When a federal court ordered the DOE to develop more than 20 energy-efficiency rules, the first rule DOE created was a commercial rule for energy transformer distribution equipment. The new DOE...
Data Mining and Warehousing:
Many utilities have no ability to turn raw customer information into significant insights about their business.
In the utility industry, any discussion of improvements in either customer or revenue management requires consideration of the critical importance of the customer-information system (CIS). Pivotal to effective customer and revenue management, the CIS typically contains the vast majority of information needed to achieve the best possible levels of customer satisfaction. It also houses much data critical to a utility's operational efficiency. The CIS is the system of record for both customer and meter data, and in combination with asset databases, these information repositories comprise the lifeblood of every utility.
Although CIS modules typically are integrated for billing, account management, meter reading, credit and collection, work orders, rate management, and customer contact, they usually are not tuned for analysis or for easy reporting, and while almost all of the utility's customer interaction, revenue, and work order functions are handled through the CIS, a single view of the customer and the business processes surrounding the customer does not exist in most of the systems in use today.
Many utilities, as a result, are data rich but information poor, with repositories consisting of gigabytes or terabytes of customer data but with no ability to turn this raw data into significant insights on management, marketing, and investment strategies. This is particularly true when the CIS is running on a legacy platform, of which there are many still in use. The convoluted nature of the legacy software and the monolithic architectures upon which old solutions were built are not conducive to flexibility of data access and manipulation. Fortunately, the return on investment of replacing legacy software with new technology based on open, Web-based architectures is increasingly attractive, and as more legacy data is migrated to new CIS software platforms, it becomes increasingly easier to access and manipulate this data.
Enter the Data Warehouse
Utilities seeking to improve both strategic and tactical decision-making while achieving greater efficiencies are benefiting through efforts to create "one-stop" repositories for the retrieval of information, with an emphasis on more fully leveraging the information that's already been created and stored in existing data archives. Here, the focus is not so much on what's taking place but rather on understanding why specific events happen.
The first step in combining archived customer and operational data with emerging analytic functionality is to consolidate into a data warehouse all the data stored in disparate databases. A data warehouse stores large quantities of data by specific categories so it can be more easily retrieved, interpreted, and sorted by users, thereby enabling executives and managers to anticipate and respond faster to market situations and make better-informed business decisions.
Some business forecasts predict that every business will have a data warehouse within 10 years. But merely storing data in a data warehouse does a company little good. That's where data mining and customer analytics come in.
Data-mining tools enable user-defined analysis of data based on a robust data warehousing framework that provides a single view of