Sales Forecast Demo

Monthly U.S. Product Supplied of Residual Fuel Oil (thousands of barrels) from 2005 through 2011 are as follows:

200923,57212,53818,32220,30313,43816,969 9,87614,63710,19415,33513,34018,034
201119,30117,55516,94417,99414,82314,131 9,811 9,87814,46012,46111,83916,088

From looking at this data, can you see any kind of annual pattern?  That is, is supplied fuel oil cyclical across time - higher at certain parts of the year, lower at other parts?  Regardless of patterns, is there any general trend going up, down, or flat? 

Blindly attempting a quantitative forecast without having a feel for these sorts of issues is pointless.  You should look at a visual plot of historical sales, and then you need to assess two factors: patterns and trends.  For any patterns and trends that you see, what time period is relevant in using these to make a forecast?  At what point does older data lose its value in assisting you to make a forecast? Importantly, what factors in the external environment have a bearing on a forecast?

Click on the following links to see interactive spreadsheets and plots:

[These will only work with MS Excel.  I believe that they won't work in versions older than 2003.  Use the school computer lab to view them if you experience any troubles.]

Each of these examples smoothes the data, useful in helping to find a trend line and to find a pattern (if there is any) when the data is "noisy". 

On each spreadsheet, you will see a slider at the top of the sheet.  Move it to change the value of n on a moving average forecast and to change the value of alpha on an exponential smoothing forecast.  You can click on the slider button or can click on the arrows on each side of the slider.  You can also click on the cell that contains the smoothing value and type a new value.

If you experiment with changes that destroy how the spreadsheet functions, just click on one of the links above to open a fresh one.