Do you want to start using people analytics in your business, but you are unsure how to go about it and what the real benefits will be? This guide will explain the whole process step by step.
HR managers are sitting on a goldmine – even if they do not always realize it. All the data they collect throughout an employee’s lifecycle in the company can be business-relevant and help management make informed decisions. The biggest challenge is turning that raw data into meaningful insights. That’s exactly what people analytics is for. But how to start people analytics?
People analytics – often called HR analytics or workforce analytics in practice – can be defined as collecting and processing employee-related data to improve business outcomes. In other words, people analytics uses metrics about your workforce to tell meaningful stories that can impact your business. It gives your business a strategic direction based on evidence, rather than guesswork and intuition.
One of the ways to do that is by using dedicated tools, such as the Human Panel HR management platform. Its easy-to-use interface, visualized statistics, and automated reports make people analytics accessible to everyone – not just analysts. If you want to test this solution, sign up for a free demo and see how it can hel your business.
Reduce guesswork. Prove HR impact on revenue.
Why people analytics?
You might be wondering what the real benefits of people analytics are, and it’s a fair question to ask. Your colleagues at HR could say it adds value to your business, but what does that mean exactly? What is the true, unique value proposition of people analytics? What tangible insights can it deliver?
Let us take a look at some of the benefits that people analytics can provide:
- Better employee retention and lower turnover.
- Identification of the best sources for quality candidates.
- Better structuring of your onboarding process to reduce time to productivity.
- Increase in the efficiency of your recruiting funnel.
- Achieving fair compensation.
- Optimizing training models and assessing employee learning capabilities.
- Increasing diversity within the organization.
- Facilitating succession planning
- Improving productivity
Crucially, people analytics is a tool that helps achieve the desired outcomes, not the solution itself. Context is everything. There is no magic formula that will solve each of your company’s problems. HR metrics will give you answers – but you need to ask the right questions first. If you adopt a question-based mindset, you’ll be on the right track to working with data in HR.
Here’s how to do it – step by step.
Step 1: Identify the challenge
To begin your people analytics journey, you need to understand what business problem you are trying to solve. Is it a high turnover rate? The rising cost of recruitment? Or perhaps declining employee satisfaction?
“These challenges should be identified in a conversation with the business leaders, the owners or other stakeholders, depending on the size of the business,” says Mateusz Karpiński, HR Business Partner and people analytics expert.
A manager of Team X says, “My employees are leaving the company. I cannot deliver the expected results because the turnover rate is too high and I cannot replace those who leave with new employees.”
That can be the starting point for a discussion. Now, you should think about why this issue is important and what impact it has on your business. You should ask some follow-up questions:
- How does this problem affect the team’s performance?
- What results would you like to achieve?
- How are these outcomes likely to impact the organization?
- Who will be affected by these outcomes?
Step 2: Review the data sources
Once you have identified the problem, ask yourself what kind of data you have to illustrate it and where you can find it. Data sources may include:
- Employee demographic data.
- Data on position, seniority, compensation, tenure, time since last promotion, learning and development opportunities, etc.
- Employee satisfaction surveys.
- Feedback from one-on-one interviews and exit interviews.
- Insights from leaders and managers.
If you are missing a relevant piece of information, consider how to gather it. Can you ask other stakeholders and check if they have any relevant data? Do you need to conduct another survey or hold another meeting with the team? Fill in some gaps in basic demographic information? What other type of data might be useful in this situation?
Step 3: Gather the data
Once you know what your data points are, you can collect and organize them in one place. This way, you start building a database that will be a pillar for your data ecosystem. You can start by organizing the information in a simple spreadsheet, or you can opt for one of the specialized workforce analytics tools.
Remember that “data” does not just mean raw numbers, metrics like payroll and NPS. A conversation with the employee about their performance is also an important source of data. The same goes for insights from managers and employees.
Step 4: Clean the data
The next step is data cleansing. In this phase, you need to sort your information and remove the data points that are not relevant or of insufficient quality. You should remove any incorrect or inconsistent data as well as extreme outliers.
For your employee satisfaction survey, you use the employee ID as the identification point. For exit interviews, you use first and last names, making it difficult to compare. How do you determine who is who? Cleaning the data means you always use the same identification metric.
Another issue is how you collect the data. Sometimes you use Google Sheets, other times it could be e-mail or a dedicated survey platform. In each of these cases, the data may come in different formats, and even different date formats can cause unwanted chaos.
