As adoption of analytics is increasing and interest is soaring, more and more companies are looking for ways to get started with HR analytics. In this article, I will give you a practical guide on how to get started with HR analytics in 5 steps.
The steps needed to get started with HR analytics are:
- Identifying business problems
- Identifying the quick wins
- Selecting relevant data
- Analyzing data
- Interpretation and execution
Let’s start with the first step.
1. Identifying business problems
The golden rule for people analytics – and for any other improvement – is to start with a business problem. Solving a problem always adds value and creates buy-in from relevant stakeholders.
People analytics is defined as the systematic identification and quantification of people drivers of business outcomes. Analytics can thus help you answer questions like: How can we improve our financial performance or how can we drive sales through smarter people decisions?
A side note: Business problems are problems for the business, not problems for HR. Where HR is often focused on optimizing its own processes, business problems are related to the key performance indicators of the organization. Where HR will be busy improving engagement, the business will be busy improving the sales performance of account managers. Only the latter is a business problem.
Tip: Talk to line managers, senior management, and business partner and list the challenges they are seeing. Identify which problems are business problem and which ones are HR or other problems. Only focus on the business problems.
2. Identifying quick wins
With your list of business problems, it’s time to make the next step. Not all business problems are equal. The first step is to rank the business problems on their importance. We want to start with the most important business problems first as solving them will add the most value to the organization.
The second step is to identify the HR contribution to these problems.
For example, your organization is looking to build a new factory in a low-wage region. What’s the HR contribution here? In this example, there are multiple personnel challenges that HR can help with. To expand successfully, qualified personnel needs to be present, available, and sufficiently cheap.
Only when these three criteria are met, will the company have a chance to expand successfully. This is very much a human resources problem that can be solved by leveraging data.
Or when sales are decreasing, HR can contribute by building sales competencies through L&D, making a better selection for salespeople, or through numerous other activities. These interventions can be invented based on company and domain knowledge and on the relevant people drivers that have been identified in the scientific literature.
Defining the added value of HR to the business outcome helps you to estimate how easy it will be to analyze data and actually add this value. This is the second key element as it helps to identify the problems that have the most impact and are easiest to solve.
Tip: Rank the problems on impact and how easy it is for HR to solve these problems. You want to first focus on a high-impact problem that is relatively easy to solve.
3. Selecting relevant data
Now you have your initial problem selected, you should take a look at the relevant data. Ideally, you will want to include the accessibility of data in your judgment in the previous step. If there is no data available, the problem is, by definition, hard(er) to solve.
Traditionally, HR has been excellent in keeping records. The accuracy of these records is debatable, but that problem is not limited to HR data.
There are a few options in this phase. First, all the data is already present. In this best-case scenario, you will need to check and clean the data and you’re ready for analysis. If the data is only partially present, you will need to collect the data yourself. This is more cumbersome as you will need to collect the data manually.
As your HR analytics capabilities mature, data will become more available as data-collection methods are improving. A good way to plan this is through the implementation of smarter software throughout the different phases of the talent journey.
Tip: Try to focus primarily on data than you already have. If you don’t have data available, limit your analytics project to a smaller group of key employees. This enables you to get to the data analytics phase faster and implement results quicker for the group that has the biggest impact.
4. Analyzing data
The data analysis is a complicated step as it requires statistical expertise. Some analysts have studied years of statistics in order to analyze data
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Not all data needs to be analyzed by a data scientist, however. Sometimes data is much more readily available or there are simpler analyses that add just as much value. In the case described above, you can get labor market statistics at recruitment consultancies that are specialized in those geographical areas. This means that you can skip most of the actual analysis.
For internal data, you can work with a data expert – but this person doesn’t need to work in HR. Many companies that are getting started with analytics work with an analyst from finance or marketing. These people have the same skills and can give you the answers you’re looking for with the right guidance of a domain expert.
Hiring a full-time data scientist in HR has always been a bit of a controversial topic. Oftentimes, the complexity of data analytics in HR is lower than the data-scientist is trained for. You need to have a lot of complicated issues to analyze and a high level of analytics maturity in HR in order to fully retain a data scientist.
A good HR analyst with excellent Excel skills and master-level I&O psychology statistics knowledge can already answer 90% of your questions. Recent I&O psychology graduates who excelled in statistics often fit this profile well – and are much cheaper than a data scientist.
Tip: Oftentimes, the actual analytics is simpler that you would think. Working with a skilled HR analyst can already bring you a long way. Be careful with hiring a full-time data scientist – rather, borrow one from the marketing or finance department.
5. Interpretation and execution
Now that you’ve finished your data analysis, it’s time to execute on your findings. This can be through a presentation and a brief report to senior management, through regular sit-downs of your business partners with line managers, or through updated performance appraisals that include the new insights.
Depending on the stakeholders and your influence on how they are managed your approach will differ. See the implementation of findings as an active change project. Key is constant communication and deliberate changes in behavior patterns through constant reinforcement.
If, for example, you have analyzed risk factors for employee turnover, you will want to connect a reduction of (the drivers of) turnover with the performance appraisals of the managers. This aligns their personal objectives with the solution to the company’s problem.
Techniques like storytelling and storytelling and data visualization are often used to communicate insights. Although these terms have been severely hyped up, they can offer basic techniques to communicate the message clearer.
As a final note, a people analytics project never happens in isolation. It often touches multiple areas in HR and impacts not only the topic of the research but also related areas. After the findings have come in there’s often a need for further analysis to understand the nuances.
There’s also often a need for more qualitative explorations of the results. If you see strong deviations between two departments, you want to know why these deviations take place – especially if the data you’ve collected seems similar. In this case, there are often elements at play that haven’t been measured yet but that are relevant to explain the differences – and thus provide excellent learning opportunities.
Long story short: HR analytics is not rocket science. It is a structured approach to solving business problems through people data. This means that it affects all the traditional HR best practices and makes them digital and data-driven. However, as you also saw in the last point, it doesn’t mean human intuition is replaced. Rather, it enhances it and it provides clues for new starting points of improvement.
This article has given you a brief overview of how analytics can be applied – and how you can get started today.