People & Leadership

What is people analytics? A guide for HR teams

What is people analytics and how can it help HR teams make better decisions? Learn how to get started and turn your people data into action.

You’ve got more data on your people than ever before, but are you using it to make decisions that actually move the needle?

This is where people analytics comes in handy.

Rather than relying on gut instinct or anecdotal evidence, people analytics gives you a way to spot patterns, predict outcomes, and make smarter choices.

Whether you’re hiring, managing performance, or trying to reduce turnover, this is how you can take action with confidence.

In this guide, you’ll learn what this type of analytics is, why it matters for medium-sized businesses, and how to build a practical strategy using the HR tools you already have.

We’ll cover the data you need, common challenges, and real-life examples to help you get started.

Here’s what we cover:

What is people analytics?

People analytics—sometimes called HR analytics or workforce analytics—is the process of gathering and analysing employee data to improve business decisions.

It covers everything from recruitment and retention to performance, wellbeing, diversity and more. The goal isn’t to just collect data, but to turn it into insights that help your business run better and support your people.

Think of it like this: rather than guessing why engagement has dropped in a certain team, you can look at survey results, absence patterns, and performance scores to find the real reason, and fix it fast.

Why people analytics matters for employers

For medium-sized businesses, resources are tight and every decision counts. People analytics helps you make more strategic, evidence-based choices across the employee lifecycle.

Here’s how it adds value:

• Spot problems early: if turnover is rising in a specific team, analytics can help you pinpoint the root cause, whether that’s workload, management style or pay disparities.
• Improve hiring decisions: by looking at the performance and retention rates of new hires, you can see which recruitment channels or interview practices lead to better long-term outcomes.
• Support diversity and inclusion: people data can highlight representation gaps, pay inequalities, or areas where inclusion could be improved.
• Boost retention: when you understand why people leave—and what keeps them—it’s much easier to build a culture where people want to stay.

David Green, managing partner of Insight222, stated on the McKinsey Talent podcast, “A really good people analytics function combines the broad view—the broad understanding of organisational research, the broad understanding that this is a field that’s been around for a while, and we know what motivates people—and then brings that to bear to highlight individual facts.”

How people analytics works

The process might sound technical, but it’s easier to get started than you think. At its core, people analytics follows a simple cycle:

1. Collect: gather data from your HR systems, surveys, performance reviews, absence logs, and more.
2. Clean: make sure the data is accurate, consistent and anonymised where needed.
3. Combine: bring different datasets together, for example, linking engagement results with absence patterns.
4. Analyse: use tools such as spreadsheets, dashboards or HR software to spot trends and correlations.
5. Act: turn those insights into actions, whether that’s a policy change, targeted support or a new hiring approach.

Even small tweaks can make a big difference.

For example, perhaps you’ve noticed that employees with certain onboarding experiences are more likely to stay beyond 12 months. That’s insight you can act on right away.

What HR data do you need?

The good news? You probably already have most of the data you need.

Key sources for people analytics include:

• Demographics: age, gender, location, tenure, department.
• Recruitment: time-to-hire, offer acceptance rates, sourcing channel success.
• Performance: ratings, promotions, training completion, goal tracking.
• Engagement: pulse surveys, eNPS (employee net promoter score), exit interviews.
• Absence and turnover: sickness rates, leave patterns, voluntary exits.

You don’t need to analyse everything at once. Just start with the metrics linked to your biggest business questions.

If you’re worried about burnout, look at overtime hours and sick leave. If you want to improve diversity in leadership, track promotion patterns across groups.

Always make sure your data complies with UK GDPR. That means handling it securely, being transparent about usage, and avoiding personally identifiable analysis unless absolutely necessary.

How to apply people analytics to your business

Data alone doesn’t drive change, what matters is how you use it.

Here are some practical people analytics use cases:

• Reducing turnover: if your exit interviews show that people leave because of unclear career progression, you can act on that insight by introducing internal mobility initiatives or mentoring programmes.
• Improving performance: analyse training data to see which development programmes actually lead to better results, and invest in what works.
• Supporting wellbeing: combine data from absence logs, workload trackers and engagement surveys to spot where wellbeing support is most needed.
• Enhancing talent acquisition: improve your hiring processes by clarifying the attributes of top performing talent and using the outcomes to guide searches for new employees.
• Guiding succession planning: use data to help you identify and develop employees to fill vital positions within the business when people leave their roles for new opportunities.

People analytics helps you move from reacting to problems to anticipating them. It supports more inclusive, fair and consistent decision-making—and it builds your credibility across the organisation.

Building a people analytics strategy

Creating a people analytics strategy doesn’t mean hiring a data scientist or buying enterprise-level software. It starts with being intentional.

Here’s how to get going (and if you’re looking for more inspiration, tools such as the CIPD’s People Analytics guide can help with practical templates and frameworks):

Know your goal

What are the biggest workforce challenges you want to solve?

Focus on one or two high-impact areas to start, such as reducing sickness absence or improving hiring quality.

Audit your data

List out what you’re already collecting and where it lives. Are there gaps? Are the sources reliable? Who owns them?

Choose your metrics

Decide on a handful of key performance indicators (KPIs) that will show whether your actions are working. Avoid vanity metrics and focus on what’s meaningful.

Get buy-in

Talk to stakeholders, such as line managers, finance, operations. Show them how people analytics can help them and their teams.

Start small, then scale up

Run a pilot project and share the results widely. Success stories will build support for broader adoption.

How HR software can help with people analytics

If you’re using modern HR software, chances are it already includes analytics tools, you just need to know where to look.

The best platforms make it easy to:

• Generate reports with built-in dashboards
• Track key metrics over time, such as absence trends or recruitment performance
• Customise visualisations to share with senior leaders or line managers
• Integrate with payroll, finance or performance tools to bring everything into one view.

HR software allows you to automate the heavy lifting—so no more fiddly spreadsheets or late-night reporting. You can track what matters and act faster, with confidence that your data is up to date.

Final thoughts

When you’re running a growing business, your people decisions matter, and with the right approach to data, you don’t have to rely on guesswork.

People analytics helps you see what’s really going on across your workforce—what’s working, what’s not, and where the biggest opportunities lie.

It’s all about bringing clarity to those questions that keep you up at night:

Why are people leaving?

How do we keep top talent?

Are we doing enough to support our managers? You don’t need a data science team to get started. You just need to start asking the right questions, and using the right tools to find the answers.