Magazine article CRM Magazine

Predicting Debt: One of Michigan's Largest Energy Providers Turns to Intelligent Results to Analyze the State's Bankruptcy-Stricken Population

Magazine article CRM Magazine

Predicting Debt: One of Michigan's Largest Energy Providers Turns to Intelligent Results to Analyze the State's Bankruptcy-Stricken Population

Article excerpt

* Tell us about your organization. DTE Energy is an energy company that provides electric and gas service to more than 3 million residential, business, and industrial customers in Michigan. In 2006, we had sales of $4.7 billion in electric and $1.9 billion in gas.

* What problems were you facing? The economic conditions in our market are difficult, to say the least. Michigan has the highest rates of unemployment, bankruptcy, and foreclosure in the nation. Due to the local economic conditions, we're consistently faced with a large percentage of customer accounts going into collection, and we were looking for a better way to understand those portfolios. We needed to identify ways we could work more efficiently with customers, without sacrificing customer satisfaction or raising rates.

In the past, we had segmented accounts using factors such as balance, age of debt, and account history. We needed to take a more scientific approach in predicting customer behavior. We were looking for a predictive analytic solution that would give us the ability to segment accounts and predict a customer's behavior and propensity to go into debt or collections.

* How did you select a vendor? We evaluated a number of products on the market and choose Intelligent Results' Predigy platform. Flexibility was the key: Our selection process was driven by the ability to develop and customize predictive models. Predigy offered us the most flexibility to create models based on our own data, such as the "champion/challenger" method, to statistically compare new strategies for our customers. We began the project with a proof-of-concept in the beginning of 2006, and within six months we had deployed Predigy in most of our operational departments.

* What have been the main rewards? We've experienced a 700 percent increase in net savings and have reduced our collection efforts by more than 15 percent. In addition, the reporting makes it easier for DTE to understand the distribution of an economic factor within a certain population.

For example, we wanted to maintain the amount collected while reducing operating costs, and to document any lessons learned for future use. We analyzed accounts and were able to prioritize efforts based on a charge-off model score. Using the "champion/challenger" strategies for account groups in various stages of collection, we determined that most early-stage accounts provided better results when contacted less frequently: People were more likely to pay if DTE contacted them less. …

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