While managing day-to-day operations of a comprehensive portfolio of programs and preparing for a new filing with the Commission, the Energy Efficiency Manager of a Mid-Atlantic utility was tasked with reporting portfolio performance key performance indicators (KPIs) to senior management on a monthly basis. Some of these KPIs were straightforward and readily available in the existing energy efficiency (EE) tracking system. Others, however, were not explicitly tracked and required an analytic process to be developed to support monthly reporting. The most challenging of these KPIs was “participation,” as most tracking systems are built around EE measures, not on unique instances of participation. Based on MCR’s track record of successful engagements with the client over more than a decade, the Energy Efficiency Manager asked MCR for help.
MCR utilized our deep knowledge of our utility client’s data and systems to determine which KPIs could be derived analytically and if there were gaps in the existing data. Working with the client’s implementation contractors, MCR developed a monthly process of collecting additional data to fill those gaps. This process entailed automated email reminders and a web-based data collection form, which ensured consistent and validated data delivery.
Additionally, we established a set of analytic procedures to summarize the KPIs already in the tracking system and to calculate those derived synthetically. In order to improve efficiency and to ensure consistent results for these monthly reports, MCR developed this analytic process with the R programming language.1 Once the data has been collected from the implementation contractors and the EE tracking system, the analysis script need only be run for the full set of KPIs to be computed.
By using our extensive knowledge of the industry, the client’s data system, and modern analytical tools, MCR was able to deliver accurate, monthly KPI metrics covering a number of reporting dimensions, including many that were not directly tracked by program management. The initial KPI report was developed and presented under a short deadline imposed by our client’s senior management in the context of many competing priorities. In addition, MCR was able to ensure consistent reports each month providing our client with high confidence in the results.
1 R Core Team (2021). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL https://www.R-project.org/