If you work in compensation long enough, you will run into jobs that do not line up neatly with the job descriptions in the salary surveys you have available. Sometimes the title is new. Sometimes the role blends responsibilities across functions. Sometimes the job exists in your company, but not in enough peer organizations to generate solid market data. And sometimes the survey has relevant data, just not at the level, industry, company size, or geography you need.

When you cannot find a straight job match in your salary surveys, your goal is still the same: build a reasonable, supportable view of market pay by looking at responsibilities, impact, qualifications, and skills. The key is to focus less on finding a perfect match and more on identifying the level of work being done, the skills required, and the market context around the role.

Here are several ways you can approach salary benchmarking when the market data is limited or doesn’t exactly match up.

Focus on core responsibilities

One of the most common mistakes in salary benchmarking is relying too heavily on job titles. Titles can vary widely from one company to another, and they often do a poor job of describing what the employee is expected to do.

Instead, start by looking at the core responsibilities of the role. Ask yourself:

• What is the primary purpose of the job?
• What outcomes is the role accountable for?
• How much scope, complexity, and decision-making does it carry?
• What knowledge or experience is truly required?

This helps you find jobs in salary surveys that may not share the same title, but do share similar work content and responsibilities.

You should also look for premium skills that may justify a pay adjustment. For example, a job may align generally to a broader benchmark role, but require specialized technical skill, a hard-to-find certification, or expertise in a fast-moving area. In those cases, the base benchmark may be directionally right, but the market may apply a premium for the skill.

That is why salary benchmarking works best when you treat titles as a clue, or directional guidance, not the answer.

Combine related jobs to create a more useful market view

Sometimes there is no single benchmark job that fully matches your internal role. In that situation, it can help to combine data from two or more related jobs to create a more informed estimate.

For example, you may be pricing a hybrid role that includes elements of compensation, HR analytics, and project management. Or you may be looking at a business-facing HR role that blends specialist and generalist responsibilities. If no individual survey match captures the full picture, you can review multiple related benchmarks and assess where the internal role falls across them.

This does not mean averaging jobs mechanically without judgment. It means using the surrounding data points to develop a practical market range.

As you do this, be clear about which responsibilities are central and which are secondary. If 70% of the role aligns to one benchmark and 30% aligns to another, that should shape how you interpret the data. The more transparent your logic, the easier it will be to explain and defend your approach.

One thing to consider is how to address a job that requires additional skill that is commanding a premium in the market. Should you combine that higher role with the lower paying role, therefore diluting the premium that market commands for that skill? Or should you just set the salary based on what the required skill commands? Either way is defensible. What’s important is that you be consistent in how you address the situation.

Broaden the comparison group when your direct market is too thin

Sometimes the issue is not the job itself. The issue is that there are not enough companies in your normal comparison group to produce stable data.

When that happens, you may need to broaden the lens.

You can start by looking at a different but adjacent industry. If your usual industry cut is too small, general industry data may give you a stronger read on market pay. You can then decide whether an industry premium or discount should apply based on talent demand, specialization, or business model differences.

Company size is another useful adjustment point. If there are too few organizations in your normal revenue or employee band, you may need to use a broader size grouping and assess how the role compares in organizational scope.

Geography also matters. In some cases, local data may be sparse, especially for emerging or specialized jobs. Looking at broader national data may provide directional insight. From there, you can apply an appropriate geographic differential to bring the data closer to your labor market.

This kind of salary benchmarking is not about forcing weak comparisons. It is about using the best available market evidence and making thoughtful adjustments where needed.

Consider a skills-based benchmark, not just a competency benchmark

As jobs evolve, traditional survey matching becomes harder. That is especially true for roles shaped by digital transformation, new technology, automation, or changing business needs.

In these cases, you may get better results by looking at the market value of skills rather than relying only on a traditional job benchmark or a broader competency framework.

A skills-based benchmark focuses on the specific capabilities the market is paying for. These may include technical, analytical, digital, regulatory, or business-critical skills that meaningfully influence pay. If the role requires scarce or high-demand skills, the market may reward those skills even when the overall job structure is not fully standardized.

A competency benchmark can still be useful, especially when you are evaluating broader expectations like leadership, influence, communication, or problem-solving. But when pay is being driven by hard-to-find capabilities, a skills lens may be more predictive.

For compensation practitioners, this means asking not just “What is the job?” but also “What skills does the market value most in this job?”

Use ranges when level-specific data is too limited

A common challenge in salary surveys is that you may find good data for a job family, but not enough reliable observations at a specific level.

When that happens, it may be more practical to work from a broader market range rather than trying to force precision that the data does not support.

For example, instead of anchoring too tightly on one thinly populated level, you might review data across adjacent levels and build a reasonable range of market positioning. This can be especially helpful when your internal role sits between standard survey levels or when the organization uses broader career bands.

Using ranges allows you to recognize uncertainty without losing direction. It also supports better compensation decisions by keeping the conversation focused on reasonable market boundaries rather than false exactness.

If you take this approach, document why. Note the sample size limitations, explain which levels were considered, and show how you landed on the final range. That strengthens the credibility of your salary benchmarking process.

Check whether other survey providers have a suitable match

Not every organization participates in the same salary surveys. That means your best match may not always live in the survey source you use most often.

If you are struggling to find enough relevant data, it is worth asking whether another survey provider may have stronger participation for that role, industry, or geography. This is especially important for niche jobs, emerging roles, or positions concentrated in specific sectors.

Using multiple salary surveys can improve both match quality and confidence in the result. Even if one source does not solve the problem completely, it may provide useful context or validation. Though not always practical, textbook “best practice” is to rely on 2-3 salary surveys for any particular job.

The goal is not to shop for the answer you want. The goal is to expand the evidence base so your salary benchmarking reflects the market as accurately as possible.

Final thoughts

When there is no perfect job match in your salary surveys, you do not need a perfect answer to make a sound compensation decision. You need a consistent method, clear judgment, and a willingness to use the market data creatively but responsibly.

If you focus on core responsibilities, combine related jobs where appropriate, broaden your peer group thoughtfully, consider skills-based benchmarks, use ranges when level data is thin, and check other survey sources, you can still produce a strong salary benchmarking outcome.

In practice, compensation is rarely about finding a single perfect data point. More often, it is about building the best market view from the information available.

And when you document that process clearly, you give yourself and your stakeholders more confidence in the final pay decision.

Mercer’s first-in-class database is 2 times the size of our competitors’, including data representing over 20 million employees and almost 7,000 organizations in the US alone. We’re here to help you find the right data to meet your needs. Give us a call at 855-286-5302 or email at surveys@mercer.com.

About the author

Karen Rutledge, Commercial Strategist Mercer Products

Karen Rutledge is a Commercial Industry Strategist Manager for Career Products at Mercer. She works closely with clients in the Energy, Retail, and Consumer Goods industries to gain prospective on how to enhance future career products to align with each industry needs.