Posted: November 11th, 2015
Forecasting HR Demand for Installers
A large kitchen cabinet and appliance distributor in the Southeast expects an
increase in annual sales during the next 10 years from $1,500,000 to $2,250,000.
In scanning its external environment, it notes that the local environment is
changing:
Many new employees have entered the market area
The population is aging; many are now “empty-nest” couples whose children have
moved away. These individuals are remodeling their homes and seek larger, more
expensive kitchens.
Many new families have entered the area who are budget conscious and want a kitchen
to fit into their price range
Building costs are steady
The HR planner for the kitchen distributor wants to forecast the requirements for
installers for the next 10-year period. Because installers require 8 months of on
the job training in addition to classroom instruction, an accurate forecast is
needed. The CEO wants to use their own installers in the future rather than
relying on the more expensive outside subcontractors. You must forecast demand by
determining the relationship between the sales of the distributor and the number of
installers required. As such, you contact several distributors of various sizes
in the United States and obtain the following information:
Sales in Millions (S) Number
of Installers
1.0
4
1.5
7
2.0
9
2.5
15
3.0
17
Tasks
Plot these figures within WORD on a scatter plot. Estimate a regression line.
That is, draw a line that cuts straight through the center of the points (one that
minimizes the distance between the lines and the plotted points).
Using your plot, estimate the number of installers needed for forecasted sales of
$2.25 million.
Answer in paragraph form: Given the trends and the nature of the industry, what
other advice can you give the HR planner? Review costs of kitchen renovations, age
of buyers, etc.
Answer in paragraph form: Why might using the plotted information alone be risky?
Answer in paragraph form: What other factors should you consider? Why?
Describe the quantitative and qualitative techniques that are used to forecast
human resources demand.
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