Posts Tagged ‘knowledge management’

An effective knowledge management strategy is mandatory for any organisation wanting to succeed in today’s knowledge-based economy.  Such strategies should cover the creation of knowledge as well as the systems that allow for it to be stored, shared and used as a catalyst for the creation of further knowledge.


That said, regardless of the form that shared knowledge portals take, they remain stubbornly under-used and under-stocked.  This is likely to remain the case for as long as they require staff to shift their effort away from their immediate activities to find, read and interpret other peoples’ work.  A knowledge management strategy built around tools that sit outside of the day-to-day activities of an organisation’s staff is unlikely to add real value


But, by developing a culture of test-and-learn analytics, it is possible to entrench knowledge within its “organisational DNA”.  In so doing, that knowledge becomes easier to store, easier to share and easier to access.



Test-and-learn is a simple but often misapplied concept.  When it ingrained within the culture of an organisation, however, it can deliver excellent financial and knowledge management results.  Based on the scientific method, it first came to prominence as a business concept in the late eighties when American credit card issuers used it to dramatically grow their industry.


Test-and-learn analysis is an evidence-based technique whose starting point is always the hypothesis that a proposed new strategy will be more profitable than the incumbent strategy.  This expectation is usually based on an analysis of existing data stored in in-house databases but could also include experience “stored” within the minds of staff members and information acquired from third-parties.


But business decisions should not be made on hypotheses alone and so theses hypotheses must first be tested.  It is from the results of this testing that learnings are gained.  The test must compare the proposed strategy to the incumbent one in a controlled environment free from extraneous influences.  The results of the test are monitored are then subjected to statistical analysis to identify the more profitable of the two strategies.  Thus identified, the ‘winning strategy’ is rolled-out across the board and becomes the incumbent strategy against which any future hypotheses are to be tested.


Consider a marketing analyst working for a retail bank who must chose between two potential marketing campaigns designed to generate applications for credit cards.  Traditionally, the bank’s new customers were enticed with the offer of a year’s free membership to its loyalty programme.

Our analyst, however, hypothesises that more customers would apply for a card if the bank offered to waive the card fees for the first year.  Wanting to make the best use of her limited budget, she must first design a test to prove her hypothesis.  A portion of potential customers will each be randomly offered one of the two options.  After two months of careful analysis, she will be able to prove whether customers respond better to her “no fees” offer.  This real evidence will justify her using the bulk of her marketing budget to advertise her “no fees” offer.  The successful strategy then also becomes the standard against which all future marketing strategies are to be compared.


The test-and-learn approach therefore creates a circular pattern as it moves an unproven hypothesis from theory to established fact against which, in time, new hypothesis will be tested.  This circular nature is what makes the test-and-learn approach a good knowledge management tool.


Creating Explicit and Collective Knowledge

The example began with tacit individual knowledge in the form of a marketing analyst’s hypothesis that a “no fees” offer would improve response rates.  By testing this hypothesis in a scientific manner, she was able to turn that tacit knowledge into explicit knowledge.  At this stage though, that explicit knowledge was only held by the analyst running the test – i.e. individual explicit knowledge.  However, as soon as the learnings from the test were used to change the marketing strategy, everyone who came into contact with the new strategy would also become explicitly aware of the new knowledge.


The test-and-learn process can therefore be simplified into three stages – “developing the hypothesis”, “testing the hypothesis” and “taking action”.  Each of these stages, in turn, represents a stage in the knowledge management process – “tacit individual knowledge” becomes “explicit individual knowledge” and then “explicit collective knowledge”. 


So, once the culture of test-and-learn analytics is fully embedded within an organisation, any member of staff need only look at test outcomes to have de facto access to all the relevant knowledge of that organisation.  Because the “free loyalty programme” campaign was replaced by the “no fees” campaign anyone with an interest in the organisation’s marketing strategies will know that the “no fees” offer is better.  Every time this knowledge is updated, for example if it is subsequently found that response rates do not drop if it is only the first six months’ worth of fees that are waived, those same stakeholders will once again have access to the new knowledge when the strategy is changed again.


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