Intended learning outcomes: Propose a forecasting technique for different products to apply to forecast future demand.
Figure 10.8.1.1 shows historical demand curves for four different products. What forecasting technique for each product do you propose to apply to forecast future demand?
Fig. 10.8.1.1 Historical demand curves for four products.
Solution:
- Product 1: demand with linear trend —> linear regression
- Product2: constant demand without trend —> moving average forecasting or first-order exponential smoothing
- Product 3: seasonal fluctuations with trend —> linear regression or second-order exponential smoothing with seasonality
- Product 4: constant demand with seasonal fluctuation —> moving average forecasting, or first-order exponential smoothing, with seasonality
Course section 10.8: Subsections and their intended learning outcomes
10.8.1 Exercise: Choice of Appropriate Forecasting Techniques
Intended learning outcomes: Propose a forecasting technique for different products to apply to forecast future demand.
10.8.2 Exercise: Moving Average Forecasting Technique
Intended learning outcomes: Calculate forecasts with moving average forecasting technique.
10.8.3 Exercise: First-Order Exponential Smoothing
Intended learning outcomes: Calculate forecasts using first-order exponential smoothing technique.
10.8.4 Scenario: Moving Average Forecast versus First-Order Exponential Smoothing Forecast
Intended learning outcomes: Differentiate between moving average forecast and first-order exponential smoothing using different numbers of observed values or smoothing constants α.
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.
