PRODUCTION LOSS FUNCTIONS AND SUBJECTIVE ASSESSMENTS OF FORECAST ERRORS - UNTAPPED SOURCES FOR EFFECTIVE MASTER PRODUCTION SCHEDULING

Master production scheduling is complicated by demand uncertainty. The problem from uncertain forecasts is scheduling either too few or too many components relative to actual demand. To cope with this problem, schedulers often form judgments about future forecasts and they adapt production schedules to reflect beliefs and opinions about forecast er rors. The research literature on scheduling has largely ignored formal methods for capturing these informal judgments and injecting them exp licitly, rather than informally, into the master scheduling process. T he current research demonstrates a method for using subjective assessm ents of forecast accuracy to improve master scheduling. First, a produ ction loss function is derived using performance data from computer si mulations of the production environment. Second, subjective assessment s of forecasts errors are integrated with the loss function to reveal how forecasts should be adjusted to minimize expected scheduling losse s. The procedure enhances intuitive judgmental scheduling; it reveals how managerial beliefs can be formally used to intentionally and optim ally bias forecasts. In applying the procedure to 44 simulated MRP con figurations, the optimally-biased forecasts are superior to unadjusted forecasts and provide an objective benchmark for using judgmental adj ustments. The results demonstrate opportunities for enhancing master s chedules by using subjective assessments of forecasts compared with sc heduling without subjective assessments.