The volume of data generated within this health service provider is enormous. As a result, consolidating, let alone identifying patterns, is a huge undertaking. Mitie manages a range of sites for this organisation, from small GP consultancies to multi-site hospitals.
Tasked with finding opportunities to reduce maintenance costs, our Data Science team set to work
At the completion of the analysis we recommended a data-supported strategy to reduce reactive maintenance work by 10%.
Our maintenance data analysis was focused on discovering any anomalies relating to equipment failure and the associated costs. Following this review, we discovered that maintenance work on lifts is consistently the most expensive kind throughout the customer’s portfolio. We were able to prioritise remedial action to the most affected sites by ranking location by maintenance cost-per-square-metre. Finally, we prepared a detailed analysis for every high spending site, and recommended changes in maintenance suppliers and practices.