Time-Series Forecast Models EXAMPLE Monthly Sales ( in units ) Jan Feb Mar Apr May Jun Jul Aug Sept Oct Nov Dec Data Point or (observation) MGMT E-5070 Data Mining and Forecast Management Wallace Garden Supply

Storage shed sales over the past year were as follows: PeriodDemandPeriodDemand January10July26 February12August30 March13September28 April16October18 May19November16 June23December14 MGMT E-5070

Wallace Garden Supply REQUIREMENTS: Predict sales for next January via : naïve 1.The naïve model. moving average 2.The 3 - month moving average model. weighted moving average 3.The 3 - month weighted moving average model with weights of 3, 2, 1 respectively. exponential smoothing 4. The exponential smoothing model with ά =.7 trend projection 5. The trend projection model. 6. Which model is the most accurate?

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Forecast Model Options

Performance Summary Forecast ModelMADBiasMSE Standard ErrorMAPE January Forecast Moving Average ( 3 - mo ) Weighted Moving Av ( 3 - mo ) Exponent Smoothing ( a =.7 ) Trend Analysis Naïve

Performance Summary Forecast ModelMADBiasMSE Standard ErrorMAPE January Forecast Moving Average ( 3 - mo ) Weighted Moving Av ( 3 - mo ) Exponent Smoothing ( a =.7 ) Trend Analysis Naïve BEST ( lowest )

Forecasting with Excel

Forecasting with Excel QM 3

Time-Series Forecast Models EXAMPLE Monthly Sales ( in units ) Jan Feb Mar Apr May Jun Jul Aug Sept Oct Nov Dec Data Point or (observation) MGMT E-5070 Data Mining and Forecast Management Wallace Garden Supply