Microlise now captures seven billion miles worth of driving data every year in the UK. Whilst customers use this data within their own systems to drive forward efficiencies around safe and economic driving, journey management and electronic proof of delivery, the capacity for Microlise to be able to do something with these large volumes of anonymised data is significant.
Opportunities are presenting themselves in a number of areas. For example, safe and economical driving, allowing our customers both within their traditional reporting environment, but also on a wider basis, allowing them to understand how their performance compares on an anonymous basis, with their peers.
Predicting Unforeseen Risk
In a similar vein, being able to use Big Data to identify by operation type, vehicle type, time of day, time of year and weather risk areas presents a big opportunity. It enables us to see areas of harsh braking, speeding and harsh cornering and we are now starting to share this information with external agencies to help them understand how risk factors correlate with black spot areas.
Understanding Traffic Flow
Very soon we will be introducing high resolution tracking functionality. By this we mean that we will capture even more granular tracking data, at one second intervals. This is very powerful for practical applications, for instance, capturing more information about speeding incidents. But in the context of this piece it also allows us to understand traffic flow rates and movement in great detail.
At the Microlise Transport Conference, we heard from Transport for London on how they want to match traffic frequency to road capacity. Having high resolution Big Data available for analysis will help organisations like this to achieve their plan, ultimately delivering better support to logistics operations. Other areas where we are capturing data that will benefit from Big Data includes planned versus actual analysis, helping us to understand the factors causing the biggest impact on deviations from planned routes.
Improving Vehicle Health
We now also capture an unrivaled amount of data from the vehicle in relation to engine health. This includes temperature levels, pressures, wall diagnostic trouble codes as well as tell tales from the FMS-3 standard. This information is being used by drivers and operators to understand when and if a vehicle is developing a fault. This data is being consumed within our own customers operations, but we also have an excellent opportunity with our OEM partners and their tier 1 suppliers to start using that Big Data information, linked to service records, to provide better levels of predictive analytics.
So in summary, Big Data is not an over-hyped pipe dream. We are seeing the use cases for it now and though I have focused on three applications here, there are hundreds more exciting uses.