*CHAPTER 2: STRATEGY &SALES PROGRAM PLANNING

*SALES FORECASTQUALITATIVE SALES FORECASTING

QUANTITATIVE SALES FORECASTING

*SALES FORECASTQUALITATIVE SALES FORECASTING

1- Sales Force Composite2- Jury of Executive Opinion3- Leading Indicator

*SALES FORECASTQUANTITATIVE SALES FORECASTING

Seasonal AdjustmentsNaive ForecastsMAPETrend ProjectionsMoving AveragesExponential SmoothingTime Series RegressionMultiple RegressionTurning Points

*EXAMPLE

*Using the following sales revenue data with actual revenue year 2008 through 2011, forecast sales revenue of the year 2012?

Quarter2008 (thousand littres)2009 (thousand littres)2010 (thousand littres)2011 (thousand littres)2012(thousand littres)1244326369487?2270343360502?3278334354459?4347360447529?

*Naive Forecasts

1977

1977

Quarter2008 (thousand littres)2009 (thousand littres)2010 (thousand littres)2011 (thousand littres)2012(thousand littres)1244326369487-2270343360502-3278334354459-4347360447529-

*MAPE = 1977+ 29%(1977) = 255015301977=>+29,2%

Quarter2008 (thousand littres)2009 (thousand littres)2010 (thousand littres)2011 (thousand littres)2012(thousand littres)1244326369487-2270343360502-3278334354459-4347360447529-

*Moving Averages19771530136311391753

Quarter2008 (thousand littres)2009 (thousand littres)2010 (thousand littres)2011 (thousand littres)2012(thousand littres)1244326369487-2270343360502-3278334354459-4347360447529-

*Seasonal AdjustmentsAverage revenue of quarter =6009/16=375,5Sales forecasting of 2012: 2550Average revenue of quarter: 637,5

Quater2008 2009 2010 2011 AR of quarterSeasonal Index2012

1244326369487356,50,945992270343360502368,70,986253278334354459345,20,915804347360447529420,71.12714

*Trend ProjectionsUse qualitative sales forecasting

*Exponential Smoothing

*1977153013631139= 0.3

Quarter2008 (thousand littres)2009 (thousand littres)2010 (thousand littres)2011 (thousand littres)2012(thousand littres)1244326369487-2270343360502-3278334354459-4347360447529-

*1977153013631139=0.3= 0.3x1977+0.7X1530) = 1664

Quarter2008 (thousand littres)2009 (thousand littres)2010 (thousand littres)2011 (thousand littres)2012(thousand littres)1244326369487-2270343360502-3278334354459-4347360447529-

197715301100*Time Series Regression2256Year 2011Y = 279.3X + 859.67Year 2012Forecast

*

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