Recently, a customer of mine wanted to know how to improve their company’s sales forecast accuracy. We discussed it at length and I mentioned how some companies use the PERT calculation. To be successful means to account for the three possible outcomes found within the calculation: These include the “best case scenario”, “most likely scenario” and “worst case scenario”. They also happen to be the same kinds of scenarios that salespeople review when analyzing their potential for business at a customer account.
The Three Variables in the PERT Calculation
Before going into how PERT can help to improve sales forecasting accuracy, it’s ideal to review these three aforementioned outcomes and the calculation itself. The analysis relies upon these three possible outcomes and assigns a value to each. When using the calculation to improve forecast accuracy, these three outcomes of “best case scenario”, “most likely scenario” and “worst case scenario”, would be similar to the kinds of scenarios salespeople might review on an account.
Those questions are predicated on the likelihood that the salesperson will secure a portion of the customer's business. It's similar to asking: "What's the most I can sell" ,"What am I likely to sell" and if neither of these happen, "What's the least I can sell?". These outcomes and the calculation are shown below. In each case, I've applied a variable to each possible outcome - A, B, & C.
Best Case Scenario = A
Most Likely Scenario = B
Worst Case Scenario = C
PERT Calculation = {1(A) + 4(B) + 1(C)} / 6
Now, the question becomes, how can PERT be used to help improve a company’s sales forecast accuracy? Well, to accomplish this, we’ll first look at the sales budgets. After all, companies always establish budgets first. It’s these budgets that are used to set goals and objectives for sales representatives.
We'll base our approach on a supplier selling product to an original equipment manufacturer, or OEM. We’ll be looking at how the calculation can be used to improve forecast accuracy by its most basic component: sales to an individual customer account. Proper sales forecasting requires the sales professional forecast what they believe they will sell at individual accounts. The sales professional would then sum up all sales to all individual accounts to come up with the forecast for their entire territory. Management would then use these numbers to gauge future sales and to establish the company’s sales budget.
An Example Using PERT in Forecasts
In our example, the equipment manufacturer currently provides three product lines with various volumes sold across those lines to its own customers. The supplier knows that for every equipment line, the OEM requires two of the supplier’s products. The supplier makes $10.00 of gross profit for each unit sold. Therefore, one line represents $20.00 of gross profit for the supplier. For each of those lines, the supplier would use the calculation to improve their forecast accuracy. Here’s an example below.
Explanation of Above Table
In our example above, the sales professional uses the PERT analysis on each equipment line based on how much they believe they would sell to this particular customer. The variables of “best case scenario”, “most likely scenario” and “worst case scenario” are present in each analysis.
For example, for line 1, the sales person believes the “best case scenario” is 100% of the equipment manufacturer's business, which would be the 100% of the gross profit ($2000). The “most likely scenario” is 50% of this equipment manufacturer's business ($1000.00) and the “worst case scenario” would be 25% ($500.00). In the case of line 1, the sales person should attain a minimum gross profit of $1,083.33.
Important Note: While this example shows percentages of what the salesperson believes he or she can sell, it could just as easily be done by focusing on unit sales. It's entirely up to you.
If you want to learn about some other tips you can use to improve your accuracy, then please read: How do we Improve our Sales Forecast Accuracy
Perform Same Analysis for Total Account
The sales person would therefore ask him or herself these same three questions when reviewing his or her potential sales to the customer for line 2 and Line 3. You’ll notice that the sales person uses different percentages for his three variables for each of the subsequent lines. In this case, he or she may feel more or less confident in each of the variables. For line 2, the sales person should attain a minimum gross profit of $1,800.00. For line 3 he or she should attain a minimum gross profit of $4,400.00. For the entire account, the sales professional should attain a minimum total gross profit of $7,283.00.
The resulting figures in our example represent a sales forecast accuracy based on an individual account using the PERT analysis. In this case, the sales representative would have to thoroughly understand the potential for sales at the customer’s account. If done properly, the calculation and analysis can be used to improve a company’s forecasts. However, this is somewhat labor intensive, and most forecasting software programs account for these three variables, to some extent.
Regardless, if someone were to come up with a monster excel spreadsheet, and had their sales people perform the analysis on each and every one of their individual customers, then they could improve their sales forecasting accuracy. If you would like to have access to a sample excel sheet for using this approach, please read: Sample Sales Territory Forecasting Excel Sheet for Small Businesses
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