People analytics: a UK employer’s guide

Solving business problems is key to moving organisations forward. Detailed data about your employees, known as people analytics, can help the HR department to move beyond reporting what’s happened and towards looking at what decisions need to be made. 

That could mean things like understanding the reasons people leave, where there are skill gaps, if absence is affecting specific teams, or if a proposed workforce change could create risks that the company hasn’t even considered. The required data is often already available, but the challenge is knowing where to find it, what to measure, and how to turn it into something useful for the business.

People analytics is the process of gathering and analysing data about an organisation’s workforce, in order to generate insights and support better decision-making. The CIPD’s guidance on people analytics emphasises that analytics should connect people data with business data, help professionals to design targeted interventions, and measure the effectiveness of the people function.

For example, knowing that staff turnover is 17% informs you about what’s happening. But people analytics delves into why it’s happening, where it’s concentrated, what it’s costing the business, and what might change the outcome.

The terms people analytics and HR analytics can be used interchangeably, as there’s no universally agreed dividing line between the two. The CIPD uses people analytics, HR analytics, talent analytics, and workforce analytics as part of the same terminology. 

In real terms, HR analytics is normally used when describing analyses that are specifically focused on HR activity, while people analytics has an overall organisational focus.

For example, HR analytics might look into:

• Employee turnover.
• Recruitment.
• Pay and conditions.
• Absence.
• Training.
• Work performance.
• Employee engagement.

People analytics is able to answer broader business questions by combining those HR data analytics with further information from across the organisation.

Example

An HR Director knows that absence has increased in one of the business units, and HR analytics identifies the rate and frequency of these absences. In order to investigate the possible reasons for this rise in absence, the HR Director would apply a people analytics exercise combining absence information with things like employee survey responses, overtime, workload, team structure, and management data. 

When considering the 7 different areas of people analytics, the important thing is to identify which questions matter to the business and then establish which data can help to answer these queries. The CIPD’s practical guide recommends starting off by defining the business issue and considering what analysis will genuinely add value. There’s no point in analysing data just because it’s available.

While there isn’t one single authoritative definition of the seven pillars of people analytics, these areas provide a useful starting point:

1. Workforce data

Begin with the basic picture of your workforce, including headcount, tenure, department, location, employment type, working hours, turnover, and anything else relevant. This then establishes a baseline for everything else.

It can also provide the evidence needed for workforce planning, as HR can start identifying how and where the workforce is changing and if future capacity or capability could become an issue.

2. Recruitment

Your talent acquisition strategy data can reveal where the organisation is succeeding, and where it’s failing and losing potential employees.

Useful data to track is:

• Cost per hire.
• Time to hire.
• Time to fill.
• Offer acceptance rate.
• Source of hire.
• Recruitment funnel conversions.
• New-hire retention.

For example, if critical vacancies are open for months, people analytics may show that the organisation is losing candidates at the offer stage because of either salary, location, working arrangements, or the length of the approval process.

3. Retention and turnover

Turnover is one of the most commonly reported HR metrics, but a single percentage can hide important patterns. Break turnover down by factors such as department, role, location, tenure, manager, and the reason for leaving.

For example, a business that discovers its overall turnover is 11% might consider that as a manageable figure. But if 40% of employees in critical roles leave within 18 months, that’s a very different problem. The analysis should move from “How many people are leaving?” to “Who is leaving, when, and why?”.

That information also feeds into strategic workforce planning, particularly when the organisation needs to understand which skills and experience it could potentially lose over the coming years.

4. Absence and wellbeing

Absence is another area where people analytics can help identify patterns that are tricky to spot when looking at a case by case basis. Employers can examine absence rates by job type, team, location, duration, and frequency, with added employee feedback to provide context. The objective here is to understand if there are any organisational issues that need addressing through an absence management process.

It’s worth remembering that employee data can be sensitive. The Information Commissioner’s Office (ICO) says employers that use monitoring must comply with data protection laws and evaluate whether monitoring is necessary, proportionate, and transparent.

5. Performance and productivity

The use of people analytics can help HR leaders to investigate the relationship between workforce factors and business performance. The CIPD points out that people analytics uses data and information to provide insights into issues with staff, as well as to guide organisational decision-making. A useful approach is to ask whether teams with specific working conditions, management practices, skills, or levels of engagement have different performance outcomes.

