[BETA] Fortnightly

IT TAKES LABOR, FUEL, OPERATING CASH AND INVESTMENT capital to produce and deliver electric power. Which utilities have managed to use these resources optimally to produce and sell kilowatt-hours? How do these utilities compare with each other? Is there room for improvement?

And what about financial success? Does efficiency, as measured by a ratio of inputs to outputs, serve as a reliable predictor of market-to-book ratios or merger premiums?

Some of these questions are answerable; others not. Yet a simple observation of the range of utility expenses on the four basic inputs - fuel, capital, labor and O&M - can provide a window of which company we might choose to label as "most efficient." This method also allows a less-efficient utility to identify "peer" companies higher up on the ladder, to mark as examples to emulate.

Economists have wrestled with these questions for a long time. Several ways to provide an answer have been proposed and used, from the simple back-of-the-envelope method to complex multi-equation econometric models. The questions and the tools are becoming increasingly relevant in today's utility markets. To stay competitive in a restructured environment, utilities are searching for ways to understand productive efficiency better, to cut costs and to ensure survival in the 21st century.

Using historical data for 140 holding companies in the United States, we analyzed the relative efficiency of the top 100 using Data Envelopment Analysis (DEA), an approach for measurement of operational efficiencies and identification of "peers" to be used as best benchmarks.

Economic theory of productive efficiency is based on the comparative analysis of the best-in-class producers vis-à-vis all others. The criterion for determining the "best" producers refers to the ability to produce maximum output given a specific level of input, or conversely, the ability to use the least amount of input to produce a specific level of output. DEA is a linear programming technique first introduced in the early 1980s by Charnes, Cooper and Rhodes. It has since been used in various applications ranging from healthcare to banking to retail. Fortune magazine stated that DEA is a tool every manager must have if his business is to remain competitive. We used static and dynamic DEA methods to measure annual operational efficiencies of holding companies as well as their respective improvements over time.

Striving for Efficiency

Increases in productivity may prove the key to competitive advantage of any economic enterprise. Yet few take the necessary steps to actually measure it. The measurement of productivity by economists, for the most part, is based on comparisons between inputs and outputs. The complexity ranges from Robert Solow's econometric production functions to the Jorgenson Divisia index to simple ratios of output to input (for example, MWh per employee).

Productive efficiency can be measured in terms of input-conserving or output-increasing orientation. Choice of orientation in most cases won't impact efficiency ratings significantly and will identify the same efficient utility companies. Since holding companies are more likely to have control over input usage than over demand for output, we chose