Business,
Other
Marketing Forecast
Marketing
The shoe company that I was recently hired is working on next year’s sales forecast for its line of
women’s casual shoes. The company has been in the shoe manufacturing and sales business for
over 35 years and sells shoes through a chain of stores located throughout three market areas, the
Northeast (New England, New York), Upper Mid-West (Ohio, Illinois, Michigan), as well as a new
market area in the Southeast U.S. (Georgia, South Carolina, Florida). The senior management and
the sales staff are experienced, however about 15 percent of the company sales came from the new
Southeast sales district last year, and the company only has last years sales figures for this
area. The company is also considering modifying 2 of its 8 different women’s shoe styles for next
year,
with
modifications
in
color
and
shape.
The Marketing Director of the company has asked for my recommendations on what techniques
should be used to prepare next year’s sales forecast for all three market areas. I need to
recommend three different techniques the company could use or some combination of techniques.
Briefly describe how the company should conduct the forecast (who might be involved, basic types
of data needed) and why I think the techniques I recommended would be effective. Being as new as
I am I don’t have a clue.
Solution – Marketing Forecast
Your Shoe Company needs to use two different approaches for forecasting for next year. The two
approaches will be different as the region in which it has been operating has been quite different.
First, the Shoe Company should use time series techniques for forecasting sales in the Northeast
and Upper mid-west regions. This is because the company has been operating in these regions
for the last 35 years. Due to this, the shoe company must be having ample amount of historical
data (35 years) which can be used to develop a robust forecasting model to predict sales for the
next year. It is quite difficult for any firm to keep a record of data for 35 years, but data for last 510 years on a monthly basis will be more than enough to develop a robust forecasting model. The
historical sales data can be used to forecast sales by incorporating any trends or seasonality effect
in the sales of shoes.
Forecasting can be done at different levels, different sizes and different colors as the Shoe Company
is planning to modify women’s shoe styles. Some of the sales forecasts that can be achieved using
historical data:

Overall
o
o
o
o
Sales
Region wise sales
Shoe number wise sales
Shoe color wise sales
Customer wise (Men / Women / Kids) wise sales
The data for the above can be structured in the following way:
Sample data set: The structuring of the data in this manner will ensure development of different
levels of forecasting model as mentioned above.
Market
Area
North east
North east
Upper mid
west
Upper mid
west
Upper mid
west
Southeast
Southeast
Southeast
Region
Year
Month
200501
200501
Sales
Customer
Size
Color
100000
90000
Men
Men
9
9
Black
Black
200501
120000
Men
9
Black
Illinois
200501
110000
Men
9
Black
Michigan
200501
85000
Men
9
Black
Georgia
200501
15000
Men
9
Black
South
Carolina
Florida
200501
18000
Men
9
Black
200501
20000
Men
9
Black
New York
New
England
Ohio
Based on the preliminary analysis of the data, specific forecasting techniques like: Moving Average,
Exponential smoothing, ARIMA/Holt-Winter’s model etc can be used for minimizing the error in sales
forecast.
For conducting sales forecast using Quantitative techniques, Data Managers, Analysts (Internal/,
External) and Senior Management should be involved.
It should be kept in mind that any changes / modifications in the product should be done only after
incorporating customer inputs through primary research by conducting a survey or observing the
change in customer’s preference towards specific colors or change in the demographics of the
customers due to which the shoe sizes are changed. This insight can be gained by conducting
simple trend analysis of available historical data.
Second, in Southeast region, sales data is available only for the previous year. Hence, Time
series forecasting or any other Quantitative Forecasting method like Simulation or Causal Modeling
(Regression) cannot be used. It is therefore recommended to use combination of Qualitative
forecasting techniques like Delphi method, Sales force opinion, Industry expert’s estimates,
consumer survey(Conjoint analysis) etc.
For conducting sales forecast using Qualitative techniques Senior/middle Management, Industry
experts, Sales force, customers and channel partners could be involved depending on the technique
used and the objective/ scope of sales forecast.