Category Archives: incentives for accuracy in forecasting

Sales Forecasts and Incentives

In some contexts, the problem is to find out what someone else thinks the best forecast is.

Thus, management may want to have accurate reporting or forecasts from the field sales force of “sales in the funnel” for the next quarter.

In a widely reprinted article from the Harvard Business Review, Gonik shows how to design sales bonuses to elicit the best estimates of future sales from the field sales force. The publication dates from the 1970’s, but is still worth considering, and has become enshrined in the management science literature.

Quotas are set by management, and forecasts or sales estimates are provided by the field salesforce.

In Gonik’s scheme, salesforce bonus percentages are influenced by three factors: actual sales volume, sales quota, and the forecast of sales provided from the field.

Consider the following bonus percentages (click to enlarge).


Grid coordinates across the top are the sales agent’s forecast divided by the quota.

Actual sales divided by the sales quota are listed down the left column of the table.

Suppose the quota from management for a field sales office is $50 million in sales for a quarter. This is management’s perspective on what is possible, given first class effort.

The field sales office, in turn, has information on the scope of repeat and new customer sales that are likely in the coming quarter. The sales office forecasts, conservatively, that they can sell $25 million in the next quarter.

This situates the sales group along the column under a Forecast/Quota figure of 0.5.

Then, it turns out that, lo and behold, the field sales office brings in $50 million in sales by the end of the quarter in question.

Their bonus, accordingly, is determined by the row labeled “100″ – for 100% of sales to quota. Thus, the field sales office gets a bonus which is 90 percent of the standard bonus for that period, whatever that is.

Naturally, the salesmen will see that they left money on the table. If they had forecast $50 million in sales for the quarter and achieved it, they would have 120 percent of the standard quota.

Notice that the diagonal highlighted in green shows the maximum bonus percentages for any given ratio of actual sales to quota (any given row). These maximum bonus percents are exactly at the intersection where the ratio of actual sales to quota equals the ratio of sales forecast to quota.

The area of the table colored in pink identifies a situation in which the sales forecasts exceed the actual sales.

The portion of the table highlighted in light blue, on the other hand, shows the cases in which the actual sales exceed the forecast.

This bonus setup provides monetary incentives for the sales force to accurately report their best estimates of prospects in the field, rather than “lowballing” the numbers. And just to review the background to the problem – management sometimes considers that the sales force is likely to under-report opportunities, so they look better when these are realized.

This setup has been applied by various companies, including IBM, and is enshrined in the management literature.

The algebra to develop a table of percentages like the one shown is provided in an article by Mantrala and Rama.

These authors also point out a similarity between Gonik’s setup and reforms of central planning in the old Soviet Union and communist Hungary. This odd association should not discredit the Gonik scheme in anyone’s mind. Instead, the linkage really highlights how fundamental the logic of the bonuses table is. In my opinion, Soviet Russia experienced economic collapse for entirely separate reasons – primarily failures of the pricing system and reluctance to permit private ownership of assets.

A subsequent post will consider business-to-business (B2B) supply contracts and related options frameworks which provide incentives for sharing demand or forecast information along the supply chain.