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3-1 McGraw-Hill/Irwin Operations Management, Seventh Edition, by William J. Stevenson Copyright © 2002 by The McGraw-Hill Companies, Inc. All rights reserved.

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Presentation on theme: "3-1 McGraw-Hill/Irwin Operations Management, Seventh Edition, by William J. Stevenson Copyright © 2002 by The McGraw-Hill Companies, Inc. All rights reserved."— Presentation transcript:

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2 3-1 McGraw-Hill/Irwin Operations Management, Seventh Edition, by William J. Stevenson Copyright © 2002 by The McGraw-Hill Companies, Inc. All rights reserved. Forecasting Chapter 3 Forecasting

3 3-2 McGraw-Hill/Irwin Operations Management, Seventh Edition, by William J. Stevenson Copyright © 2002 by The McGraw-Hill Companies, Inc. All rights reserved. Forecasting FORECAST: A statement about the future Used to help managers –Plan the system –Plan the use of the system

4 3-3 McGraw-Hill/Irwin Operations Management, Seventh Edition, by William J. Stevenson Copyright © 2002 by The McGraw-Hill Companies, Inc. All rights reserved. Forecasting 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

5 3-4 McGraw-Hill/Irwin Operations Management, Seventh Edition, by William J. Stevenson Copyright © 2002 by The McGraw-Hill Companies, Inc. All rights reserved. Forecasting Assumes causal system past ==> future Forecasts rarely perfect because of randomness Forecasts more accurate for groups vs. individuals Forecast accuracy decreases as time horizon increases I see that you will get an A this quarter. Common Features

6 3-5 McGraw-Hill/Irwin Operations Management, Seventh Edition, by William J. Stevenson Copyright © 2002 by The McGraw-Hill Companies, Inc. All rights reserved. Forecasting Elements of a Good Forecast Timely Accurate Reliable Meaningful Written Easy to use Cost effective

7 3-6 McGraw-Hill/Irwin Operations Management, Seventh Edition, by William J. Stevenson Copyright © 2002 by The McGraw-Hill Companies, Inc. All rights reserved. Forecasting Steps in the Forecasting Process Step 1 Determine purpose of forecast Step 2 Establish a time horizon Step 3 Select a forecasting technique Step 4 Gather and analyze data Step 5 Make the forecast Step 6 Monitor the forecast “The forecast”

8 3-7 McGraw-Hill/Irwin Operations Management, Seventh Edition, by William J. Stevenson Copyright © 2002 by The McGraw-Hill Companies, Inc. All rights reserved. Forecasting 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

9 3-8 McGraw-Hill/Irwin Operations Management, Seventh Edition, by William J. Stevenson Copyright © 2002 by The McGraw-Hill Companies, Inc. All rights reserved. Forecasting Judgmental Forecasts (Qualitative) C onsumer surveys D elphi method E xecutive opinions –Opinions of managers and staff S ales force.

10 3-9 McGraw-Hill/Irwin Operations Management, Seventh Edition, by William J. Stevenson Copyright © 2002 by The McGraw-Hill Companies, Inc. All rights reserved. Forecasting 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

11 3-10 McGraw-Hill/Irwin Operations Management, Seventh Edition, by William J. Stevenson Copyright © 2002 by The McGraw-Hill Companies, Inc. All rights reserved. Forecasting Forecast Variations Trend Irregular variation Cycles Seasonal variations 90 89 88 Figure 3-1 cycle

12 3-11 McGraw-Hill/Irwin Operations Management, Seventh Edition, by William J. Stevenson Copyright © 2002 by The McGraw-Hill Companies, Inc. All rights reserved. Forecasting The Forecast of Forecasts Naïve Simple Moving Average Weighted Moving Average Exponential Smoothing ES with Trend and Seasonality

13 3-12 McGraw-Hill/Irwin Operations Management, Seventh Edition, by William J. Stevenson Copyright © 2002 by The McGraw-Hill Companies, Inc. All rights reserved. Forecasting Simple to use Virtually no cost Data analysis is nonexistent Easily understandable Cannot provide high accuracy Naïve Forecast

14 3-13 McGraw-Hill/Irwin Operations Management, Seventh Edition, by William J. Stevenson Copyright © 2002 by The McGraw-Hill Companies, Inc. All rights reserved. Forecasting NAÏVE METHOD No smoothing of data

15 3-14 McGraw-Hill/Irwin Operations Management, Seventh Edition, by William J. Stevenson Copyright © 2002 by The McGraw-Hill Companies, Inc. All rights reserved. Forecasting Techniques for Averaging Moving average Weighted moving average Exponential smoothing

16 3-15 McGraw-Hill/Irwin Operations Management, Seventh Edition, by William J. Stevenson Copyright © 2002 by The McGraw-Hill Companies, Inc. All rights reserved. Forecasting Simple Moving Average Smoothes out randomness by averaging positive and negative random elements over several periods n - number of periods (this example uses 4)

17 3-16 McGraw-Hill/Irwin Operations Management, Seventh Edition, by William J. Stevenson Copyright © 2002 by The McGraw-Hill Companies, Inc. All rights reserved. Forecasting Points to Know on Moving Averages Pro: Easy to compute and understand Con: All data points were created equal…. …. Weighted Moving Average

18 3-17 McGraw-Hill/Irwin Operations Management, Seventh Edition, by William J. Stevenson Copyright © 2002 by The McGraw-Hill Companies, Inc. All rights reserved. Forecasting 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  i – weight applied to period t-i+1 0.60.30.1


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