Ch 4 Forecasting 2009

Ch 4 Forecasting 2009 - Chapter 4 Forecasting A....

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Chapter 4 Forecasting A. Understanding Forecasting 1. Define Forecasting It’s a process of predicting a event. It’s an underlying basis of all business decision. 2. Types of Forecasts by Time Horizon 1. Short-range forecast Usually < months Job scheduling, worker assignments, purchasing (more accurate than long-range forecast) 2. Medium-range forecast months to years 3. Long-range forecast Usually > Years 3. Realities of Forecasting 1. Forecasts are ____________________ perfect 2. Most forecasting methods assume there is some underlying in the system 3. Both product family and aggregated product forecasts are _________________ accurate than individual product forecasts 4. Forecasting Approaches 1
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Approach: subjective - Used when situation is & little data exist (e.g. new products & technology) - Involve intuition and experience (e.g. sales on internet) Strengths: Incorporates insider’s information Particularly useful when the future is expected to be very from the past Weaknesses: Forecast bias can reduce the accuracy of the forecast Approach: numeric (objective) - Used when situation is & historical data exist (e.g. existing products & current technology) - Involve mathematical techniques (e.g. predicting sales of color TV) Strengths: Consistent and Can consider a lot of data at once Weaknesses: Necessary data isn’t always available Forecast quality is dependent upon Data 2
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3. 3. Qualitative Forecasting Methods o opinion Pool opinions of high-level executives, sometimes augmented by statistical models o composite estimates from individual salespersons are reviewed for reasonableness, then aggregated o method: Iterative group process, continues until consensus is reached 3 types of participants: - Decision makers Evaluate responses and make decisions - Staff: Administering survey - Respondents: People who can make valuable judgments Involves anonymity of responses conducted asynchronously by paper Use questionnaire queried iterative; repeat 2, 3 times o survey Ask the customer 4. Quantitative Forecasting Approaches Time Series Models 1. Naïve Approach: assume demand in next period is the same as this period. 2. Moving Average (MA) 3. Weighted Moving Average (WMA) 3. Exponential Smoothing (ES) 4. Trend Projection using Linear Regression 3
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B. What is a Time Series? A time series is a set of numerical data obtained by observing variable at regular time periods Forecast based only on past values 0. Assumes that factors influencing past, present & future will continue Example Year: 2001 2002 2003 2004 2005 Sales: 78.7 63.5 89.7 93.2 92.1 4. The four components of a time Series Cyclical Component Upward or downward swings May vary in length Usually lasts 2 - 10 years Sales
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Ch 4 Forecasting 2009 - Chapter 4 Forecasting A....

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