1. CHAPTER 12 FORECASTING

2. THE CONCEPTS A prediction of future events used for planning purpose Supply chain success, resources planning, scheduling, capacity planning, reducing customer response time and cutting inventories Based on mathematical model using historical data, qualitative method of managerial experiences and combination of both

3. DEMAND CHARACTERISTICS Patterns of demand : horizontal, trend, seasonal, cyclical, random External factors : interest rate, government regulations, turning point indicators, consumers’ behaviors Internal factors : internal decisions about design, price, marketing strategy, incentives, expansion, etc

4. DESIGNING THE FORECASTING SYSTEM What to forecast ? Total demand for groups or clusters and individual product or service forecast : level of aggregation, unit of measurement What type of forecasting technique to use for different characteristics of demand needs to consider of trading off accuracy and cost. Qualitative and Quantitative Methods or combination of both.

5. QUALITATIVE METHOD Judgment Method lack of historical data, new product, technology is changing, relying on experiences and managerial judgment sales force estimates, executive opinion, market research, delphi method

6. CAUSAL METHODS : LINEAR REGRESSION Available historical data The relationship between factors to be forecasted and other external & internal factors can be identified Dependent Variable to forecast is related to one or more Independent Variable(s) in linear equation : Y=a+bX The objective : to find value of a and b that minimize the sum of the squared deviations of the actual data

7. CAUSAL METHODS : TIME SERIES Naïve Forecast : forecast for the next period = current demand Simple Moving Average : horizontal & random pattern, no trend, seasonal and cyclical patterns. How many period to include ? More n is for stable demand series Weighted Moving Average Exponential Smoothing Trend-adjusted Exponential Smoothing Seasonal Patterns

8. FORECAST ERROR Bias and random error CFE is useful in assessing bias in a forecast and it tends to be 0 when correct forecasting system is being used Small MSE,  and MAD is preferable for they indicate the forecast is close to the actual demand Tracking signal is a measure that indicates whether a method of forecasting is accurately predicting actual changes in demand

9. CRITERIA FOR SELECTING TIME SERIES METHOD Minimizing bias Minimizing MAD or MSE Meeting managerial expectations of changes in the components of demand Minimizing the forecast error last period