Walking the Tightrope of Sales Compensation Modeling

Author: 
Dave Egloff, Senior Director at Gartner

For many organizations, sales commissions are the highest variable expense and unfortunately, very challenging to forecast. That is an uncomfortable fact — the chief sales officer’s highest variable expense might be the most challenging to predict.

While most CSOs scrutinize compensation designs and the tie between rewards and sales strategy, very few are paying attention to how the sales compensation plans are modeled. It’s not enough to ask if a sales compensation plan was modeled. A CSO must ask how the sales compensation plan was modeled.

A commonly observed modeling approach is to take a compensation plan and examine how changes influence commission expense based on the prior year’s sales performance. For example, a CSO may ask “what is the commission impact of a compensation plan change based upon last year’s results?” While most sales compensation practitioners can answer that question, a CSO needs to understand that last year’s performance isn’t likely to reoccur this year. This renders the prediction unlikely and misleading. CSOs need to start by asking two questions:

  • What is the probable range of sales compensation expense for the upcoming year?
  • What assumptions led to that conclusion?

Posed with the original question of “what would have been the impact last year?”, many practitioners offer a fixed number (e.g., $400k of additional expense). While this might be the best guess, it falls short to describe the range of possible outcomes or the sensitivity that might drive the estimates up or down. Using a forward-looking stress test, a more descriptive answer to the question of “how much?” is possible:

Last year, the impact would have been $400,000 of additional expense, but the stress test suggests an impact of $490,000 with a probable range between $400,000 and $675,000 in additional expense based upon possible dispersions of sales performance.

Traditional modeling approaches are limited

The two most common approaches — back-testing and extrapolation — are reasonably simple and generate plausible answers. However, these approaches lead to false senses of certainty and misinformation. Traditional modeling is extremely dependent on predictability. If anything changes to diminish predictability — like sales strategy shifts, head count changes, macro-economic conditions, etc. — traditional modeling reliability rapidly deteriorates.

To manage expense risk and generate more predictable outcomes, CSOs should require that sales compensation plans be evaluated using tools like a Monte Carlo simulator.

A Monte Carlo simulator is a probability-based simulation that leverages statistically relevant but randomized inputs that are repeated over many different trials. In one simulation, a modeled outcome derives from 20-years (or more) of trial results. This is not just a model but a true stress test. While this may sound elaborate and expensive, it can be built in MS Excel with an intermediate competency level.

Many factors alter commission expense, including compensation plan design, sales coverage model, quota allocation effectiveness, and seller performance. If nothing else, individual seller performance is unlikely to repeat from one year to the next. Therefore, even without compensation plan changes, commission expense varies from year to year.

Monte Carlo Simulators are far more comprehensive

The Illustrated Monte Carlo Simulation Output provides an example of what a CSO should expect to see each year.

CSOs can design a more effective sales compensation plan, improve financial planning and manage risk by understanding the probable range of outcomes. Additional insights come from examining the less probable outcomes. If the less probable outcomes are not tolerable, the compensation plans should be redesigned to reduce volatility.

In addition to volatility, CSOs should recognize the compensation plan sensitivity. Sensitivity represents the change in anticipated expense outcomes as the aggregate sales performance changes. More plainly, sensitivity shows how expense increases with overall over-performance and how expense decreases with under-performance. CSOs should look to address the commission expense impact as sales results vary by +/-5%.

Sales compensation modeling is first and foremost about confidence

CSOs must be confident that the proposed compensation plan designs are stress tested before offering their approval. This is the best practice and a key part of sales compensation effectiveness and risk management.