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Linking performance drivers in production planning and inventory control to process choice
Authors:MHossein Safizadeh  Larry P Ritzman
Institution:Department of Operations and Strategic Management, Wallace E. Carroll School of Management, Boston College, Chestnut Hill, MA 02167, USA
Abstract:This study investigates how process choice relates to production planning and inventory control decisions. We empirically examine the validity of deductively derived patterns about these types of decisions. More importantly, we look for normative insights by exploring how production planning and inventory control decisions affect operations performance. Our findings show that production line and continuous flow plants use more of a level production strategy, and carry less raw material and work-in-process inventory. The performance drivers for these plants, through which the operations function excels, are effective utilization of equipment, reduced finished goods inventory, and reduced setup down time. To gain forward demand visibility and batching economies, job and batch shops rely much more on backlogs in their planning process. These plants use more of a production chase strategy and position inventory lower in the bills of materials. Four performance drivers for top-performing job and batch shops are to find ways that better anticipate customers' orders, have a more responsive chase strategy, carry less raw material or purchased inventory, and shorten production planning horizon, partly through less reliance on backlogs. It is intriguing that top-performing plants not only do the expected things, given their choice of process, but also excel in selected dimensions—some of which fit the profile normally associated with a different process choice. To monitor and continuously improve operations, evaluation ‘scorecards’ should pay particular attention to performance drivers, which change depending on the plant's process choice.
Keywords:Aggregate planning  Empirical research  Process design  Inventory control  Operations strategy  Scheduling
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