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Best in class (BIC) denotes a superior level of performance in a particular area. PMG defines BIC as the average of the top quintile of a population. For example, in a population of 20 survey responses on inventory levels, the BIC level is defined as the average of the four lowest numbers; for inventory turns, on the other hand, it would be the four highest numbers. For a normal distribution, where about two-thirds of the population falls within one standard deviation, this means that more than 90 percent of the responses fall below the BIC performance level. This definition can be applied to the majority of quantitative and many qualitative practice-assessment questions, where a certain practice is recognized as superior to others. In addition to the simple example just given, best-in-class analysis can be used to provide insight into the range of operational performance levels associated with a particular strategy, practice, or financial result. For example, in an industry population of companies that have BIC delivery performance, we can see which manufacturing strategy and IT-enabled delivery practices are dominant. For companies that have BIC performance across a set of metrics, we can see what profit margin is achieved relative to other companies in their industry.
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APPENDIX A Source and Methodology for Benchmarking Data
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There are many survey questions where the BIC definition cannot be applied. Some examples include those related to demographics (e.g., number of locations) or business characteristics (e.g., percentage of sales by region) that do not represent relative performance and for which BIC is not applicable. While the BIC performance level provides a useful measure of the top level of performance represented by the best 20 percent of respondents for a given metric, the BIC levels across a set of metrics do not represent the performance of any one set of companies. For example, for a population of 20 companies in the chemical industry that primarily use a make-to-stock manufacturing strategy, the four companies that have the best delivery performance may not be the same four companies that have the best inventory performance. Because virtually no company is best in all metrics, PMG created an index consisting of several different supply chain metrics. This best-in-class company (BICC) index provides a method for sorting the high performer companies from the typical performer or low performer companies and enables comparisons among subpopulations.
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ENSURING QUALITY BENCHMARKS
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To be effective, a benchmark must have a precise definition that can be applied consistently across companies. For quantitative metrics, this means a clear description of the formula and the data sources. For qualitative practice measures, this means a detailed characterization of practices, including IT-enabled functions, and a rule to clarify how consistently the practice is used in the organization. Quality benchmarks are rooted in the age-old saying, An apples to apples comparison. PMG provides support and logical estimation techniques to participants during data collection and validates all survey submissions prior to creating benchmarks. Quality benchmarks are maintained by screening out data that are extreme outliers relative to the population, requiring a certain minimum number of data points, and updating the benchmarks on a regular basis based on the latest survey submissions. Confidentiality of company-specific data is ensured by disclosing only benchmarks, rather than individual company data, for use in comparisons with the database. The vast majority of companies consider measures of their internal operations and business-unit financial performance to be confidential. Contractual obligations between participating companies and PMG prohibit the disclosure of company-specific survey information, and PMG limits the disclosure of the names of companies in the database to companies that are interested in using the database.
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Strategic Supply Chain Management
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POPULATION DEMOGRAPHICS AND SCOPE OF SURVEY
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PMG s supply chain database contains several surveys that address an organization s supply chain activities at various levels, for example, surveys that focus on reverse logistics and repair operations or supply chain planning practices and performance. For both the analysis of BICC and the analysis of supply chain maturity (see Appendix B for a definition of stages of process maturity), we selected companies that had fully completed PMG s supply chain performance scorecard survey during 2002. This survey assesses quantitative performance based on the calendar year 2001 and dominant (2001) and emerging (projected for 2003) supply chain practices. The population consists of 89 organizations from 65 companies. The industry distribution reflects PMG s participant base, which is largely high tech (44 percent), followed by consumer goods (30 percent), with the remaining from process industries such as chemicals and pharmaceuticals (see Figure A-1). These organizations employ a variety of manufacturing strategies. More than half the companies use make to stock as their primary manufacturing strategy, and more than a quarter use make to order (see Figure A-2).
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