Abstract
This paper proceeds from the premise, derived from the literature, that uncertainty is predominantly a demand-side and/or lead time problem in healthcare inventory management. It conceptually explores how organizational exposure to the risks of uncertain demand and lead time may be hedged, especially considering that forecasting stock-outs and overstocks can be quite challenging in healthcare. We examine these challenges probabilistically. Theoretically, by inquiring into the underlying premises of aggregate demand, order quantity, and reorder point. And practically, regarding the implications of hedging inventory risks under conditions of uncertainty. Three measures that can efficiently hedge against demand and lead time variabilities under a continuous review inventory system are identified and analyzed: safety stock with service level, stock-out and overstock costing, and low-cost reorder point. Mathematical modeling, simulation, and optimization enhance integrated financial and operational problem-solving. With appropriate technology and software, demand forecasting and risk-hedging offer real-time visibility into stock levels. These should help healthcare organizations make critical, data-driven decisions and contain costly understocking and unnecessary overstocking when demand and lead time are stochastic and discreet.
Published Version
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