A technique called balanced benchmarking provides managers with a sophisticated mechanism by which to assess and manage the effectiveness of different branches or units.
In his 2003 book Moneyball: The Art of Winning an Unfair Game, Michael Lewis described how the Oakland Athletics baseball team used statistical analysis to identify undervalued players.1 One lesson from the baseball world of “moneyball” is that we can’t always trust our intuition about how employees will perform. Savvy business managers know that their intuition can often be misleading, if not downright incorrect. And just as sports teams have increasingly relied on rigorous quantitative analyses, so have many businesses. In particular, a growing number of service businesses have been investigating the use of a sophisticated linear programming technique called DEA, or data envelopment analysis. (In this article, we use the term “balanced benchmarking” to denote DEA.) The technique enables companies to benchmark and locate best practices that are not visible through other commonly used management methodologies. (See “The Basics of Balanced Benchmarking.”) When it was first introduced in the 1980s,2 balanced benchmarking was an academic tool for measuring and managing the relative efficiency of peer organizations. Balanced benchmarking required the adaptation of various computer programs, so its use in the 1980s was limited to a small group of academics and practitioners with linear programming expertise. Early users were able to apply and generate results from balanced benchmarking that demonstrated its effectiveness, but its inaccessibility limited its independent adoption and application by managers. However, shortly after 2000, balanced-benchmarking algorithms were adapted for Excel software — making it accessible to users with little or no knowledge of linear programming.3 Balanced benchmarking is unique both in its ability to identify paths to improve productivity and in its value as a complement to other analytic techniques. Balanced benchmarking simultaneously considers the multiple resources used to generate multiple services, along with the quality of the services provided. For example, bank branches can use six or more types of resources and provide 20 or more types of services, all of which are considered with balanced benchmarking.