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Chapter 3

Chapter 3. Forecasting. FORECAST: A statement about the future Used to help managers Plan the system Plan the use of the system. Forecast Uses. Plan the system Generally involves long-range plans related to: Types of products and services to offer Facility and equipment levels

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Chapter 3

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  1. Chapter 3 Forecasting

  2. FORECAST: • A statement about the future • Used to help managers • Plan the system • Plan the use of the system

  3. Forecast Uses Plan the system Generally involves long-range plans related to: Types of products and services to offer Facility and equipment levels Facility location Plan the use of the system Generally involves short- and medium-range plans related to: Inventory management Workforce levels Purchasing Budgeting

  4. Common Features • Assumes causal systempast ==> future • Forecasts rarely perfect because of randomness • Forecasts more accurate forgroups vs. individuals • Forecast accuracy decreases as time horizon increases I see that you willget an A this quarter.

  5. Timely Accurate Reliable Easy to use Written Meaningful Elements of a Good Forecast Cost effective

  6. “The forecast” Step 6 Monitor the forecast Step 5 Makethe forecast Step 4 Gather and analyzedata Step 3 Select a forecastingtechnique Step 2 Establish atimehorizon Step 1 Determinepurposeof forecast Steps in the Forecasting Process

  7. Types of Forecasts • Judgmental - uses subjective inputs (qualitative) • Time series - uses historical data assuming the future will be like the past (quantitative) • Associative models - uses explanatory variables to predict the future

  8. Judgmental Forecasts(Qualitative) • Consumer surveys • Delphi method • Executive opinions • Opinions of managers and staff • Sales force.

  9. Time Series Forecasts(Quantitative) • Trend - long-term movement in data • Seasonality - short-term regular variations in data • Irregular variations - caused by unusual circumstances • Random variations - caused by chance • CYCLE- wave like variations lasting more than one year

  10. Irregularvariation Trend Cycles 90 89 88 Seasonal variations Forecast Variations Figure 3-1 cycle

  11. The Forecast of Forecasts • Naïve • Simple Moving Average • Weighted Moving Average • Exponential Smoothing • ES with Trend and Seasonality

  12. Naïve Forecast • Simple to use • Virtually no cost • Data analysis is nonexistent • Easily understandable • Cannot provide high accuracy

  13. NAÏVE METHOD • No smoothing of data Now why would you use this method?

  14. Techniques for Averaging • Moving average • Weighted moving average • Exponential smoothing

  15. Simple Moving Average • Smoothes out randomness by averaging positive and negative random elements over several periods • n - number of periods (this example uses 4)

  16. Points to Know on Moving Averages • Pro: Easy to compute and understand • Con: All data points were created equal…. …. Weighted Moving Average

  17. 0.6 0.3 0.1 Weighted Moving Average • Similar to a moving average methods except that it assigns more weight to the most recent values in a time series. • n -- number of periods ai – weight applied to period t-i+1

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