John Tropea is one of my top Twitter friends for sharing interesting links and insights. Yesterday, he unearthed a great blog post from Patrick Lambe dating from 2006 (“If We Can’t Even Describe Knowledge Sharing, How Can We Support It?“). Patrick’s post starts calmly enough:
A combination of two very different incidents reminded me this week of just how incompetent we still are in KM at capturing the complexity, richness and sophistication of human knowledge behaviours. In the first incident I was asked to do a blind review of an academic paper on knowledge sharing for a KM conference. In the second, knowledge sharing was very much a matter of life and death. Although they shared a common theme, they might as well have represented alien universes.
From there, he becomes a bit more immoderate:
Let’s look at the conference paper first. After working my way through the literature review (a necessary evil), I started into the research proposal with my stomach starting to knot up and a growing sense of incredulity.
Although the authors had adopted Davenport & Prusak’s perfectly respectable definition of knowledge as a “fluid mix of framed experience, values, contextual information, and expert insight” it was becoming increasingly apparent as I worked my way into the paper that what they really meant by “knowledge sharing” was confined to contributing to and consuming from an online KM system. The research being described was designed to identify the factors that would indicate propensity for or against said behaviours. A knowledge sharing system that could, theoretically, be engineered.
Shame on them. After a good decade of practical effort and research focused on KM, how can people still think so mechanically and bloodlessly?
Justly immoderate, I think. Read on to see why.
It has to be right that knowledge in action is more valuable to organisations than inactive knowledge. Rory Stewart’s walking and engaging with people, as I wrote yesterday, shows one way in which high quality insight into complex systems can come from simple interactions rather than formal organised learning and knowledge. This is a point that Patrick made at greater length in an excellent paper he wrote in 2002 called “The Autism of Knowledge Management” (it’s a 23-page PDF downloadable from the linked blog post).
It depresses me that I have only just discovered this paper. Patrick wrote an incredibly useful critique of some traditional and ingrained organisational attitudes to e-learning and knowledge sharing. It should be much more widely known.
Here is his starting point:
There is a profound and dangerous autism in the way we describe knowledge management and e-learning. At its root is an obsessive fascination with the idea of knowledge as content, as object, and as manipulable artefact. It is accompanied by an almost psychotic blindness to the human experiences of knowing, learning, communicating, formulating, recognising, adapting, miscommunicating, forgetting, noticing, ignoring, choosing, liking, disliking, remembering and misremembering.
Once he has expanded on this, carefully defining what he means by ‘autism’ and ‘objects’ in this context, Patrick then presents and deals with five myths that arise as a result of this way of thinking. These are the myths of reusability, universality, interchangeability, completeness, and liberation. Of these, the one that struck me most was the myth of completeness:
The myth of completeness expresses the content architects’ inability to see beyond the knowledge and learning delivery. Out of the box and into the head, and hey presto the stuff is known. The evidence for this is in the almost complete lack of attention to what happens outside the computerised storage and delivery mechanism – specifically, what people do with knowledge, how it transitions into action and behaviour. How many people in knowledge management are talking about synapses, or the soft stuff that goes on in people’s heads? Is it simply assumed, that once the knowledge is delivered, it has been successfully transferred?
Knowledge only has value if it emerges into actions, decisions and behaviours – that much is generally conceded. But few content-oriented knowledge managers think through the entire lifecycle of the knowledge objects they deal in. Acquiring a knowledge artefact is only the first stage of what’s interesting about knowledge. We don’t truly know until we have internalised, integrated into larger maps of what we know, practised, repeated, made myriad variations of mistake, built up our own personalised patterns of perception and experience.
I can think of few more succinct and clear expressions of the process of knowing. In the organisational context, we need to be sure that everyone takes responsibility for developing their own knowledge — they cannot just plug themselves into a knowledge system or e-learning package. This statement shows why. The impact of this personal responsibility becomes clear within the section on the myth of interchangeability, where Patrick makes a valuable point about information and insight that resonated especially given my blog post from yesterday.
Beyond a basic informational level (and value added knowledge and learning need to go far beyond basic informational levels), when I have a specific working problem such as how to resolve a complex financial issue, the last thing I want is a necklace of evenly manufactured knowledge nuggets cross-indexed and compiled according to the key words I happen to have entered into the engine. Google can give me that, in many ways more interestingly, because it will give me different perspectives, different depths and different takes.
What really adds value to my problem-solving will be an answer that cuts to the chase, gives me deep insight on the core of my problem, and gives me light supporting information at the fringes of the problem, with the capability to probe deeper if I feel like it. Better still if the answer can be framed in relation to something I already know, so that I can call more of my own experience and perceptions into play. Evenness and interchangeability will not work for me, because life and the situations we create are neither even, nor made up of interchangeable parts.
We do have an evolved mechanism for achieving such deep knowledge results: this is the performance you can expect from a well-networked person who can sustain relatively close relationships with friends, colleagues and peers, and can perform as well as request deep knowledge services of this kind.
I suspect that (whether inside our organisations or otherwise) we can all identify people whose personal networks add significant value to their work and those around them. (And probably plenty whose silo mentality brings problems rather than focus.)
In his conclusion, Patrick presents “six basic principles that seem to work consistently in our knowledge and learning habits; principles that knowledge management and e-learning technologies need to serve.” These are:
- Highly effective knowledge performers prefer knowledge fragments and lumps to highly engineered knowledge parts.
- Parts need to talk to their neighbours.
- The whole is more important than the parts.
- Knowledge artefacts provide just enough to allow the user to get started in the real world.
- Learning needs change faster than learning design.
- Variety is the spice of life.
I need to read this section again — it didn’t resonate as well for me as the rest of the paper. That said, reading the paper again will be a delight rather than an imposition. I recommend it highly to anyone with an interest in knowledge and learning processes, and the systems we create to support them.