<P> Another approach to making comparisons involves using more aggregative cost or production information to identify strong and weak performing units . The two most common forms of quantitative analysis used in metric benchmarking are data envelope analysis (DEA) and regression analysis . DEA estimates the cost level an efficient firm should be able to achieve in a particular market . In infrastructure regulation, DEA can be used to reward companies / operators whose costs are near the efficient frontier with additional profits . Regression analysis estimates what the average firm should be able to achieve . With regression analysis, firms that performed better than average can be rewarded while firms that performed worse than average can be penalized . Such benchmarking studies are used to create yardstick comparisons, allowing outsiders to evaluate the performance of operators in an industry . Advanced statistical techniques, including stochastic frontier analysis, have been used to identify high and weak performers in industries, including applications to schools, hospitals, water utilities, and electric utilities . </P> <P> One of the biggest challenges for metric benchmarking is the variety of metric definitions used among companies or divisions . Definitions may change over time within the same organization due to changes in leadership and priorities . The most useful comparisons can be made when metrics definitions are common between compared units and do not change so improvements can be verified . </P>

Define the term benchmarking and describe the steps for benchmarking