Step 5: Analysis
To perform an insightful data analysis, break it down into smaller steps.
Defining the objective
Focus on the goal you want to achieve and the question you want to answer. Analyze only the data that is truly relevant to your investigation.
For example, if you are investigating why employees leave Team X, you can exclude those who retire from your analysis.
Descriptive analysis answers the question “what happened”. It is a retrospective analysis that reports on past events and serves as the first level of your investigation.
Descriptive analysis shows you a synthesis of raw HR metrics such as:
- How many people left Team X in July.
- What position these people held in the company.
- What age they were.
- How much they earned.
- Who their supervisor was.
- What learning and development opportunities they took advantage of.
- How long it has been since they were last promoted.
- What their performance was.
It is important to understand that this is only the first level of data. To run a thorough analysis, you will need to add information about the employees who have left the company. The sources for this can be surveys, polls, and exit interviews. This kind of information can deepen your knowledge and answer the following questions:
- What were the reasons employees gave for leaving?
- How high was their level of engagement and satisfaction?
- What kind of feedback did they give about the company?
- How did they rate their managers?
- Where did they leave the company?
These questions are not exhaustive, but they highlight the mindset you should have. The key is to keep digging deeper and asking “why”. That way, you have a chance to get to the root of the problem.
Now it’s time to correlate the data. Diagnostic analysis shows you the relationships between the data and answers questions like:
- What is the turnover in Team X related to? Is it related to gender, age, position, compensation, time since last promotion, or the change of a leader?
- How does it look on the timeline – is it related to changes in the way you work (remote/hybrid) or are external factors involved, such as intense recruiting by your competitors?
- How did the employees who left you respond in surveys and interviews? Were there any leading indicators of their dissatisfaction?
Again, this is by no means an exhaustive list, but it will give you a general idea of what to expect from a diagnostic analysis.
Predictive analysis uses known data to answer the question “what will happen” – making predictions about future events. It is primarily used in planning, but can also help predict who is most likely to leave your company. Using algorithms and machine learning, it shows you who is at risk and which areas you should address first.
Step 6: Evaluation
Before you start turning your insights into actions, you need to evaluate them and decide which ones are most relevant and which ones may be just “noise.” Are there any surprises? Or has your hypothesis just been confirmed? Do you see the need for additional analysis?
It’s also a good moment to structure and organize your conclusions to get ready to present them to the key stakeholders.
Step 7: Communication
Translating the insights and explaining their meaning is an important step – you need to decide who should be told about your key findings and why they are important to the business.
“Hard facts rather than assumptions pave the way for a data-driven conversation with key stakeholders and elevate the position of HR. You can say, ‘I know the root cause of the problem and how we can solve it. I am not experimenting to see if something works, I have numbers to back up what I am doing,’” Mateusz Karpiński comments.
Step 8: Take action
Once you have the insights and have explained them to your executives, you can take action and come up with an intervention strategy. Then, it’s also important to monitor these strategies and see if they are producing the desired results. What impact are they having? Is the change visible? Are there areas where you are not having success? And why?
Tools to start people analytics
You do not have to be an analyst to start people analytics in your organization. Building the analytics team in HR is a process, and many companies started with teams that consisted of a single person.
Of course, the ability to read data is highly desirable – but with a platform Human Panel provides, you can automatically generate reports and visualize data in a user-friendly way that’s accessible to everyone.
With dedicated software, you can automate many of your HR processes and spread the knowledge throughout your organization. You may eventually want to build an HR analytics team – learn more about how to do that here.
Do not be daunted by the amount of work you need to do – a proper people analytics project is a process that can take years, but the sooner you start the better.
If you want to see how it works, subscribe to our demo – it’s an entirely free and non-binding opportunity to watch people analytics in action.
Reduce guesswork. Prove HR impact on revenue.
HR is a vital area for any business. It has a real impact on revenue and should be based on data – rather than biased opinions and assumptions. In this way, HR can take its place at the executive table and contribute meaningfully to the profitability of the business.
People analytics is one way to do this. It can elevate the role of HR and protect the greatest asset of any business – human resources. It helps you get rid of emotions and “gut feelings”, and allows you to make informed decisions and standardize all your HR processes.
To get started, you do not need special skills, complicated formulas or sophisticated tools. What matters is a mindset based on questions. This is not an empty promise – if you embark on this journey, you will see the results quite quickly, and they will be impressive.