A Scientific
Approach to Cost and
Performance Benchmarking
Performance Benchmarking
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A Scientific
Approach to Cost and Performance Benchmarking |
About Us
J Lewis & Associates specializes in scientific benchmarking of costs and performance predominantly for electric utilities and transit systems. New research in the educational field is presently focused on Washington State 4th, 7th, and 10th Grade WASL pass rates. We call our analytical approach Multi-Dimensional Benchmarking (MDB). Our basic approach uses historic data to test for and quantify the relationships that exist between the physical aspects of an entity (i.e. size, age, location, etc.) and the operating costs and performance of that business. We have compiled extensive databases on electric utilities, transit systems, and Washington State high school 10th grade WASL results Using these databases and commonly used analytical techniques including a combination of iterative variance analysis and complex non-linear multiple regression, we have isolated and quantified the mathematical relationships that exist between these characteristics and the parameters studied. These mathematical relationships are subsequently used in models to normalize (i.e., equalize) all the entities being analyzed. Applying these factors puts dissimilar entities on the same basis; in other words, turns apples and oranges into just apples—rather like setting handicaps in golf. Finding these factors is often referred to as Data Mining. Data mining encompasses testing as many physical, cost, and performance data sets as reasonably available to discover the true relationships that exist between them as opposed to trying to verify theoretical hypotheses. By using this approach, in many instances, unexpected relationships are found and expected relationships are sometimes found not to apply or to apply in a different way. In traditional benchmarking, entities compare themselves with other similar entities (small peer groups) or on a single dimensional basis with the industry at large on a single year basis. Single dimensional comparisons include dollars per customer, customers per employee, etc. These approaches often result in confusing or misleading conclusions and none provide precise results. On the other hand, our MDB approach uses multiple factors simultaneously over a seven-year period to find the mathematical relationships that exist between an entity’s physical aspects and its costs and performance. By using MDB, all entities regardless of their characteristics can be compared on a common basis. As a result, average and optimal performance for each individual entity can be determined with a high degree of precision. |