In: Finance
The Fresh Detergent Case
Enterprise Industries produces Fresh, a brand of liquid detergent. In order to more effectively manage its inventory, the company would like to better predict demand for Fresh. To develop a prediction model, the company has gathered data concerning demand for Fresh over the last 33 sales periods. Each sales period is defined as one month. The variables are as follows:
Demand = Y = demand for a large size bottle of Fresh (in 100,000)
Price = the price of Fresh as offered by Ent. Industries
AIP = the average industry price
ADV = Ent. Industries Advertising Expenditure (in $100,000) to Promote Fresh in the sales period.
DIFF = AIP - Price = the "price difference" in the sales period
Question:
Month/Yr. |
PERIOD |
PRICE |
AIP |
DIFF |
ADV |
DEMAND |
June 2016 |
1 |
6.1 |
5.8 |
-0.3 |
5.3 |
14.4 |
2 |
5.75 |
6 |
0.25 |
6.75 |
15.3 |
|
3 |
5.7 |
6.3 |
0.6 |
7.25 |
16.5 |
|
4 |
5.7 |
5.7 |
0 |
7.3 |
16.1 |
|
5 |
5.6 |
5.85 |
0.25 |
7.2 |
16 |
|
6 |
5.6 |
5.8 |
0.2 |
6.5 |
15.5 |
|
7 |
5.6 |
5.75 |
0.15 |
6.75 |
15.2 |
|
Jan. 2017 |
8 |
6.3 |
5.85 |
-0.45 |
6.89 |
13.9 |
9 |
6.4 |
5.65 |
-0.75 |
5.8 |
13.3 |
|
10 |
6.2 |
6 |
-0.2 |
5.5 |
13.12 |
|
11 |
5.9 |
6.1 |
0.2 |
6.5 |
13.8 |
|
12 |
5.9 |
6 |
0.1 |
6.25 |
14.8 |
|
13 |
5.7 |
6.1 |
0.4 |
7 |
15.3 |
|
14 |
5.75 |
6.2 |
0.45 |
6.9 |
16.3 |
|
15 |
5.75 |
6.1 |
0.35 |
6.8 |
17.5 |
|
16 |
5.8 |
6.1 |
0.3 |
6.8 |
17.4 |
|
17 |
5.7 |
6.2 |
0.5 |
7.1 |
17.1 |
|
18 |
5.8 |
6.3 |
0.5 |
7 |
16.8 |
|
19 |
5.7 |
6.1 |
0.4 |
6.8 |
16.5 |
|
Jan. 2018 |
20 |
5.8 |
5.75 |
-0.05 |
6.5 |
16 |
21 |
5.8 |
5.75 |
-0.05 |
8.1 |
15.2 |
|
22 |
5.75 |
5.65 |
-0.1 |
7.7 |
15.3 |
|
23 |
5.7 |
5.9 |
0.2 |
7.3 |
15.9 |
|
24 |
5.55 |
5.65 |
0.1 |
7.5 |
16.2 |
|
25 |
5.6 |
6.1 |
0.5 |
8.1 |
17.5 |
|
26 |
5.65 |
6.25 |
0.6 |
8.3 |
18.4 |
|
27 |
5.7 |
5.65 |
-0.05 |
8.7 |
19.4 |
|
28 |
5.75 |
5.75 |
0 |
9.2 |
19.1 |
|
29 |
5.8 |
5.85 |
0.05 |
8.4 |
18.7 |
|
30 |
5.3 |
6.25 |
0.95 |
8.8 |
18.2 |
|
31 |
5.4 |
6.3 |
0.9 |
9.5 |
18.4 |
|
Jan. 2019 |
32 |
5.7 |
6.4 |
0.7 |
9.3 |
17.5 |
Feb. 2019 |
33 |
5.9 |
6.5 |
0.6 |
9.1 |
17.1 |
PRICE | AIP | DIFF | ADV | DEMAND | |
PRICE | 1 | ||||
AIP | -0.23374 | 1 | |||
DIFF | -0.76244 | 0.807343 | 1 | ||
ADV | -0.55717 | 0.299438 | 0.537413 | 1 | |
DEMAND (Y) | -0.64098 | 0.299191 | 0.588114 | 0.783047 | 1 |
The Above table shows the result of the co-relation matrix. the co relation matrix could be calculated by using excel. In excel, under Data Tab, go to data analysis and click. From the list of options select co relation. Select the above table in the input column and click enter.
Interpreting the results:-
the strong co relation factors (r>.5) are DIFF and ADV.
This means that when the product price is less than that of the industry, the product seems more attractive and hence demand increases. This shows that the DIFF and Demand are positively co related.
ADV or Advertising Expenditure also increases. More the expenditure, more will be the demand for the product
As we can see Price has a very strong negative co relation with the demand. that is as the price goes up, the demand decreases.