"….the blueprints for the Saturn rocket have been lost and much of the knowledge of the 400,000 engineers that made the first moon landing possible lies in documents that are devoid of meaning without the contextual and personal knowledge of those who generated them."
"NASA had lost knowledge of how to manufacture the material because it had kept few records of the process when the material was made in the 1980s, and almost all staff with expertise on production had retired or left the agency"
The cost of knowledge, in this case lost knowledge and attrition, is one of the reasons that we need a KM department; to coach and counsel organisations in the value of knowledge, and moreso the lack of resilience in a loss of knowledge.
A lot of KM has to do with knowledge sharing, (especially across silos), accessing people who can help, communication, and awareness…and we claim the lack of this is partly to blame for disasters perhaps like "Tsunami Japanese Nuclear Plant" the "Challenger space shuttle disaster", "9-11" etc…just quietly this may be more a problem of seeing the world as connecting the dots, rather than anticipatory awareness.
In this case the aspect of KM I’m talking about is observable work…which of course can help with awareness and other points I’ve mentioned above, but it also helps in understanding why decisions were made. If we can find the workings out, the work-in-progress, the thinking out loud conversations, the peripheral information, then we will understand the meaning and the context behind decisions.
Not only that, we can re-mix these nuggets of work-in-progress and assemble them with other thinking to create something entirely new…this is KM as a flow or as a flux…fragments connecting, morphing…
"Why was this decision made in paragraph 2 on page 3…I want to use the thinking behind this for something else" asks the manager.
"I’m not sure, it must be in emails, minutes of meetings, buried in our repository…one of those people are currently on vacation and the other has left the organisation" says the worker.
That’s right our knowledge is in our head and is represented in conversation and email communications…where it goes to die. Hence Ross Mayfield’s brilliant insight in using social tools for doing work; which retains the represented knowledge by default. Not only this; but it can be commented on, talk to the author, re-used, enhanced, re-mixed…
In a comment on a past post I likened this to a maths problem:
"Again this is like a maths solution to me in a way
From equation to solution
- show me the workings out
- show me all the paths that we took that failed
- in essence show me all the conversations around each step in both the failed paths and successful path"
And all this brings me to the idea of having an inventors notebook and diary; all the thinking (and the "way" they think), workings out, conversations, peripheral information, and even failed attempts and wrong paths.
Without this how do we know why decisions were made (make sense of something without the underlying context), why they may have failed to see some things (again the context of the time or situation may give clues), what to avoid (which helps to not re-invent the wrong wheel), how to replicate starting conditions, how to re-create things, and how to take a fragment that made up a product and use it in another product.
Not just the know-what, but the know-why, and a glimpse into the know-how.
If we go back to the NASA documents; they are merely information…KM is not just about content and finished products. The repository of documents is not good enough if you can’t make sense of it…and a best practice may not be able to transfer to the new context or complexity of the situation. We need to connect with the authors or at least see their trails of conversation that led to these documents…only then can we get closer to the know-how and know-why. In this respect KM has more in common with observation, apprenticeship, conversations/stories than it does with organising documents (information management).
Here’s an example:
"In a blog post in January 2009, Gowers asked whether spontaneous online collaborations could crack hard mathematical problems—and if they could do so in the open, laying the creative process out for the world to see.
As Gowers wrote on his blog, Polymath may be “the first fully documented account of how a serious [math] research problem was solved, complete with false starts, dead ends, etcetera.” Or, as Tao puts it, the project was valuable because it showed “an example of how the sausage is made.”
If you want an extended look at this thinking consult my two posts: