- Reduce the number of ‘do not attends’ for appointments by allocating more appropriate times for certain demographics – i.e. a Wednesday afternoon instead of a Monday morning for an 18-year-old male student.
- Reduce ambulance fuel consumption by identifying ‘hotspots’ and station vehicles closer to them, or creating best routes to take to A&E depending on the time of day.
- Reduce pressure on operating theatres by making the most of existing theatres taking into consideration things like non-clinical preparation times and standard operation times per surgeon.
- Improve tax collection by identifying those who are unlikely to pay i.e. those who won’t pay and don’t care about consequences, versus those who can’t afford to pay.
- Improve police resourcing at an event i.e. football match by taking into consideration things like weather, opposition, distance to travel of away fans, the day of the week and times.
- Reduce the need for street cleaning by placing more litter bins in places with high footfall, to identify most common areas for fly tipping.
- Save money on transport by reducing refuelling times, or improving the planning of maintenance based on vehicle usage and parts wear.
- Increase the competitiveness of your insurance company by using customer data to give a more personalised underwriting using more detailed factors.
- Increase your number of online sales by identifying where people most commonly drop out and either do not purchase from you or have to contact customer service to continue purchase.