Tuesday, 31 March 2015

Evidence-based decision making

We all have biases. It's perfectly natural for the decisions we make in life and work to be influenced by knowledge gained through prior experience and intuition. Most of the time this serves us well. However we would not expect major business decisions to be made just on on 'gut-feel'.
Using an open and transparent evidence base for decision making is now common practice in the Health and Third sectors and increasingly in Government policy making. Retail has been driving value from its customer data for years. Quality data, available in real-time is becoming an increasingly important resource for every organisation. Sources and quantity of data are proliferating and becoming almost cost-free; witness the 'internet of things' and open government data. Amazon and Facebook were built ground-up on 'big data' *.
However the analysis and facilitation skills needed are not keeping up with the huge leaps in data technology. By that I don't mean data scientists' skills, but managers' ability and confidence to make business decisions predicated on data analytics. A recent McKinsey insight highlighted the need for organisations to adapt if they are to get big results from big data. The example they give is that of an organisation geared around weekly or daily product price adjustments. Unless they adapt their business processes to leverage real-time competitor pricing and market conditions, they won't get the benefit from that data.
I am currently planning the Knowledge and Innovation Network members' Autumn quarterly workshop 'Evidence-based Decision Making'. This event is not for 'techies' or data-geeks; we will be looking at the organisational capability, processes and skills needed by KIN member organisations to improve rapid decision making. We have a great line-up of thought-leaders, case studies from members and experiential learning activities proposed. The KIN calendar will be updated as they are confirmed.
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* I'd heard the phrase 'big data' many times, but admit I didn't really know what it meant. Margaret Rouse has a useful explanation in her graphic; it is about exponential volume (Mb to PetaBytes), velocity (from batch processing to real-time) and variety (from spreadsheets to unstructured social data).

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