Predictive Metrics

Key Performance Indicators (KPIs) or metrics are based on historical information; therefore, they are backward-looking and often don’t help in predicting future events. This column discusses some tactics developed during research conducted for an MIT Master’s thesis, titled “Predictive Metrics for Supply Chains.” The tactics involve ways to transform or render historical data useful for predicting supply chain glitches and major shifts in a demand-supply chain. Larry Lapide | Dr. Lapide is a Research Affiliate at MIT and a Lecturer at the University of Massachusetts, Boston Campus. He has extensive experience in industry, consulting, business research, and academia as well as a broad range of forecasting experiences. He was an industry forecaster for many years, has led forecasting-related consulting projects for clients across a variety of industries, and has researched as well as taught forecasting. He was also a market analyst researching forecasting and supply chain software. (This is an ongoing column in The Journal, which is intended to give a brief view on a potential topic of interest to practitioners of business forecasting and planning. Suggestions on topics that ...