Making people decisions based on gut feeling is no longer enough. With HR data analytics, you can predict which employees might leave, spot high performers early, and show exactly how HR adds to profit.
Companies that use HR analytics have structured processes for managing employee performance, recruitment and retention. This ultimately leads to more predictable results on employee churn, onboarding, and productivity.
A lot of HR analytics is still very manual and Excel-driven. However, there is a big potential for automation in HR analytics.
In this article, we will share multiple case studies and discuss the primary KPIs for HR analytics.
If you’re looking to achieve more with your HR data, our data analytics consultancy is here for you. But first, let’s break down how it all works in this article.
HR data analytics is the process of using data to inform hiring, promotion, training and management decisions within your organisation. Instead of guessing, you use facts, numbers, and patterns to know what’s happening and what needs to change in your business.
Once you start looking at your people data differently, you’ll start to see patterns you’ve been missing for years. HR analytics helps you make sense of the daily decisions that shape performance and culture, and cuts costs in the following ways:
HR Analytics lets you see the departments and teams with high turnover and address them on a case-by-case basis. With the help of this, you can also see how many years of service your employees leave after.
Understand the data so that you can hire easily on channels that bring the best candidates at the most reasonable cost.
HR analytics helps to identify productivity killers and measure the productivity of every team member, which in turn helps to increase it over time.
Analysing the data on employee skills helps to identify skill gaps and plan for training programs.
You may think that there is no bias in your hiring, but perhaps it is just not obvious? HR analytics helps to determine if any ethnicities, age groups or genders are underrepresented on every seniority level in every department.
At Vidi Corp, we have developed multiple HR Analytics solutions for our clients.
We built this dashboard to help a recruitment company figure out which talent source channels are actually worth their time and money.
It shows how many applicants came from each source and the cost involved at every stage of the hiring process, from when applications were received to interviews and finally to placements.
This helps in identifying the most cost-effective sources of hire.
The dashboard also helps assess the quality of each source by highlighting those that resulted in actual hires or yielded the best return on investment.
Armed with these insights, the company will now be able to make well-informed decisions as to which channels they ought to be focusing on.
In a different project, we created a Power BI HR dashboard for a manufacturing company. This dashboard helped the HR team to track the main KPIs:
Attrition can be analysed in more detail by looking at the number of resignations per departments and designation.
It is also important to collect the data on self-reported reason for resignation so that those reasons can be adressed by the management.
Finally, it is useful to track the number of people leaving and joining each month (as you can see on the table in the top right). This analysis helps to understand the length of time between an employee leaving and a replacement being found.
Analysing leave is also very important. If little leave is taken by an employee in a large organisation, this may point to a employment fraud where a fake employee is registered and the salary is paid every month. On the other hand, too much leave in a department may slow down their progress towards meeting their KPI.
We helped our client to analyse % of times that employees were on leave or absent in every department. We also analysed the reasons for leave e.g. annual leave, emergency leave, etc.
The dashboard is fully interactive so if you click on a department, you can filter all the other visuals and see what are the most common leave reasons for this specific department.
Analysing overtime is important because it is an extra expense on top of the salaries. As a result, creating reports to track overtime is essential to ensure that the overtime does not exceed the budget.
We helped our client analyse the number of overtime hours per location and business unit. This helps the client to understand where in the business they need additional capacity. This analysis informs hiring and recruitment decisions in each location and business unit.
Finally, it is important to track overtime per month to ensure that the extra expenses for overtime are still under control. Ideally, as the organisation hires more full time employees, the overtime would decrease.
For this dashboard, we worked with the HR team of our client in creating a workforce composition report that was delivered to the senior management.
The report provides readers with an overview of the workforce structure by job role, department, and tenure group.
We calculated metrics like job satisfaction and work-life balance scores from the responses to the employee surveys.
While attrition rate was based on how many roles have remained vacant or experienced high turnover over the years.
Users interact with the dashboard by clicking on any job role and looking at its average satisfaction and work-life balance scores, giving them a bigger focus on what is happening within each team.
Much like the latter, this HR dashboard provides insights into the workforce composition of another one of our clients. It classifies their workforce by role, designation, grade, and management level, providing a quick view of how talent is distributed across the different layers of their organisational structure.
