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 FORCASTING PART TWO Chapter Three Forecasting

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 Chapter 3 Forecasting

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: A statement about the future Used to help managers –Plan the system –Plan the use of the system

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 AccountingCost/profit estimates FinanceCash flow and funding Human ResourcesHiring/recruiting/training MarketingPricing, promotion, strategy MISIT/IS systems, services OperationsSchedules, MRP, workloads Product/service designNew products and services Uses of Forecasts

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 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 semester.

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 Elements of a Good Forecast Timely Accurate Reliable Meaningful Written Easy to use

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 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 Prepare the forecast Step 6 Monitor the forecast “The forecast”

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 Types of Forecasts Judgmental - uses subjective inputs Time series - uses historical data assuming the future will be like the past Associative models - uses explanatory variables to predict the future

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 Judgmental Forecasts Executive opinions Sales force composite Consumer surveys Outside opinion Opinions of managers and staff –Delphi method

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 Time Series Forecasts Trend - long-term movement in data Seasonality - short-term regular variations in data Irregular variations - caused by unusual circumstances Random variations - caused by chance

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 Forecast Variations Trend Irregular variatio n Cycles Seasonal variations Figure 3-1

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 Can be a standard for accuracy Naïve Forecasts

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 Stable time series data –F(t) = A(t-1) Seasonal variations –F(t) = A(t-n) Data with trends –F(t) = A(t-1) + (A(t-1) – A(t-2)) Uses for Naïve Forecasts

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 Naive Forecasts Uh, give me a minute.... We sold 250 wheels last week.... Now, next week we should sell....

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 Techniques for Averaging Moving average Weighted moving average Exponential smoothing

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 Simple Moving Average Figure 3-4 MA n = n AiAi i = 1  n Actual MA3 MA5

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 Exponential Smoothing nPremise--The most recent observations might have the highest predictive value. –Therefore, we should give more weight to the more recent time periods when forecasting. F t = F t-1 +  ( A t-1 - F t-1 )

3-18 McGraw-Hill/Irwin Operations Management, Seventh Edition, by William J. Stevenson Copyright © 2002 by The McGraw-Hill Companies, Inc. All rights reserved. Forecasting Example of Exponential Smoothing

3-19 McGraw-Hill/Irwin Operations Management, Seventh Edition, by William J. Stevenson Copyright © 2002 by The McGraw-Hill Companies, Inc. All rights reserved. Forecasting Picking a Smoothing Constant .1 . 4 Actual

3-20 McGraw-Hill/Irwin Operations Management, Seventh Edition, by William J. Stevenson Copyright © 2002 by The McGraw-Hill Companies, Inc. All rights reserved. Forecasting Common Nonlinear Trends Parabolic Exponential Growth Figure 3-5

3-21 McGraw-Hill/Irwin Operations Management, Seventh Edition, by William J. Stevenson Copyright © 2002 by The McGraw-Hill Companies, Inc. All rights reserved. Forecasting Linear Trend Equation b is similar to the slope. However, since it is calculated with the variability of the data in mind, its formulation is not as straight-forward as our usual notion of slope. Y t = a + bt t Y

3-22 McGraw-Hill/Irwin Operations Management, Seventh Edition, by William J. Stevenson Copyright © 2002 by The McGraw-Hill Companies, Inc. All rights reserved. Forecasting Calculating a and b b = n(ty) - ty nt 2 - ( t) 2 a = y - bt n   

3-23 McGraw-Hill/Irwin Operations Management, Seventh Edition, by William J. Stevenson Copyright © 2002 by The McGraw-Hill Companies, Inc. All rights reserved. Forecasting Linear Trend Equation Example

3-24 McGraw-Hill/Irwin Operations Management, Seventh Edition, by William J. Stevenson Copyright © 2002 by The McGraw-Hill Companies, Inc. All rights reserved. Forecasting Linear Trend Calculation y = t a= (15) 5 = b= 5 (2499)- 15(812) 5(55)- 225 = =

3-25 McGraw-Hill/Irwin Operations Management, Seventh Edition, by William J. Stevenson Copyright © 2002 by The McGraw-Hill Companies, Inc. All rights reserved. Forecasting Associative Forecasting Predictor variables - used to predict values of variable interest Regression - technique for fitting a line to a set of points Least squares line - minimizes sum of squared deviations around the line

3-26 McGraw-Hill/Irwin Operations Management, Seventh Edition, by William J. Stevenson Copyright © 2002 by The McGraw-Hill Companies, Inc. All rights reserved. Forecasting Linear Model Seems Reasonable Computed relationship

3-27 McGraw-Hill/Irwin Operations Management, Seventh Edition, by William J. Stevenson Copyright © 2002 by The McGraw-Hill Companies, Inc. All rights reserved. Forecasting Forecast Accuracy Error - difference between actual value and predicted value Mean absolute deviation (MAD) –Average absolute error Mean squared error (MSE) –Average of squared error Tracking signal –Ratio of cumulative error and MAD

3-28 McGraw-Hill/Irwin Operations Management, Seventh Edition, by William J. Stevenson Copyright © 2002 by The McGraw-Hill Companies, Inc. All rights reserved. Forecasting MAD & MSE MAD = Actualforecast   n MSE = Actualforecast )   n (

3-29 McGraw-Hill/Irwin Operations Management, Seventh Edition, by William J. Stevenson Copyright © 2002 by The McGraw-Hill Companies, Inc. All rights reserved. Forecasting Tracking Signal Tracking signal = ( Actual - forecast ) MAD  Tracking signal = ( Actual - forecast) Actual - forecast   n

3-30 McGraw-Hill/Irwin Operations Management, Seventh Edition, by William J. Stevenson Copyright © 2002 by The McGraw-Hill Companies, Inc. All rights reserved. Forecasting Exponential Smoothing T3-2

3-31 McGraw-Hill/Irwin Operations Management, Seventh Edition, by William J. Stevenson Copyright © 2002 by The McGraw-Hill Companies, Inc. All rights reserved. Forecasting Linear Trend Equation T3-3

3-32 McGraw-Hill/Irwin Operations Management, Seventh Edition, by William J. Stevenson Copyright © 2002 by The McGraw-Hill Companies, Inc. All rights reserved. Forecasting Trend Adjusted Exponential Smoothing T3-4

3-33 McGraw-Hill/Irwin Operations Management, Seventh Edition, by William J. Stevenson Copyright © 2002 by The McGraw-Hill Companies, Inc. All rights reserved. Forecasting Simple Linear Regression T3-5