Course schedule
Chapter 2: Inventory management &
risk pooling
1 Why is inventory required?
− Uncertainty in customer demand
• Short life cycle of an increasing number of products => historical data of demand
is not available
• The presence of many competing products => it is easy to forecast demand
across product groups than all product competing in the same market
− A significant uncertainty in the quantity and quality of the supply
− Lead time
• Hold inventory due to manufacturing and delivery lead times
− Economies of scale in transportation and manufacturing
• Incentives for larger shipment
, 2 Economic Lot Size Model
− Constant and deterministic demand, infinte planning horizon
− Goal: minimize annual purchasing and carrying costs
− Two important insights:
• Increases the order quantity Q, inventory holding costs per unit of time increase
while setup costs per unit of time decrease
• Total inventory cost is insensitive to order quantities; that is, changes in order
quantities have a relatively small impact on annual setup costs and inventory
holding costs
3 The effect of demand uncertainty
− The forecast is always wrong
• It is difficult to match supply and demand
• Estimate forecast accuracy (proxy for demand uncertainty)
− The longer the forecast horizon, the worse the forecast
• It is even more difficult if one needs to predict customer demand for a long period of
time or much ahead of the selling season
− Aggregate forecasts are more accurate
• More difficult to predict customer demand for individual SKUs
• Much easier to predict demand across all SKUs within one product family
4 Single period model
− One ordering opportunity only before demand occurs
− Using historical data
• identify a variety of demand scenarios
• determine probability each of these scenarios will occur
Chapter 2: Inventory management &
risk pooling
1 Why is inventory required?
− Uncertainty in customer demand
• Short life cycle of an increasing number of products => historical data of demand
is not available
• The presence of many competing products => it is easy to forecast demand
across product groups than all product competing in the same market
− A significant uncertainty in the quantity and quality of the supply
− Lead time
• Hold inventory due to manufacturing and delivery lead times
− Economies of scale in transportation and manufacturing
• Incentives for larger shipment
, 2 Economic Lot Size Model
− Constant and deterministic demand, infinte planning horizon
− Goal: minimize annual purchasing and carrying costs
− Two important insights:
• Increases the order quantity Q, inventory holding costs per unit of time increase
while setup costs per unit of time decrease
• Total inventory cost is insensitive to order quantities; that is, changes in order
quantities have a relatively small impact on annual setup costs and inventory
holding costs
3 The effect of demand uncertainty
− The forecast is always wrong
• It is difficult to match supply and demand
• Estimate forecast accuracy (proxy for demand uncertainty)
− The longer the forecast horizon, the worse the forecast
• It is even more difficult if one needs to predict customer demand for a long period of
time or much ahead of the selling season
− Aggregate forecasts are more accurate
• More difficult to predict customer demand for individual SKUs
• Much easier to predict demand across all SKUs within one product family
4 Single period model
− One ordering opportunity only before demand occurs
− Using historical data
• identify a variety of demand scenarios
• determine probability each of these scenarios will occur
