2 FORECAST:A statement about the future value of a variable of interest such as demand.Forecasts affect decisions and activities throughout an organizationAccounting, financeHuman resourcesMarketingMISOperationsProduct / service design
3 Uses of Forecasts Accounting Cost/profit estimates Finance Cash flow and fundingHuman ResourcesHiring/recruiting/trainingMarketingPricing, promotion, strategyMISIT/IS systems, servicesOperationsSchedules, MRP, workloadsProduct/service designNew products and services
4 Assumes causal system past ==> future Forecasts rarely perfect because of randomnessForecasts more accurate for groups vs. individualsForecast accuracy decreases as time horizon increasesI see that you will get an A this semester.
5 Elements of a Good Forecast TimelyAccurateReliableMeaningfulWrittenEasy to use
6 Steps in the Forecasting Process Step 1 Determine purpose of forecastStep 2 Establish a time horizonStep 3 Select a forecasting techniqueStep 4 Gather and analyze dataStep 5 Prepare the forecastStep 6 Monitor the forecast“The forecast”
7 Types of Forecasts Judgmental - uses subjective inputs Time series - uses historical data assuming the future will be like the pastAssociative models - uses explanatory variables to predict the future
8 Judgmental Forecasts Executive opinions Sales force opinions Consumer surveysOutside opinionDelphi methodOpinions of managers and staffAchieves a consensus forecast
9 Time Series Forecasts Trend - long-term movement in data Seasonality - short-term regular variations in dataCycle – wavelike variations of more than one year’s durationIrregular variations - caused by unusual circumstancesRandom variations - caused by chance
11 week.... Now, next week we should sell.... Naive ForecastsUh, give me a minute....We sold 250 wheels lastweek.... Now, next week we should sell....The forecast for any period equals the previous period’s actual value.
12 Techniques for Averaging Moving averageWeighted moving averageExponential smoothing
13 MAn = n Ai Moving Averages Moving average – A technique that averages a number of recent actual values, updated as new values become available.Weighted moving average – More recent values in a series are given more weight in computing the forecast.MAn=nAii = 1
15 Exponential Smoothing Ft = Ft-1 + (At-1 - Ft-1)Premise--The most recent observations might have the highest predictive value.Therefore, we should give more weight to the more recent time periods when forecasting.
16 Exponential Smoothing Ft = Ft-1 + (At-1 - Ft-1)Weighted averaging method based on previous forecast plus a percentage of the forecast errorA-F is the error term, is the % feedback
18 Picking a Smoothing Constant .1.4Actual
19 Associative Forecasting Predictor variables - used to predict values of variable interestRegression - technique for fitting a line to a set of pointsLeast squares line - minimizes sum of squared deviations around the line
20 Linear Model Seems Reasonable Computed relationshipA straight line is fitted to a set of sample points.
21 Forecast AccuracyError - difference between actual value and predicted valueMean Absolute Deviation (MAD)Average absolute errorMean Squared Error (MSE)Average of squared errorMean Absolute Percent Error (MAPE)Average absolute percent error
22 MAD, MSE, and MAPE Actual forecast MAD = n MSE = Actual forecast) -12n(MAPE=Actualforecastn/ Actual*100)(
24 Choosing a Forecasting Technique No single technique works in every situationTwo most important factorsCostAccuracyOther factors include the availability of:Historical dataComputersTime needed to gather and analyze the dataForecast horizon