveries came out of this including the discovery of a radical disconnect between decisions recorded when they were made and the process maps of the organisation which described how they should be made.  Seeing that and making changes drive another key aspect of the knowledge mapping method.

Understanding the context in which knowledge was used was also key and that was when we started to focus on real current issues for the organisation, not just senior leaders but more critically middle management.  Nonaka famously said that change comes middle-bottom-up and I agree with him.  In a KM programme pay more attention to middle managers, not senior managers.  They have real problems, are less given to platitudes and are cynical in all the right ways.  They also have far more influence on if your KM programme is seen as useful or simply a nice to have, or worst still a pet initiative of a C-level Executive – you really don’t want to be there.  Gathering those, clustering them and ranking them allowed us to look at how the more effective management of knowledge could have both a strategic and operational impact, and critically moved away from buying technology to generate a practice, to see if technology could support a practice.

The net result of this was clusters of micro-projects, tangible and measurable rather than some grand vision about how things should be.  In the next post, I will outline that using the Hexi approach we are pioneering at the moment.

The banned picture is cropped from an original by Patrick Tomasso. Pebble construct is  by Jeppe Hove Jensen both on Unsplash