When survey pay data doesn’t add up 

Compensation leaders rely on market data to inform critical pay decisions, from annual merit budgets to incentive design. Yet one of the most common questions we hear from clients is deceptively simple:

“Why doesn’t the median base salary plus the median bonus equal the median total cash?”

The short answer: because tabular survey data are independently arrayed by design. Understanding what that means, and how to use the data correctly, can materially improve the quality of pay decisions.

How survey data are constructed

In WTW compensation surveys, as in most compensation surveys, each element of pay is analyzed on its own. This approach applies to base salary, short‑term incentive (STI) opportunity (annual bonus), long‑term incentive (LTI) opportunity, target total compensation (TTC), and target total direct compensation (TDC).  

In practice, this means the median base salary is calculated independently of the median STI opportunity. The median TTC is not derived simply by adding median base and median bonus, it is also calculated independently. The same principle applies to TDC and its underlying components.

Each figure reflects the median of that specific pay element across all participants. It is not intended to represent a single, internally consistent “median pay package” that any one individual actually receives.

Why independent arraying matters

Independent arraying serves two important purposes. First, it accurately reflects what is really happening in the market by showing the full range of pay practices submitted by survey participants. Second, it protects participant confidentiality by ensuring no one can reverse-engineer an individual’s pay package.  

However, there is a more practical reason this approach matters: Companies emphasize pay elements differently. In other words, they don’t design pay the same way.

Some organizations more heavily weight LTIs while maintaining modest annual bonuses. Others emphasize cash incentives while using equity more selectively. Still others prioritize base pay stability. These design choices are intentional and vary widely by size of organization, industry and even among peers within the same industry.

As a result, the submissions driving the median STI opportunity are not necessarily the same submissions driving the median LTI opportunity. Independent arraying acknowledges reality rather than forcing different pay designs into an artificial TCC or TDC calculation.  

An illustrative example

Imagine a simplified survey population with two broad groups of executives:

• Group A executives have relatively high STI opportunities, but less emphasis is placed on LTIs
• Group B executives have more modest STI opportunities but significantly higher LTI opportunities

Now consider what happens when the data are summarized:

• The median STI percentage may be driven primarily by Group A
• The median LTI percentage may be driven primarily by Group B

Those medians each reflect the market accurately but are influenced by two different groups of employees. If you then apply those two medians to the same base salary, the resulting “constructed” TDC can appear higher — or lower — than what any individual executive in the survey actually receives.  

That outcome is not an error. It is a reminder that percentile statistics describe distributions and are not additive. In other words, they are not fully designed pay packages and the medians, by design, do not add up.

What this means for compensation professionals

The implication for compensation decision making is clear: Market data should be evaluated both by individual pay elements and the aggregate, but not mechanically built-up from component medians.

In practice, that means stepping back from medians and focusing on intent of your pay program. Start by assessing pay competitiveness at the element level (e.g., base vs. market base, STI leverage vs. market STI).  

Follow that assessment with an independent review of aggregate measures such as TTC and TDC. on their own terms rather than summing up the elements that comprise their respective definitions.  

Finally, and most importantly, use the pay data to design pay intentionally. Align the pay mix with your business strategy, performance orientation and talent priorities rather than forcing alignment to a synthetic “median package” that doesn’t actually exist in the market.  

This approach helps organizations focus on the right questions:

• Are we positioning base pay appropriately for role scope and talent risk?
• Is our incentive mix aligned with how we want leaders to create value?
• Does our total opportunity reflect the market for our design philosophy, not someone else’s?

Using market data as insight, not a formula

Survey data are powerful precisely because they capture the full range of market practices, not a single, one‑size‑fits‑all answer. Independent arraying ensures the market is represented clearly, without creating artificially constructed totals that no incumbent actually earns.  

The most effective compensation programs do not attempt to replicate a “median incumbent.” Instead, they use market data as a strategic reference point, layering in judgment, context and business intent.

When used this way, market data stop being a math exercise and become what they are meant to be: a tool for better, more informed decision making.