Managing Flow Variability: Safety Inventory

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Managing Flow Variability: Safety Inventory

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Presentation transcript:

Managing Flow Variability: Safety Inventory Forecasts Depend on: (a) Historical Data and (b) Market Intelligence. Demand Forecasts and Forecast Errors Safety Inventory and Service Level Optimal Service Level – The Newsvendor Problem Lead Time Demand Variability Pooling Efficiency through Aggregation Shortening the Forecast Horizon Levers for Reducing Safety Inventory ........................................................................................................................................................................................................................................ ........................................................................................................................................................................................................................................ ........................................................................................................................................................................................................................................

Four Characteristics of Forecasts Forecasts are usually (always) inaccurate (wrong). Because of random noise. Forecasts should be accompanied by a measure of forecast error. A measure of forecast error (standard deviation) quantifies the manager’s degree of confidence in the forecast. Aggregate forecasts are more accurate than individual forecasts. Aggregate forecasts reduce the amount of variability – relative to the aggregate mean demand. StdDev of sum of two variables is less than sum of StdDev of the two variables. Long-range forecasts are less accurate than short-range forecasts. Forecasts further into the future tends to be less accurate than those of more imminent events. As time passes, we get better information, and make better prediction.

Demand During Lead Time is Variable N(μ,σ) Demand of sand during lead time has an average of 50 tons. Standard deviation of demand during lead time is 5 tons Assuming that the management is willing to accept a risk no more that 5%.

Forecasts should be accompanied by a measure of forecast error Forecast and a Measure of Forecast Error Forecasts should be accompanied by a measure of forecast error

Demand During Lead Time Inventory Demand during LT Lead Time Time

ROP when Demand During Lead Time is Fixed LT

Demand During Lead Time is Variable LT

Demand During Lead Time is Variable Inventory Time

Safety Stock Quantity A large demand during lead time Average demand ROP Safety stock Safety stock reduces risk of stockout during lead time LT Time

Safety Stock Quantity ROP LT Time

Re-Order Point: ROP Demand during lead time has Normal distribution. If we order when the inventory on hand is equal to the average demand during the lead time; then there is 50% chance that the demand during lead time is less than our inventory. However, there is also 50% chance that the demand during lead time is greater than our inventory, and we will be out of stock for a while. We usually do not like 50% probability of stock out We can accept some risk of being out of stock, but we usually like a risk of less than 50%.

Safety Stock and ROP Service level Risk of a stockout Probability of no stockout ROP Quantity Average demand Safety stock z-scale z Each Normal variable x is associated with a standard Normal Variable z x is Normal (Average x , Standard Deviation x)  z is Normal (0,1)

z Values Service level Risk of a stockout Probability of no stockout SL z value 0.9 1.28 0.95 1.65 0.99 2.33 ROP Average demand Quantity Safety stock z z-scale There is a table for z which tells us Given any probability of not exceeding z. What is the value of z Given any value for z. What is the probability of not exceeding z