The challenge – Big data analysis of membership records
Beehive was approached by the UK’s largest gliding club to help answer a perceived issue with membership numbers. It had been noticed over a decade that certain categories of membership had declined. Initially Beehive was asked to devise a research programme with lapsed members to establish why this had occurred and what it meant to the organisation in the future.
Instead of diving straight into a research programme with lapsed members, Beehive recommended that using big data analysis of membership records would be a more appropriate starting point. We obtained thousands of flying records (over 25,000 per annum over an 11 year period from 2004 to 2015), membership profile data (age, gender…etc.), financial information and other external data including daily weather data and the strength of the economy over the same period. Using big data analysis techniques we identified and correlated this information.
Our conclusion was that the issue with membership was a temporary one. It had been triggered predominantly by the recession. However launch volumes had been totally unaffected by the decline in the membership, but the biggest contribution was operational efficiency which, not surprisingly, correlated heavily with the weather.