Compensation Observability: The 7 Signals Every Revenue Leader Should Be Tracking

Sales compensation plans are some of the most influential tools at an organization’s disposal to drive sales behavior. However, at many companies, compensation is treated solely as a payroll tool only used at the end of a period to calculate commissions.

There’s a problem with this thinking. 

Compensation isn’t just a payout tool it’s a goldmine of behavior signals that indicate how your sales organization is executing on your go-to-market strategy. When you continuously track and surface these signals through your RevOps process, RevOps and executive teams can identify revenue risks long before they surface in your numbers.

This process is known as compensation observability. 

Compensation observability refers to the practice of monitoring key signals in your compensation program that indicate how sales teams are likely to behave given their current incentives.

In this post, we’ll review 7 of the top signals every revenue leader should be tracking.

Why Compensation Data Is An Undervalued Revenue Signal

All deals booked by a sales representative are executed with incentive compensation in mind. After all, every deal closed represents the path of least resistance (or highest reward) based on the current plan design.

Do your reps prefer booking deals with higher revenue or higher margin? Are accelerators tied to upsells encouraging your team to push certain products harder?

Left unexamined, these behavior patterns can haunt your numbers. When properly tracked through modern Sales compensation solution, however, these patterns become invaluable signals.

Below are seven compensation observability signals every revenue leader should add to their scorecard.

Signal 1: Commission-to-Revenue Ratio Drift 

Organization-wide commission-to-revenue ratio shows how much of every dollar of revenue is being paid out in sales incentives.

Typically, you’d expect this number to remain relatively stable from month-to-month and quarter-to-quarter. If you start to see this ratio increase without explanation, you may be at risk for:

1. Poor discount discipline
2. Accelerators running too high
3. Poor quota setting 

Let’s say your organization expects a 9% commission-to-revenue ratio each quarter. But when analyzing your numbers on SAP SuccessFactors Incentive Management, you notice the current quarter is pacing at 12%. Why? Digging deeper, you discover several enterprise deals have qualified for multiple accelerators.

Without tracking this signal, increasing cost of sales will bleed through your margins without anyone noticing.

Signal 2: Quota Attainment Distribution 

Analyzing quota attainment distribution will help you understand how many reps are exceeding (or failing to meet) quota.

Ideally, you want to see a bell curve with:

1. High performers far exceeding quota
2. Majority of reps close to or at quota
3. Low performers falling short of quota 

However, if a majority of your reps are drastically exceeding quota halfway through the year, your quotas are probably set too low. Alternatively, if very few reps are hitting their quota, your plan is probably not motivating your team enough.

For instance, if you find that only 20% of your sales reps are hitting quota at the end of Q3, leadership may decide to conduct a review of territory design, quota setting, or market shifts.

Signal 3: Override Frequency 

High override frequencies can indicate areas where your plan has failed to keep up with the ways your organization does business.

Overrides occur when exceptions to standard plan rules must be applied to special deals. Examples include unusually large deals, customer pricing wins, enterprise contracts spanning multiple years, or strategic accounts.

If you start to see a high frequency of overrides occurring each month, it’s a sign there are problems with your plan’s mechanics. For example, let’s say enterprise deals frequently require a payout override because your plan doesn’t account for multi-year contracts. Rather than continuing to manage these deals as exceptions to the plan, RevOps should work with sales leadership to revise plan mechanics to account for these types of deals.

As a general rule of thumb, if you’re seeing more than 5% overrides each month, it’s likely worth revisiting plan design.

Signal 4: Deal Size Concentration 

Sudden increases or decreases in average deal size can have material effects on your commission payouts.

If you start to see higher concentrations of revenue being generated by large enterprise deals, your commission structure may result in unexpectedly large payouts.

Consider a scenario where a commission plan was designed based on an average deal size of $50,000. However, over time your sales teams start closing more $1 million enterprise deals. Rather than commission payouts increasing gradually with revenue, payouts may spike to unhealthy levels.

Tracking deal size concentration can help you plan for and maintain predictable incentive expenses.

Signal 5: Margin Variance on Commissionable Deals 

Revenue growth is only good if it can be profitable.

If your sales teams are booking deals with no regard for margin (perhaps by qualifying for 100% commission even if they offer no margin to the organization), they may tend to drive deals through no matter the cost.

Monitoring margin variance on deals that earn commission can help RevOps understand whether sales teams are being driven to sell profitably.

Imagine your commissions plans qualifies reps to earn 100% commission on all deals >= $10,000 regardless of margin. If you start to see average gross margin on commissionable deals drop from 65% to 52% in Q1, something may need to change in the plan.

Signal 6: Product Mix Incentive Effectiveness 

Product specific incentives are commonly used to drive adoption of new products.

However, just because you offer a higher commission rate on Product A doesn’t necessarily mean your reps will focus on selling it.

Through compensation observability, sales leaders can use data to understand whether changes to product mix are being influenced by your incentive plans.

If you launch a new analytics product that sells for $500 per user but offers a 20% commission rate, but adoption doesn’t start to materialize until several months later, there could be a few reasons why:

1. Your sales teams aren’t being trained how to sell the product
2. Your new product has poor product-market fit
3. There are underlying issues with how your new product’s incentives are designed

Knowing these signals can help leadership troubleshoot which changes to plan design (or perhaps even go-to-market strategy) need to be made.

Signal 7: Commission Dispute Rate 

Commission disputes are a signal that not everyone is happy with the way commissions are being paid.

If employees feel that commission isn’t being paid accurately, they can submit a dispute which is typically reviewed by a committee of leadership.

If commission disputes start to become frequent (for example 18% of employees submit a commission dispute each quarter), leadership may need to take action to improve plan design or improve transparency.

While dispute handling takes time away from RevOps teams, high frequencies of commission disputes can also erode trust between sales and finance.

Conclusion 

The power of compensation observability is realizing your compensation program is much more than just a tool to pay commissions.

Revenue leaders who continuously track these 7 signals will be better equipped to:

1. Catch shifts in behaviour sooner
2. Exert financial control
3. Ensure incentives are properly aligned to business objectives
4. Iterate on plan design proactively 

Waiting until next year’s plan design process to analyze how your plan is driving behavior is no longer an option.

Revenue leaders who implement compensation observability gain a real-time window into how sales teams will behave given their current incentives.

And when your incentives are aligned to your strategy, predictable revenue *and* profitability will follow.