Intended learning outcomes: Produce an overview of forecasting techniques. Explain history-oriented techniques for constant demand in detail. Identify history-oriented techniques with trend-shaped behavior. Describe three future-oriented techniques. Disclose how to use forecasts in planning.
Whenever cumulative lead time exceeds customer tolerance time, production or procurement must take place on the basis of a demand forecast. The dark background in Figure 10.0.0.1 shows this task and the planning processes that require forecasting. The figure refers to the model for business processes and tasks of planning & control in Figure 5.1.4.2.
Fig. 10.0.0.1 The darker background shows the tasks discussed in this chapter.
Sections 5.3.1 and 5.3.2 provide a good basis for the material in this chapter. We recommend that you reread Sections 5.3.1 and 5.3.2 before studying Chapters 10 to 12. The need for forecasting varies over time, depending on market and product. Examples of markets with a great need for forecasting include trade in consumer goods or provision of the components needed for a service or for investment goods. Before receiving any definite customer orders, the company must produce or procure, for example, machine parts in advance.
The following sections classify forecasting techniques and describe the procedures in principle. They describe and compare individual techniques in detail. They define the consumption distribution as an overlay of the distribution of consumption events and the distribution of the quantity consumed per event. This will allow us to derive safety demand and the limits of determining independent stochastic demand. We will also take a look at the transition from forecast values to independent demand and how this is managed. The material in this chapter is both qualitative and quantitative in nature. In many parts, it demands not only intuitive or basic knowledge, but also an understanding of at least elementary statistical methods.
Course 10: Sections and their intended learning outcomes
Course 10 – Demand Planning and Demand Forecasting
Intended learning outcomes: Produce an overview of forecasting techniques. Explain history-oriented techniques for constant demand in detail. Identify history-oriented techniques with trend-shaped behavior. Describe three future-oriented techniques. Disclose how to use forecasts in planning.
10.1 Overview of Demand Planning and Forecasting Techniques
Intended learning outcomes: Produce an overview on the problem of demand planning. Present the subdivision of forecasting techniques. Disclose principles of forecasting techniques with extrapolation of time series and the definition of variables.
10.2 Historically Oriented Techniques for Constant Demand
Intended learning outcomes: Describe the moving average forecast. Explain the first-order exponential smoothing forecast. Differentiate between the moving average forecast and the first-order exponential smoothing forecast.
10.3 Historically Oriented Techniques with Trend-Shaped Behavior
Intended learning outcomes: Explain the regression analysis forecast and the second-order exponential smoothing forecast. Describe the Trigg and Leach adaptive smoothing technique. Produce an overview on seasonality.
10.4 Future-Oriented Techniques
Intended learning outcomes: Explain the trend extrapolation forecast and the Delphi method. Describe scenario forecasts.
10.5 Using Forecasts in Planning
Intended learning outcomes: Produce an overview on the choice of suitable forecasting technique. Describe consumption distributions and their limits, continuous and discontinuous demand. Explain demand forecasting of variants of a product family. Present safety demand calculation for various planning periods. Disclose the translation of forecast into quasi-deterministic demand.
10.6 Summary
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10.7 Keywords
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10.8 Scenarios and Exercises
Intended learning outcomes: Choose an appropriate forecasting technique. Calculate an example for the moving average forecasting technique and for the first-order exponential smoothing technique. Differentiate between the moving average forecast and the first-order exponential smoothing forecast.
10.9 References
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Case [Course 10]
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