It goes by many names: HR analytics, people analytics, workforce analytics...
Regardless of the name used, it has become one of the most important pathways to organizational success. But what is HR analytics, why is it important, and how do you do it?
What is HR analytics? And why is it important?
HR analytics is the study of employee data. It helps leaders make decisions based on data, for the best possible outcomes.
It can be used for a huge range of beneficial purposes in an organization: to better understand people and performance, measure attrition and turnover, and understand how things like time to hire and retention rate impact business performance.
HR analytics can tell a company if they have problems with hiring, diversity, high turnover, and other issues that can impact productivity and profitability.
It can help maximize revenue, minimize expenses, and mitigate risks, by implementing goal-oriented workforce strategies.
Today, HR analytics is vital to organizational success. It can improve hiring, retention, and widen the talent pool.
Most importantly, it can empower the people who make a business what it is – and it all stems from a core truth, one that the best companies in the world have known all along: what’s good for employees is good for the company.
What metrics does HR analytics measure?
HR analytics tools and dashboards can be used to quantify almost everything about your employees, at a granular level. An abundance of data sounds good, and it usually is – but only if you know what you want from it, or can give your business value with it.
These are some of the most important metrics in HR analytics:
1. Revenue per employee
This is one of the big, easy metrics that leaders want to know: is their investment in people paying off? Revenue per head is simple to find – just divide the company’s revenue by the total number of employees:
$70,000,000 annual turnover ÷ 500 avg. employees = $140,000 revenue per employee.
Yes, it’s overly-simplistic, but it’s the one everyone wants to know. It can help set salaries, manage and forecast company expenditure, and gives an indicator of company performance.
2. Expenses per employee
This isn’t just salaries – it’s training budgets, equipment, software, resources – everything your company has to spend in order for their people to be able to do their jobs. In the services sector and knowledge industries, where there are few other expenses, this is usually the largest portion of company spending.
3. Time to fill and time to hire
Time to fill is the number of days it takes to fill a vacant role from posting a job. Time to hire is how long it takes a candidate to accept an offer after they’ve been approached. These are both important metrics, because they determine recruitment strategy and can help improve the candidate experience.
4. Offer acceptance rate
How many people have accepted a position at the company versus the number of offers given. If the offer acceptance rate is low, it can be a sign of uncompetitive compensation, lackluster benefits – or a deeper problem in your organization, like diversity or perceived company culture. The good news is that these factors can also be analyzed with HR analytics, too.
5. Attrition rate and turnover
Attrition occurs when employees voluntarily choose to leave their jobs. The rate is calculated by dividing the number of employees who left voluntarily by the average number of employees in the organization over a given period.
It can be a sign of job dissatisfaction, poor progression, wage stagnation, changes to workloads or the working environment – or simply down to personal reasons. Reliable feedback data is required to understand this fully.
A high rate of involuntary turnover can be a sign of poor hiring decisions, prompting recruitment processes to be reevaluated.
6. Diversity, Equity, Inclusivity (DEI)
Innovation suffers without diversity. Progress and profitability become stifled when only a narrow set of ideas, experiences, and voices are represented. HR analytics can help avoid this by tracking DEI and setting benchmarks for hiring diverse talent.
It can also help companies offer better and more competitive pay and equity, identify bias, and move towards a more inclusive, representative workplace.
Questions you can answer with HR analytics
With HR analytics, you can answer questions like:
- Why is turnover so much higher in certain branches?
- Why are top performers leaving at a higher rate than others?
- How does employee engagement differ by age, ethnicity, and gender?
- What attributes do our most effective managers share?
- Why do new hires leave within the first few months?
- Is turnover higher among female employees?
- Should we hire more candidates with college degrees?
- What’s the relationship between employee engagement and performance?
- Is there a gap in engagement between remote employees and on-site employees?
- How do we identify employees suitable for promotion?
HR analytics, used properly, can answer just about any question you have about your workforce. Any attribute, any outcome, any hypothesis – HR analytics can help formulate tests and measure results. But you cannot answer any of these without data; clean, reliable data.
How to Get Started With HR Analytics
To get started with HR analytics, you’ll need tools, data analysts, and goals you want to achieve. We’ll leave the goals and staffing up to you – but HR analytics tools are ten a penny. Cutting through that noise can be tough.
For the end result, though, you’ll want to have clear, easy to understand HR dashboards: a way to visualize data. In the early stages, this is a simple and effective solution – a quick overview of the most important metrics that impact your company.
Later down the process, you may want deeper insight and more granularity; or a system that can predict outcomes. Advanced machine learning can do things like analyse large quantities of employee data, check for LinkedIn changes, and connect behavioural changes to identify flight risk.
That’s pretty heavy stuff. But some systems (like ours) make even the most complex HR analytics processes simple.
Collecting data with HR analytics tools: top software for HR analytics
There are so many HR tools, HRIS tools, recruitment tools, and benchmarking tools on the market – way too many to list! But here are some of the top-rated, most widely used platforms for collecting HR analytics data.
Workday offers a suite of HCM, finance, talent management and employee insight tools.
Gusto is primarily a payroll and benefits platform, but it has HR tools built-in, too.
Applicant tracking and onboarding tool Greenhouse is a hiring intelligence platform.
SmartRecruiters is a talent acquisition tool with AI recruitment and applicant tracking.
Data requirements for HR analytics
Data needs to be collected and stored at each stage in the employee lifecycle, from recruitment to exit interview.
This can be a challenge – because different tools collect different types of data, and combining disparate data sets can give spurious results.
But here’s what we need in all cases:
- Employee data, like performance reviews, salary, and demographics
- Company financial data
- Performance, product, or services data
- Employee feedback data
- External data – benchmarking your company against others
Mashing all this data together can be difficult, and data cleanliness can suffer as a result. This can lead to improper decision-making or obvious errors that take time and research to resolve.
Even slight discrepancies can seriously undermine the trustworthiness of your data.
The quality of the data you have is just as important as the quantity; if the data’s junk, it makes no difference if you have a ton of it.
If the data’s pristine, but there’s hardly any of it, you don’t have enough representation to make a call.
Whatever you want to measure, setting good practice for data collection and collation is priority number one in HR analytics.
And that’s just one of the areas where eqtble excels.