Feedback loops in the Knowledge cycle

Last week I described a “Pull cycle” for knowledge – let’s now look at the feedback loops in that cycle.

You can find description of the cycle here. This is a cycle based on knowledge demand (unlike the supply-side cycles you normally see) and includes the following steps;

  • The cycle starts with a problem, and the identification of the need for knowledge to solve the problem (the “need to know”)
  • The first step is to seek for that knowledge – to search online, and to ask others
  • Seeking/asking is followed by finding
  • However generally we tend to “over-find”. Unless we are lucky, or there is a very good KM system, we find more than we need, so the next step is to review the results and select those which seem most relevant in the context of the problem.
  • This found knowledge then needs to be integrated into what is already known about the problem, and integrated into solutions, approaches, procedures and plans.
  • Finally the integrated knowledge needs to be applied to the problem.
In the picture above, I have added the monitoring and feedback loops to each step, which work like this:
  • After the behaviour of asking/seeking, you feedback firstly whether there was any asking/seeking (so the organisation can track the behaviours of knowledge seeking) and you monitor and feed back the topics that people are asking about or searching for. You can for example analyse questions in a community of practice, or queries to a helpdesk, and you can analyse search terms from the corporate search engine logs. These will give you some ideas of the knowledge needs in the organisation, which knowledge supply has to match. 
  • After the finding step you feedback whether  you found the knowledge you needed, or not. This feedback will help identify gaps in the knowledge base where the knowledge needs are not being met, and can trigger the creation of new knowledge assets of articles.
  • After the review step you feed back whether the knowledge was relevant or not. In reality this feedback will be merged with the previous step. 
  • After the Integration step you feed back on the quality of the knowledge you found. This feedback will identify knowledge assets or knowledge articles which need to be updated.
  • After the Apply step, you feed back whether the knowledge was actually applied. This will help identify the most applicable and useful knowledge assets and articles. 
  • Finally, after the problem solution step, you feed back how much difference the knowledge made, and how much value was realised through problem solution. This allows you to track the value of the entire pull cycle and the entire knowledge management framework
Many of these monitoring and feedback loops are well developed in the customer-focused KM approaches such as KCS (Knowledge Centred Support), but any KM approach can apply these as part of their own KM metrics framework.
It is through the feedback associated with the steps that you can tell whether KM is actually working.

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