Logistics Management LSM 730 Lecture 21 Dr Khurrum

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Logistics Management LSM 730 Lecture 21 Dr. Khurrum S. Mughal 1 -1

Logistics Management LSM 730 Lecture 21 Dr. Khurrum S. Mughal 1 -1

What’s Forecasted in the Supply Chain? • Spatial Vs Temporal Demand • Lumpy Vs

What’s Forecasted in the Supply Chain? • Spatial Vs Temporal Demand • Lumpy Vs Regular Demand • Derived Vs. Independent Demand CR (2004) Prentice Hall, Inc. 8 -2

Some Forecasting Method Choices • Qualitative üSurveys üExpert systems or rule-based • Historical projection

Some Forecasting Method Choices • Qualitative üSurveys üExpert systems or rule-based • Historical projection üExponential smoothing • Causal or associative üRegression analysis • Collaborative CR (2004) Prentice Hall, Inc. 8 -3

Demand Behavior • Trend – a gradual, long-term up or down movement of demand

Demand Behavior • Trend – a gradual, long-term up or down movement of demand • Random variations – movements in demand that do not follow a pattern • Cycle – an up-and-down repetitive movement in demand • Seasonal pattern – an up-and-down repetitive movement in demand occurring periodically Copyright 2011 John Wiley & Sons, Inc. 12 -4

Typical Time Series Patterns: Random CR (2004) Prentice Hall, Inc. 8 -5

Typical Time Series Patterns: Random CR (2004) Prentice Hall, Inc. 8 -5

Typical Time Series Patterns: Random with Trend 250 Sales 200 150 100 Actual sales

Typical Time Series Patterns: Random with Trend 250 Sales 200 150 100 Actual sales Average sales 50 0 0 5 10 15 20 25 Time CR (2004) Prentice Hall, Inc. 8 -6

Typical Time Series Patterns: Random with Trend & Seasonal CR (2004) Prentice Hall, Inc.

Typical Time Series Patterns: Random with Trend & Seasonal CR (2004) Prentice Hall, Inc. 8 -7

Sales Typical Time Series Patterns: Lumpy Time CR (2004) Prentice Hall, Inc. 8 -8

Sales Typical Time Series Patterns: Lumpy Time CR (2004) Prentice Hall, Inc. 8 -8

Forecasting Process 1. Identify the purpose of forecast 2. Collect historical data 3. Plot

Forecasting Process 1. Identify the purpose of forecast 2. Collect historical data 3. Plot data and identify patterns 6. Check forecast accuracy with one or more measures 5. Develop/compute forecast for period of historical data 4. Select a forecast model that seems appropriate for data 7. Is accuracy of forecast acceptable? No 8 b. Select new forecast model or adjust parameters of existing model Yes 8 a. Forecast over planning horizon 9. Adjust forecast based on additional qualitative information and insight 10. Monitor results and measure forecast accuracy 12 -9

Qualitative Methods • Management, marketing, purchasing, and engineering are sources for internal qualitative forecasts

Qualitative Methods • Management, marketing, purchasing, and engineering are sources for internal qualitative forecasts • Delphi method – involves soliciting forecasts about technological advances from experts 12 -10

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