CASE 7-1
SALTFLATS, INC.
A Sales Force Allocation Case
SaltFlats is a modestly sized salt producer. The market for salt is stable, with little growth from year to year. Growth for SaltFlats usually occurred through trading shares with other salt producers -- thus increasing its sales at the expense of competitors. The average number of accounts for each salesperson in the firm is around 85.
Let us follow a procedure to evaluate SaltFlats' salesperson call performance. While in the main command menu of SALESPLN, invoke "GRID", and the screen will appear as in Figure 7-3. As the Figure shows, most of the accounts for the two salespeople are in Grid segment 3 and 4 -- those with low growth opportunity. In particular, many accounts appear in Grid 3. For a mature market as is the case with salt, such an allocation is probably appropriate. In a growing market, however, such a large proportion of Grid 3 accounts could cause problems for future growth of the company.
Although the salespeople appear to be allocating their calls appropriately on Grid 3 and Grid 4 accounts, we would expect a larger average number of calls in Grid 3 (which has high strength) than Grid 4. This is not happening. Another discrepancy appears to be in the average number of sales calls for Grid 2 accounts.
To investigate further, we need to go to the individual salesperson database. Hit <ENTER> to return to the main menu, then "RETRIEVE", load STEMP1, and select "VIEW" from the secondary command menu. The screen will appear as in Figure 7-6.
It happens that Salesperson #1 (in Figure 7-4) frequently calls on Grid 2 accounts. To quickly find which accounts receive many calls, the database may be sorted. Choose the "DBASE," then the "SORT" command, and sort the file on the number of calls (column C). The screen will appear as in Figure 7-7.
FIGURE 7-6
"GRID" VIEW OF SALESPERSON #1
A B C D E F G H
35 GRID BREAK VALUE B-OPP B-STR
36 0.15 0.15
37
38 SUMMARY STATISTICS BY GRID
39 GRID GRID GRID GRID TOTAL
40 GRID 1 2 3 4
41 COUNT 10 5 4 1 20
42 TOTAL SALES CALLS 183 46 18 6 253
43 TOTAL SALES 247280 128412 3015 1475 380182
44 AVERAGE SALES CALLS 18.30 9.20 4.50 6.00 12.65
45 AVERAGE SALES 24728 25682.4 753.75 1475 19009.
46 ATTRACTIVENESS TOTALS 181.25 29.07 22.47 3.56
47 RECOMMENDED CALLS 12 10 6 4
48 TOTAL RECOMMENDED CALLS 120 50 24 4 198
FIGURE 7-7
SORTED ACCOUNTS FOR SALESPERSON A
A B C D E F G H
1 ACCT# NAME CALLS SALES OP1 OP2 OP3 ST1
2 18725 AAJ 96 144687 350000 20000 4 1
3 32530 AAT 35 29992 30000 3000 3 3
4 28414 AAM 24 111341 300000 5000 3 1
5 12795 AAF 10 12801 12000 2000 3 3
6 18676 AAI 10 6278 100000 6000 3 2
7 32150 AAR 6 2285 6000 1000 3 2
8 2350 AAC 6 429 2000 500 2 3
9 14670 AAG 6 834 1000 350 3 3
10 31475 AAN 6 3873 5000 1000 3 2
Notice the number of calls to account AAJ. In asking Salesperson #1 about this, SaltFlats learned that this salesperson made it a point to call on account AAJ about twice a week and drop by a box of doughnuts. The calls, therefore, were not truly sales calls, but were a simple courtesy. (SaltFlats subsequently referred to this account as the "doughnut connection.") The courtesy evidently paid off, however, considering the volume of sales coming from that account (the SALES column).
The large number of calls to this account, however, highlights the importance of investigating individual statistics more closely when summary statistics appear to be out of line. In this case it is a result of a special consideration for an account. The sales call figure could possibly be adjusted to represent the number of "true" sales calls to avoid overwhelming the averages. Or, the case could be taken out of the database because of its unique nature.
What-if Calculations. Several what-if scenarios can be performed. One of these scenarios might deal with the classification of accounts, using what we have called "break point values." These are shown in the "VIEW" screen. Break point values allow you to set the criterion levels which classify each account into high or low opportunity and strength grids. This classification is based on the values of OPP and STR (discussed above) for the account, and the break point value. That is, grid membership for the account is affected by the value set for the break points.
The break points are standardized scores, with the average account having a score of 0. In the current worksheet, the break points have been set at .15 for both opportunity (B-OPP) and strength (B-STR). This sets break points at levels slightly higher than the average levels for opportunity and strength.
Break point values are set at a value above 0.0 to be sure that accounts were well above average before classifying them into High Opportunity or High Strength. A problem can occur, however, if several of the accounts are at the extreme end of the opportunity or strength range. For instance, our AAJ account is several standard deviations above the mean. The large amount of sales potential for this account alone has significantly raised the mean. Thus the other, more normal, accounts appear lower compared to that mean.
As a what-if scenario, we can compensate for extreme cases by changing the Opportunity Break Value from 0.15 and see what changes occur to the portfolio allocations. To make a change, "QUIT" the menu, change the value in cell C-36, recalculate the worksheet (press function key F9), then re-invoke the menu with <ALT>-<M>.
The second what-if decision is based upon management assumptions and is the "RECOMMENDED CALLS" by Grid segment. Allocating 12, 10, 6, and 4 to the segments respectively may be appropriate, but what if significantly more calls were allocated to Grid 2 to recognize the opportunity in a stable market to capture market share from such accounts? In addition, an average of 4 calls to Grid 4 seems a little high. What if only 2 were allocated on average? You can easily make such changes, the worksheet recalculated (as above), and observe the impact on the sales call portfolio. An even better picture of the changed results can be seen by viewing the recommended call levels for individual accounts in the data.
We have just touched on some of the analyses that can be performed for SaltFlats. Others include:
1. Analyzing total recommended calls by each salesperson and across territories and comparing them with budget and time constraints.
2. Analyzing individual accounts to highlight large deviations in actual calls from expected.
3. Factoring service requirements into recommended call levels for accounts to adjust the level up or down.