Client context
Platform Housing Group is one of the largest housing associations in the Midlands, managing more than 47,000 homes and serving around 120,000 residents. Its in-house repairs service, Platform Property Care, manages more than 100,000 repairs each year.
The business problem
The organisation wanted to improve visibility into “linked repairs”: multiple repair visits and jobs that were actually connected to a single underlying issue. These hidden inefficiencies were increasing costs, creating avoidable repeat visits and negatively impacting resident experience. Leadership needed a way to understand the true time and cost of repairs, identify root causes and intervene earlier.
What we did
Red Olive developed a proof of concept using advanced analytics and predictive modelling. Using six years of historical repairs data, we applied our Infinite Insight Methodology to identify patterns indicating when separate repair jobs were likely to be linked.
The analysis uncovered recurring causes of inefficiency, including repairs requiring multiple visits, trades and unplanned follow-up work. The project delivered a systematic method for identifying linked repairs, visibility into true costs, insight into root causes, and predictive models to support earlier intervention.
The results
The project demonstrated how data and predictive analytics can help housing providers improve operational performance while delivering better resident outcomes. Key benefits included reduced repeat visits, improved understanding of operational inefficiencies, better visibility of repair performance, and a foundation for future AI and predictive maintenance initiatives.
Looking ahead
Platform Housing Group is exploring additional data and AI use cases, including predicting repairs and complaints earlier, using IoT data to improve maintenance planning, and applying computer vision and document intelligence to improve home safety processes.
