Monday 12 December 2016

Garbage lessons in, garbage knowledge out

If we think of Knowledge Management as a supply chain, moving knowledge from the suppliers of knowledge to the people who need it, then feeding poor quality lessons into the system will result in poor knowledge output. 

"Garbage in, "garbage out", or GIGO is a truism for any informational system, reflecting the idea that poor-quality input will produce faulty output. Wikipedia traces the genesis of the concept back to Charles Babbage, as follows;

On two occasions I have been asked, "Pray, Mr. Babbage, if you put into the machine wrong figures, will the right answers come out?" ... I am not able rightly to apprehend the kind of confusion of ideas that could provoke such a question. — Charles Babbage, Passages from the Life of a Philosopher 

The same is true for Knowledge Management systems and frameworks. The knowledge that you get out of the system will only be as good as the knowledge you put in.

One of the more common inputs to the KM cycle is lessons. Operational lessons are collected, documented, gathered, stored, synthesised, and output as guidance, advice, checklists or other knowledge items. However if the lessons are poor quality, then the output knowledge items will also be poor - either lacking detail, overly generic, biased, or just plain wrong.  And with wrong knowledge, you get wrong results.

Therefore your lessons capture process must include a level of quality assurance, to ensure that collected lessons are

  • valid
  • valuable
  • usable
  • objective
  • well written
  • and helpful to the reader. 
We believe the best way to capture lessons is through facilitated team discussion, ensuring that lessons are built on ground truth, which has been well analysed to find the root cause, and then restated as future advice. 

A supply of good quality lessons ensures the transfer of good quality knowledge, and avoids GIGO.

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