Many conversations are taking place about what the healthy proportion of junior to senior roles should be. So, HR often needs dashboards like the one above to balance the ratio of senior to junior roles for efficiency, better team structure, and long-term planning.
We worked with the HR manager of a lawn care company to analyse the productivity of the technicians. This involved tracking metrics such as the:
Before we stepped in, the HR manager was spending around 15 hours every week just trying to understand how productive her technicians were. She had to pull data from different systems, clean it up, and manually piece it together.
After we built the dashboard, it dropped to just 2 hours. So, not only did she track technician productivity better, she became more productive herself.
Another client wanted to grasp how their team’s time was being used, so we built a dashboard that helps them track billable versus unbillable hours.
Billable means hours spent on client or paid projects, whereas unbillable time covers everything else, like admin, training, meetings, sales, etc.
The dashboard tells them how many hours are logged in total each month, how many of those are billed, and how those hours are sliced across departments and individuals. They get a clear view of where time is spent, who’s overstretched, and where they stand to improve. This has helped the team with better planning, reducing hours wasted, and channelling focus on revenue-generating work.
We worked with a recruitment company in the UK that ran a DEI survey among marketing professionals, asking about their seniority level, age, gender, sexual orientation, and more. We then analysed this data to uncover DEI trends and patterns across the UK marketing industry.
Our client later ran a similar survey for a large UK bank and added that data as a “comparison group.” This allowed the bank to measure its DEI performance against other marketing departments in the country.
The analysis revealed several hidden biases:
With this insight, the bank was able to raise these issues with its hiring team to reduce future bias.
You can read more about this analysis here.
Depending on the data available to you, there are several key performance indicators (KPIs) that you can and should track when dealing with HR Analytics. We have already touched on a handful of them in the case studies above, but let’s break them down here properly:
Every HR professional knows hiring takes time, costs money, and carries the risk of bringing in someone who isn’t the right fit. These metrics will help analyse and improve the hiring process over time:
Companies want to retain top talent, and these metrics give insight into what makes them stay or leave:
Training is expensive, so you should know if it will develop the team or enhance their performance. These metrics help in checking that:
These help in determining how productive your team really is, and you may use such metrics to enhance output without burnout:
Companies use diversity metrics to check if their teams are balanced and inclusive:
You already have valuable HR data. It lives in the systems you use every day. The key is knowing where to look and how to connect it. This is a breakdown of where your most useful people data may come from and what each one can tell you:
The system is the core people system of the organisation. It contains job history, roles, departments, and employment changes. It is usually the basis for a lot of HR analytics.
Your ATS tells you how candidates proceed through your hiring process. Use it to find bottlenecks, strong sources, and qualities of a good hire.
They assist you in setting goals and measuring results, ratings, and feedback from parties involved in the process. They show the performance and growth of individuals and teams over time.
Find out who is learning what, when, and whether or not training helps. Using this data, an LMS correlates training with actual skill-building and job performance.
Survey tools provide a pulse for how employees are feeling. Proceed with the results to fix issues in their early stages.
Your pay data helps you analyse equity, pay gaps, and overall spend. It’s also useful for spotting patterns tied to performance or attrition.
See how much time people spend at work, how often they miss days, and whether patterns link to burnout, stress, or low morale.
When someone leaves your organisation, there is always a reason. Use this exit data to find themes, understand what went wrong, and prevent repeat issues.
HR analytics isn’t plug-and-play. You’ll run into a few bumps along the way, but each one has a solution that works.
Gut feelings don’t cut it anymore. If you want to make smarter people decisions and show how HR drives business results, it’s time to put your data to work. At Vidi Corp, we help HR teams move from guesswork to insights with less effort and bottlenecks. Reach out to us and let’s get started.
You define a goal, collect the right data, and use tools to find patterns that guide action.
Turnover analysis, hiring efficiency, and linking training to performance.
Stepwise conversion of HR data to insights and actions. It involves collecting, analysing, and interpreting human resources data to make better people decisions.
HR analytics is concerned with people data, whereas data analytics applies to any kind of data.
