Sales forecasting
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Sales Forecasting. “All planning begins with a forecast.”. Sales Forecasting at IDES Mfg. IDES manufactures a desktop computer, the “Eman” . The computer is made at the IDES plant in Flagstaff.

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Sales forecasting

Sales Forecasting

“All planning begins with a forecast.”


Sales forecasting at ides mfg

Sales Forecasting at IDES Mfg.

  • IDES manufactures a desktop computer, the “Eman”. The computer is made at the IDES plant in Flagstaff.

  • It is the beginning of January 2002 and different groups of IDES management is engaged in planning for the next month, the next year, and the next five years.

  • Since all planning begins with a forecast, IDES needs to get busy creating forecasts.


Planning activities at ides

Planning Activities at IDES

  • IDES present computer manufacturing capacity:

    • Per Qtr. Regular Time = 312,000; O/T = 374,400

    • Per Year Regular time =1,248,000; O/T = 1,497,600

  • For the 1st quarter of 2002, IDES needs to make plans to schedule production. This requires determining the labor and materials needs to meet sales demand.

  • For the entire year 2002, IDES needs to determine if any additions to capacity will be required to meet sales demand.

  • IDES needs to know if the present Flagstaff plant will be able to produce enough “Eman” computers to meet sales demand over the next five years.


Ides historical sales data

Annual Sales

YearUnit Sales

1998 420,000

1999 622,000

2000 901,000

2001 1,321,000

Quarterly Sales (000)

2000 2001

Qtr. 1 186 250

Qtr. 2 222 314

Qtr. 3 216 310

Qtr. 4 277 447

Total 901 1321

IDES Historical Sales Data:


The time frame for the sales forecast will determine the appropriate forecasting technique

The time frame for the sales forecast will determine the appropriate forecasting “technique”.

  • In many situations, short-run sales forecasts are made using the technique, “same period last ____”.

  • Other short-run sales forecasting techniques are “moving average”, “weighted moving average”, and “exponential smoothing”.

  • “Trend Projection” can be used to make both short-run and intermediate-run sales forecasts. This techniques uses the statistical tool known as regression analysis.

  • In “Trend Projection”, the assumption is made that sales depend on the passage of time. Sales follow a “trend” (increase, decrease, remain the same) as time passes.


Creating a short intermediate trend projection forecast using simple linear regression

Creating a short & intermediate “Trend Projection” Forecast using Simple Linear Regression

  • Arrange the Sales Data in SLR Format:

    Year Qtr(x)Sales (y)(x)2 xy

    2000 1 1 186 1 186

    2 2 222 4 444

    3 3 216 9 648

    4 4 277 16 1108

    2001 1 5 250 25 1250

    2 6 314 36 1884

    3 7 310 49 2170

    4 8 477 64 3816

    Sum 36 2252 204 11506


Finding the trend line y a bx for the intermediate run sales forecast

Finding the “trend” line (y = a + bx) for the “intermediate-run” sales forecast:

  • Use the formulas on page 94 to calculate “b” (the slope) and “a” (the intercept) of the SLR “trend” line.

    b = 11506 – 8(4.5)(281.5) = 32.67

    204 – 8(4.5)^2

    a = 281.5 – 32.67(4.5) = 134.49


Calculate the 2002 sales forecast by quarter

Calculate the 2002 Sales Forecast by Quarter:

  • Yt = a + bxt = 134.49 + 32.67(xt)

  • We used “x” values 1-8 to derive the above equation.

  • Substitute the next 4 values for “x” into the above equation and solve:

    Year-Quarter (xt)Unit Sales(000) (yt)

    2002 - 1 9 428.52

    - 2 10 461.19

    - 3 11 493.86

    - 4 12 526.53


Calculating a trend forecast using simple linear regression

Calculating a “Trend” Forecastusing Simple Linear Regression

  • Arrange the Annual Sales Data in SLR Format:

    Year (x) Sales (y) (x)2 xy

    1998 1 420 1 420

    1999 2 622 4 1244

    2000 3 901 9 2703

    2001 41321165284

    Sum 10 3264 30 9651

    x-bar = 2.5 y-bar = 816


Using slr trend projection to create the long term sales forecast

Using SLR (trend projection) to create the “Long-Term” Sales Forecast:

  • Use the formulas on page 94 to calculate “b” (the slope) and “a” (the intercept) of the SLR “trend” line.

    b = 9651 – 4(2.5)(816) = 298.2

    30 – 4(2.5)(2.5)

    a = 816 – 298.2(2.5) = 70.5


Calculate the 5 year sales forecast

Calculate the 5-Year Sales Forecast

  • Yt = a + bxt = 70.5 + 298.2(xt)

    Substitute the next 5 values for “x” into the above equation and solve:

    Year (xt)Unit Sales (000) (yt)

    2002 5 1561.5

    2003 6 1859.7

    2004 7 2157.9

    2005 8 2456.1

    2006 9 2754.3


What does the long term sales forecasts tell us

What does the “Long-Term” Sales Forecasts tell us?

Forecast Present Capacity

Year SLR Reg Time O/T Shortage

2002 1562 1248 1498 64

2003 1860 1248 1498 362

2004 2158 1248 1498 660

2005 2456 1248 1498 958

  • 2754 1248 1498 1256

  • IDES Manufacturing will have to subcontract for 64,000 units during 2002 and begin to add capacity during 2002 to meet the expected demand during the next five years.


Another method for making the intermediate term sales forecast

Another method for making the “Intermediate-Term” Sales Forecast:

  • Calculating a “Seasonally Adjusted Trend” Sales Forecast:

  • From the historical data, find the “Seasonal Index” (SI) for each quarter of the year.

  • Using the “trend line” calculate the sales for 2002 (entire year).

  • Multiply the appropriate SI by the sales forecast for the year to obtain the “Seasonally Adjusted” sales forecast for each quarter.


Seasonal index ave for qtr ave for year

Seasonal Index = Ave for Qtr/Ave for Year

2000 2001 Total Ave. Seasonal Index

Qtr. 1 186 250 436 218 0.1962

Qtr. 2 222 314 536 268 0.2421

Qtr. 3 216 310 526 263 0.2367

Qtr. 4 277 447 724 362 0.3258

Total 901 1321

Total sales for both years = 901+1321 = 2222

The average annual sales for the two years = 1111

To calculate the SI:

Qtr.1 = (Ave Sales Qtr 1)/(Ave Annual Sales) =0.1962


Seasonally adjusted forecast for 2002

Seasonally Adjusted Forecast for 2002

  • Multiply the SI for each quarter by the forecast for the entire year:

    Qtr 1: (0.1962)(1562) = 306.46

    Qtr 2: (0.2421)(1562) = 378.16

    Qtr 3: (0.2367)(1562) = 369.73

    Qtr 4: (0.3258)(1562) = 508.90


Forecast for qtr 1 of 2001

Forecast for Qtr 1 of 2001:

  • Use the forecast for Qtr 1 we just calculated. It incorporates both the trend (growth in this case) and the seasonal influences that are evident in the historical sales data.

  • Qtr 1 Forecast = 306.46


What does the qtr 1 forecast tell us

What does the Qtr 1 Forecast tell us?

  • Production capacity at regular time exceeds the sales forecast.

  • Regular time capacity = 312

  • Forecast = 306.46

  • IDES does not need to use overtime production or subcontracting to meet the needs for this quarter.

  • But Qtr 2 sales are expected to be 378.16 and this does exceed O/T capacity (364).

  • What should IDES do?


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