Whenever Manchester United play at home, eight hours after kick-off the local crime rate jumps by almost 10 per cent – regardless of the score. Yet, when Wigan Athletic play at home, there is no such effect on crime rates.
The weather also plays a part on crime rates in these areas of the UK. The number of crimes committed peaks at moderate temperatures, but the number of incidents police attend increases as the temperature increases. As it happens, criminals prefer to commit crime when the weather is mild. As wind and rain levels increase, both the number of crimes and incidents decrease. The way football matches and weather patterns are being used to fight crime in the UK is a prime example of the potential of ‘Big Data’ to transform business outcomes across the world.
For the Greater Manchester Police force big data has been ground-breaking in helping the force understand and predict police demand. The Manchester police have constructed a database that includes over eight million incidents and 2.5 million crimes in the ten year period to 2013. There are 120+ control variables… so far, and they are filtering relevant stories from public sources in 100 different languages. The aim is to build a map of expected criminal activity that enables the police to better allocate and deploy resources. From a financial standpoint, the benefits of more effective deployment will reduce the demand on police and compensate for a lack of funding.
Besides the weather and Manchester United games, the police have also learnt that, like real estate, location matters – one quarter of locations generate 80 per cent of incidents. This has radically improved crime prevention, as the policy can now anticipate where crimes are most likely to occur.
Super funds have an enormous amount of data at their disposal. Imagine if this data could be segmented to provide a better understanding of when a member is most likely to make a contribution or rollover; change their investment or insurance options, or need financial advice. What if funds knew when and where to target current or prospective employers or if they were able to predict where the next members were coming from and when.
Some Australian super funds are already crunching their data to better understand the behaviour of their members, their interactions and intentions. This is certainly what big banks and supermarkets are already doing, and more super funds will need to move down this path.
It will mean greater utilisation and allocation of resources in terms of BDM’s, administration and call centre staff. It could lead to better liquidity management and insurance offerings. Most importantly, it has the potential to improve engagement of members and employers as they will be able to relate to your super fund as a brand that understands their needs.
The best thing about data is that is never too late to start – the technology moves so quickly, it’s possible to leapfrog competitors. Better to be the frog than the lily pad.
So the next time you are watching Red Devils, think of where the police are being deployed eight hours after kick-off to prevent a crime. Then think of how your fund might be able to do something equally clever with data to retain a member or know when they will need advice.
Tom Garcia is chief executive of the Australian Institute of Superannuation Trustees