How benchmark data works in the People Insight Platform

A quick insight: Benchmark data helps you understand how your survey results compare with relevant external norms, giving your organisation clearer context for what strong, typical or lower results look like. In the People Insight Platform, benchmark data supports sharper listening by helping you interpret results more accurately, and smarter action by helping you focus on the areas most likely to make a difference.

Benchmark data is one of the most useful tools available when you are trying to make sense of employee survey results.

A score on its own can only tell you so much. It might tell you that engagement is 72%, or that confidence in leadership is 58%, but without context, it is much harder to know what those figures really mean.

In the People Insight Platform, our global benchmark data helps organisations compare their results with relevant reference points across sectors, demographics, regions and other groupings. It adds context, helps highlight relative strengths and weaknesses and makes it easier to focus on the areas most likely to benefit from action.

Employee listening becomes sharper when results are interpreted in context rather than in isolation. Action becomes smarter when leaders can see not just what their scores are, but how those scores compare and where attention is most needed.

In this guide, let’s take a look at what benchmark data is, why it’s so important and how it works within the People Insight survey platform.

Related: People data in the age of AI: faster analysis, better decisions?

What is benchmark data?

Benchmark data is reference data that allows you to compare your survey results with results from other relevant groups.

In employee surveys, that usually means comparing your scores against broader norms such as:

• sector averages
• country or regional averages
• demographic groups
• organisation size
• role or job family norms

In simple terms, benchmark data helps answer a very practical question:

How do our results compare with others like us?

That context is especially useful when you are trying to decide whether a score is:

• a genuine strength
• an area of relative concern
• typical for your sector or workforce
• improving in a meaningful way over time

Why does benchmark data matter?

Survey results are much more useful when they are placed in context.

Without benchmark data, organisations can end up overreacting to scores that are actually fairly typical, or overlooking scores that are low relative to their sector or workforce. Benchmarking helps leaders interpret results more confidently and make better decisions about where to focus.

It also helps organisations:

• understand how they compare with peers
• identify relative strengths and development areas
• set more realistic goals
• prioritise action more effectively
• explain results more clearly to stakeholders

Benchmark data is most useful when it helps you move from raw scores to clearer priorities.

How benchmark data works in the People Insight Platform

In the People Insight Platform, benchmark data is designed to help users interpret survey results more clearly and compare them against relevant external norms.

That means benchmark data can support analysis in several ways:

• adding context to top-line scores
• helping leaders compare results across sectors or demographics
• showing where one group’s experience differs from a broader norm
• helping managers understand whether a result is unusually strong or weak
• supporting clearer conversations about priorities and action

Compare your organisation with others in your sector

One of the most common uses of benchmark data is sector comparison.

This helps organisations understand how their employees’ experience compares with others in the same or similar sectors. That could include comparisons around:

• Employee engagement
• leadership
• communication
• benefits
• career development
• Organisational culture

Sector benchmark data is particularly useful because employee expectations often differ by industry. A score that looks positive in one sector may be less competitive in another. Comparing your results with sector norms gives you a stronger sense of what employees are likely to expect and where you may have room to improve.

Use benchmark data to understand demographic differences

Benchmark data is also useful when looking at how different groups experience the workplace.

For example, demographic benchmarking can help organisations explore whether experiences differ by:

• gender
• age
• location
• level or seniority
• function or team

Overall averages do not always show where experience is uneven. Benchmark data adds another layer by helping organisations understand not only that groups differ internally, but also how those group scores compare with broader external norms.

This can be especially useful when exploring themes such as inclusion, belonging and fairness alongside diversity and inclusion work.

Compare by country or location

Many of our clients operate across multiple regions or countries. When this is the case, benchmark data can also support location-based interpretation.

This is especially helpful for global organisations that want to understand whether lower or higher scores reflect something specific to their local environment, a wider trend in the region or a pattern unique to the organisation itself.

Location-based benchmark data helps leaders ask better questions, such as:

• Is this issue consistent across all locations?
• Are expectations different in this region?
• Is this result lower than local norms, or broadly in line with them?
• Where should we focus first?

Benchmark data supports sharper listening

Benchmark data is a strong example of Sharper listening. Smarter action. in practice.

It supports sharper listening because it helps organisations interpret results more accurately. Instead of looking at scores in isolation, leaders can understand them in relation to sector, geography, demographics and relevant norms.

That makes it easier to:

• avoid shallow interpretation
• spot meaningful differences
• ask better follow-up questions
• understand where context matters most

This is also where benchmark data becomes more valuable when paired with employee listening more broadly, rather than being used as a standalone comparison tool.

Benchmark data supports smarter action

Benchmark data also supports smarter action.

Once leaders understand where scores are strong, typical or under pressure relative to useful comparison groups, they are in a much better position to decide where action is needed most.

That means benchmark data can help organisations:

• prioritise areas with the biggest relative gaps
• avoid wasting effort on the wrong issues
• explain priorities more clearly to stakeholders
• track whether progress is meaningful over time

This is where benchmark data works particularly well alongside post-survey action plan activity, because it helps leaders decide which issues need attention first.

How Prism and benchmark data work together

Benchmark data helps you understand how results compare externally. Prism helps you understand what those results mean in practice.

Together, they support a stronger interpretation process:

• benchmark data adds context
• Prism helps identify patterns and likely priorities
• leaders and managers can then focus action more clearly

Prism can help surface what looks most important in the data, while benchmark data helps show how those results sit in relation to broader norms. That creates a clearer route from measurement to meaningful action.

What benchmark data should not be used for

Benchmark data is valuable, but it should be used carefully.

It should not be treated as:

• the only measure that matters
• a reason to ignore your organisation’s specific context
• a substitute for employee comments or deeper analysis
• a competition table
• proof that one issue automatically matters more than another

A score being below benchmark does not always mean it is your top priority. Equally, a score being above benchmark does not always mean it can be ignored. Benchmark data is most useful when it supports interpretation, not when it replaces judgement.

That is why it should be considered alongside survey comments, segmentation and practical discussion with leaders and managers.

What good use of benchmark data looks like

A strong approach to benchmark data usually looks like this:

• results are reviewed in context, not in isolation
• comparisons are made against relevant groups
• benchmark gaps are explored, not assumed
• benchmark context is combined with comments and segmentation
• leaders use the insight to focus action realistically
• progress is reviewed over time

This is where benchmark data becomes most useful: not as a static comparison, but as part of a wider decision-making process.

How benchmark data fits into a wider survey process

Benchmark data works best when it sits inside a broader employee listening process.

That broader process usually includes:

• designing the right survey
• collecting useful feedback
• interpreting results clearly
• comparing results in context
• turning insight into action
• reviewing progress over time

In that sense, benchmark data is not a separate extra. It is part of how organisations make better use of employee survey results overall.

Improve interpretation with benchmark data in the People Insight Platform

Benchmark data helps organisations understand survey results more clearly by adding context, comparison and perspective.

In the People Insight Platform, it supports sharper listening by helping leaders understand how results compare with relevant norms. It supports smarter action by helping organisations focus on the issues most likely to make a meaningful difference.

Combined with Prism, segmentation and clear reporting, benchmark data becomes a practical tool for better decisions rather than just a point of comparison.

Want to see how benchmark data works in the People Insight Platform? Talk to us to learn how we help organisations compare results meaningfully and turn insight into smarter action.