Modeling Inventory Systems with @RISK: Lost Sales and Back Orders

Whether of raw material, intermediate or final product, human or financial resource, or even resources such as hotel rooms and seats on a plane, inventory is a fact of life for the service and manufacturing industries. Most introductory courses in operations research or management science present analytical models (e.g., EOQ) to assist with the related inventory decisions of how much and how often to order in a manner that minimizes total inventory-related costs. If the assumptions behind these models hold they can prove very useful. When the assumptions don’t hold however, simulation is appropriate. Recent experience with supply chain disruptions and customer demand during turbulent economic times should have woken all who work with inventory to the difficulties presented by uncertain demand and order lead time, making most analytical inventory system models, where both demand and lead time are assumed to be constant, inappropriate. Following a brief discussion of several basic inventory system analytical models and their associated assumptions, this webinar will present @RISK models for simulating inventory systems that handle lost sales and back orders while treating demand and lead time as uncertainties. Several additional embellishments will then be discussed to account for situations where further analytical model assumptions don’t hold.