Case Study - Electricity Retailer

Our client is an energy retailer that purchases energy on the open market and sells it to consumers and businesses at retail prices. For the client to purchase electricity (the product for this project), they had to predict end user load usage as accurately as possible. Discrepancies in the predicted vs. actual load consumption by the customer was leading to losses for our client. They were either purchasing excess energy that was going to waste or if they did not purchase enough energy, they were having to purchase the shortfall on the open market at very high costs. Unfortunately there was no way to store unused electricity for later consumption.

Complicating the issue, there were several stakeholders involved in providing the data, namely the energy and services vendors, the utility companies, and the electricity contract data that was signed by the clients’ sales staff with the consumers of electricity.

The client was desperate to solve the problem, as they were consistently losing money on every contract they had. Given that most contracts were for 5 years, there was no opportunity for re-negotiation of prices within a reasonable time frame. In addition, they were unable to sign on more customers as there was no way to know if they would be profitable.

Learn we helped them solve this problem using Digital Lean Sigma.