Business Forecasting - Activity

This activity is designed to be used in the classroom or as a homework task to support the teaching and learning of Business Forecasting.

Business Forecasting - Activity

This Activity aims to help you practice some of the main techniques that you will be expected to know and demonstrate in analysing and assessing business decision-making.

You will be given a series of tasks to complete, with a step-by-step guide on how to master the techniques. An accompanying Excel spreadsheet of the data is also included to assist you in the tasks. Of course, you can carry out the tasks manually if you wish.

Task 1

  • Construct graphs based on the data below. Extrapolate the data to predict the company's sales for 2006.

Company 1

Year Sales (£000s)
2001 3000
2002 3600
2003 4200
2004 4800
2005 5400
2006  

Use the data in an Excel spreadsheet...

Company 2

Year Sales (£000s)
2001 2000
2002 2200
2003 3000
2004 4600
2005 7200
2006  

Use the data in an Excel spreadsheet...

Task 2

  • Explain the reasoning for your prediction.
  • Which of the two companies was easier to predict and why?
  • What other information would be useful in helping you to comment on the validity and reliability of the prediction?
  • Assume that your prediction could be inaccurate by + or - £50,000. How might you show this on your graph?

Calculating Moving Averages

The aim is to use the data below to predict the level of sales for 2006. Follow the tasks below to make your prediction.

Year Actual Sales (£m)
1993 150
1994 153
1995 157
1996 151
1997 149
1998 156
1999 163
2000 159
2001 154
2002 153
2003 159
2004 165
2005 162

Use the data in an Excel spreadsheet...

Task 3

  • Plot the data in the table into a graph. (You can use the spreadsheet to facilitate this process).
  • What, if any, trends does the data exhibit?
  • What explanation could you offer for the trend/s you may have identified? (Hint: think about the business cycle - see the glossary for a definition of this term)

Task 4

  • Calculate the 5-point moving total. To do this, add the first 5 years data and then move forward by one year adding the next 5 points and so on.

Year Actual Sales (£m) 5-Point Moving Total
1993 150  
1994 153  
1995 157  
1996 151  
1997 149  
1998 156  
1999 163  
2000 159  
2001 154  
2002 153  
2003 159  
2004 165  
2005 162  

Use the data in an Excel spreadsheet...

Task 5

  • Calculate the 5-point moving average by dividing the 5-point moving total by 5. The result should be placed in the middle box of the series of numbers (1995 for the first series).
  • If you were to use a 3-point moving average, you would do the same process but use only 3 years. The aim of this technique is to smooth out cyclical variations in data.
  • What factors might determine the number of 'points' you settle on?

Year Actual Sales (£m) 5-Point Moving Average
1993 150  
1994 153  
1995 157  
1996 151  
1997 149  
1998 156  
1999 163  
2000 159  
2001 154  
2002 153  
2003 159  
2004 165  
2005 162  

Use the data in an Excel spreadsheet...

Task 6

  • Plot the 5-point moving average data on the graph you have drawn of total sales against time.

We are now in a position to be able to calculate the cyclical variation in the data. The cyclical variation = the actual data minus the trend data. The 5-point moving average gives us the trend data for the set of sales figures we have been given.

Year Actual Sales (£m) 5-Point Moving Average Point in the Cycle
1993 150   1
1994 153   2
1995 157   3
1996 151   4
1997 149   5
1998 156   1
1999 163   2
2000 159   3
2001 154   4
2002 153   5
2003 159   1
2004 165   2
2005 162   3

Use the data in an Excel spreadsheet...

The table above has the point in the cycle added in. This is simply done by starting with the first year and assigning that as point 1 and then counting down. This allows us to identify which year in the cycle our prediction year is. In our example, 2006 is point 4 in the cycle.

Task 7

  • Calculate the average cyclical variation for point 4 in the cycle. This is done by finding the sum of the cyclical variations (a test of your knowledge of adding positive and negative numbers!) and dividing by the number of points identified (in this case it is 2 but could be more depending on the amount of data used and the number of points, chosen i.e. whether it is 3 point, 4 point and so on).

We are now in a position to make a prediction on the sales forecast for 2006. The last moving average data we have is for 2003. To make an assumption about what the moving average would be for 2004 and 2005, we can expect the data in this example to increase by using the following method.

Task 8

  • Calculate the interval between the years 1995 and 2003. Subtract the moving average figure for 2003 from that of 1995 and divide by the number of intervals. This figure can be added onto the moving average to give you the likely trend for 2004 and 2005.

Now the final step.

Task 9

  • Take the result from task 5 and do a + and - calculation to the 2005 figure you have just calculated. This will produce a range within which the forecast might be reasonably being expected to sit.

Task 10

  • Evaluate the reliability of the forecast you have made. Consider the factors that might influence the actual outcome and discuss what a business might do to take such factors into consideration in their planning.

    (Hint: think of the factors outside a firm's control - the nature of the business, the lead time in production, the type of productive process and how the business might plan to cope with shortages/surpluses. You have free reign here to base your evaluation around different types of business, using ones you are familiar with is always advisable).

Extension Work

Look at the following Web sites:

Offer a critical analysis of the value of using non-traditional methods of business forecasting.

The Time-Critical Decision Makingfor Business Administration site also has some useful information and goes into more detail on forecasting methods. (http://home.ubalt.edu/ntsbarsh/stat-data/Forecast.htm)

Related lesson plan: 
Related mind map: