Even before bad debt shook the mortgage industry, Direct Energy was feeling its effects, including eroding revenue streams due to customer churn. Until, that is, the company effectively mined its way out in the best fashion: business intelligence.
"Various groups were pulling data from various systems and not having integrated information," explains John Katsinos, vice president of IS for Direct Energy's mass markets operations. "There was no way to tie together a customer's end-to-end lifecycle."
Without that holistic view of customer records, it was difficult for Direct Energy analysts to understand, let alone prevent, customer churn. So began BI Jumpstart, the company's initiative to give its analysts insight into customer actions that precipitate into the dropping of Direct Energy services, as well as tools for forecasting bad debt. The result has been savings of tens of millions of dollars and a more proactive approach to customer retention via more accurate pricing, forecasting, and targeted marketing.
"We wanted to mitigate the risk to our business and customer base, and to grow our customer base and revenue," Katsinos adds. "That meant being able to understand customer data at a level where we can forecast and predict behavior."
Katsinos kicked off BI Jumpstart by assembling a crack analytics team consisting of an IS project manager, a data modeler, a pair of ETL developers, an analytic developer, a BI architect, and a BI administrator. That group then implemented a "multilayered business intelligence" strategy that, Katsinos explains, comprises data warehousing, data marts, OLAP repositories, and ETL.
"Now, we can slice and dice any way we want," Katsinos says.
The result is a data miner's dream: Direct Energy analysts can use the integrated BI program to predict what customers in which areas are likely to turn over, then adjust the company's services, pricing, and marketing campaigns accordingly. For example, with BI Jumpstart in place, Direct Energy can now determine why one of its offerings experiences a 2 percent churn while another sees 20 percent of its customers dropping the service.
More than an initiative geared toward new revenue streams, BI Jumpstart helps Direct Energy make the most of what it already has.
"The biggest payoff has been the mitigation of lost revenue, reducing bad debt by $5 million, and reducing customer churn," Katsinos says. "We're already up to $28 to $30 million in savings -- well worth the price of the investment."
Moreover, "The return came quickly."
The upside of BI Jumpstart is far from fully realized. The project will soon move beyond Texas, Direct Energy's largest market and the least regulated in the United States, says Katsinos.
"We're now expanding the project to give a 360-degree view of all our mass markets in North America," Katsinos adds. "Now that we have a consolidated view, we're going to leverage that to forecast even more."
Consider it a pilot project worth $30 million.
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