Improvement in the efficiency and productivity of the installation fleet through enhanced systematic planning and scheduling, underpinned by end-to-end data analysis.

Large energy suppliers were failing to achieve installation targets despite investment in their engineer workforce, meter installation fleets and commercial vehicles. The challenges included high demand in unpredictable locations, the requirement to match specific engineering competencies against those locations, diversity of operating models across different suppliers’ fleets, and the need to integrate with legacy systems inherited from traditional meter installation programmes.

Working closely with client teams, we conducted several sprints across three months, adopting a flexible approach. Upon mobilising an integrated team of business analysts and data scientists, we analysed the business processes and IT systems, identified and interrogated the data sources for potential improvement studies and developed a full suite of tools and improvement initiatives based on robust mathematical modelling of contract performance. 

Our analysis established baseline performance levels against which benefits could be tracked. We provided forecasts of programme performance for “as is” and “with improvements” scenarios, and compared against out turn measured performance. This provided an evidence-based foundation for tracking the efficacy of changes to strategic planning and commercial decisions. 

The net improvement was substantial, as smart meter installers raised their productivity by more than 60%. The practical impact of this work was greatly enhanced by our ability to embed the outputs into the clients' delivery processes, through an operational engagement programme following the analytics project, emphasising the vital role for the smart metering teams in realising the benefit from the outlined improvements.