6. Rewards, skills, and progression

Data on rewards and skills can reveal issues that aren’t necessarily available from headcount alone.

A business would do well to examine pay by role, tenure, and job level, along with promotion rates, training participation, and movement between roles. This is where job architecture comes into its own, as having a consistent role structure makes it much easier to compare jobs, understand progression, and identify patterns in reward.

Similarly, if employees are leaving in droves because they can’t see opportunities to progress up the career ladder, internal mobility data can help to establish whether the organisation is making enough use of its existing talent.

7. Employee experience

Employee experience data helps employers to really understand what their staff experience while working for the company. Surveys, employee voice channels, focus groups, and exit interviews can reveal issues that workforce numbers alone can’t explain.

If staff turnover is on the rise, for example, employee feedback is invaluable in helping to identify the cause – whether it’s the workload, the management, lack of career progression, or a toxic workplace culture. Analysing this information, along with retention, absence, and performance data, can give HR a more complete picture of what’s happening.

The important thing is to actually act on what employees are telling you. Collecting feedback, but then doing nothing about it, can undermine trust. People analytics should help organisations to measure employee experience, then identify where changes can make a meaningful difference.

One of the main reasons why organisations struggle with people analytics is that the information rarely sits neatly in one place.

Relevant data might be held in:

• HR information systems.
• The payroll and other finance systems.
• Employee surveys.
• Performance systems.
• Absence systems.
• Learning platforms.
• Workforce planning spreadsheets.
• External salary or labour-market data.

The key is understanding how data can be used to answer organisational questions. That doesn’t necessarily mean you have to invest in new software. As an alternative, create a data map covering what you  have, where it is, who owns it, how often it’s updated, and how reliable it is.

Building a business case for people analytics normally starts with a business problem. For example, “Valued employees are leaving quicker than can be replaced. We want to understand why this is and identify what interventions we can take to improve staff retention.”

The business case show how people analytics can help resolve the issue, in terms of:

• The problem: what’s happening?
• The evidence: what does available data tell us?
• The impact: what will this cost?
• The decision: what can we do differently?
• The measure: how will we know if it’s worked?

This approach gives people analytics a clear commercial purpose. It also helps HR to hold increasingly meaningful conversations with senior leaders to explain what the data means for cost, capability, productivity, risk, or organisational capacity.

It’s true to say that most organisations will have gaps in their people analytics data – reasons for leaving may have been recorded differently by different HR teams, older employee records may be incomplete, or important information may be languishing in long-forgotten spreadsheets.

However, that shouldn’t stop the analysis. Instead, document the limitations and begin by improving the data that matters the most.

For example, if an organisation wants to get to grips with turnover, it needs to agree on a single definition of voluntary turnover and standardise how reasons for leaving are recorded. It follows that the next analysis will be more reliable than the last. 

Not necessarily. Excel or existing reporting systems may be enough for straightforward questions and small datasets. As businesses become more data-intensive, specialist HR analytics software can make it easier to combine datasets, automate reporting, and visualise trends, but the technology should follow the business question rather than become the objective.

People analytics is worth it when it changes or challenges a decision. It can help an employer to distinguish between a general retention problem and a problem concentrated in one critical skill group, for example. Or it can show if absence is spread evenly across an organisation or specific to one particular team. It can help identify if employees are leaving because they can’t see a clear career path or whether the organisation already has the internal talent to fill some of its vacancies.

A useful example of what HR leaders wish they knew comes from Careerminds research in the US, which found that 30.9% of HR respondents said their organisations had lost critical skills and expertise through AI-related layoffs. This is exactly why people analytics is commercially important, as it can help leaders to see the workforce consequences of a decision before those consequences become too expensive to reverse.

For organisations going through workforce change, this also creates a natural connection between workforce data and career transition support. When decisions about roles are made, the organisation still has a responsibility to manage the human impact effectively. Careerminds boasts a 95% placement rate for its participants, providing an example of how structured outplacement support can help affected employees move towards their next opportunity.

You probably already have more workforce data than you realise. The organisations that get the most from their people data won’t necessarily be the ones with the most sophisticated systems, but the ones willing to use evidence to challenge assumptions and make better decisions.