HR Management & Compliance

The Three Building Blocks of People Analytics

A lot has been written on the importance of people analytics. A data-driven approach to managing people offers a lot of advantages and supports managerial decision-making. In this article, we’ll explore the foundation for getting started with people analytics.

Start with What’s Available

When we get started with people analytics, we’re essentially creating a new way of working and looking at data in a traditional-thinking HR department. This deviation from the status quo can be compared to the process of new venture creation within an existing organization.

One of the key approaches to this new venture and value creation is effectuation. Effectuation is a form of reasoning in which one starts with the available means instead of a number of set goals. Instead, the goals are formulated based on the available means.

This applies to the HR organization as well. In HR, we have different means that are available and that will structure what we can achieve with people analytics. In general, I would define three key means:

  1. Business problems
  2. People data
  3. Analytical competencies

Let’s go over these three areas one by one and see how each enables us to work with data to make better decisions.

1. Business Problems

We often talk about business problems in people analytics. Analytics will only add value if it solves real problems. This means that it doesn’t focus on pet projects but on projects that make an impact on the entire organization.

What this looks like in practice will differ from organization to organization as each has different challenges.

For example, an organization with high levels of turnover will have to analyze different data and implement other measures compared to an organization that copes with high levels of absenteeism. These problems are also often related to country and culture: turnover is much more a problem in developing countries like Brazil and India compared to Western European countries.

In addition, these problems also involve different kinds of people or human capital. Turnover is more a problem in developing countries because global businesses that are looking for lower-skilled and easy-to-replace labor are actively competing with each other. More established companies with older workforces based in Europe usually have more loyal and higher-educated workers—but they cope with higher levels of absence.

The golden rule in any business area is that if you solve a problem, you will create value—and this holds true in people analytics. If you can leverage people data to solve a business issue, you are off to a good start.

Let’s now look at this second element: people data.

2. People Data

When we know the problems in the business, the second step is to check if we have the data to solve these issues.

Traditionally, a lot of data in HR has been tracked in Human Resource Information Systems. Usually, these are transactional systems that keep track of demographic data of employees: their salaries, performance, time since last promotions, previous internal job titles, but also information on the previous employer, education, university, internships, absence records, and other information.

This information is usually stored in separate systems but can, when combined, provide excellent input to solve the issues we mentioned previously. For example, someone’s career path can be used to measure intention to quit. If someone has been waiting for a promotion for a long time—or received a promotion without a salary increase—these may increase one’s intention to leave the company. When all these different possible variables are combined in a predictive model, it can help to predict turnover.

Similarly, previous absence, age, work intensity, and other stress factors can be used to analyze employee absenteeism and risk factors for long-term absence.

Not all data are available. Sometimes, you have to collect new data to properly analyze an issue. This is often a time-intensive process, and it is a best practice to do this only when (1) necessary and (2) for a small group of critical employees. This is in line with agile HR, an increasingly popular approach in human resources.

Critical employees are, in this case, the people whose performance will make the biggest impact on the issue you’re researching. When you’re trying to improve customer satisfaction, you will want to start with front-office employees because they are assumed to make the largest impact on your business outcome. This focus saves time and money.

3. Analytical Competencies

The third key element in getting started with people analytics is about having the actual skills.

Creating a people analytics unit requires different skills. It includes the ability to connect people, build alliances over functional divisions (with IT, legal and compliance, and marketing or finance), and making progress towards a goal that may challenge conventional HR practices.

The people working in the people analytics unit need to be able to conceptualize problems, define data requirements, and work with data. This is not everyone’s strong suit.

When the results of the analysis are in, your business partners need to implement it. I would estimate that around one-third of HR professionals actually see data as something that is important and that can help to make more impact. Training your HR professionals to get the most out of data and insights is an integral process of building people analytics capabilities. But before we reach this point, we need to do our first analysis.

Getting Started with Analyzing People Data

The three key means described in this article are business problems, people data, and skills. When these three are combined, we have the basics for value-adding analyses.

Key in this effort is to focus on easy wins, especially early on. Using the principles of effectuation, we can define a number of best practices. These are a focus on key employee groups, a focus on projects for which the data is already available, and doing analyses that are within the team’s skill set.

These best practices enable you to create early wins that will help in establishing people analytics in the organization.

Erik van Vulpen is founder of Analytics in HR (AIHR). He is a writer, speaker, and trainer on people analytics. Van Vulpen is an instructor for the HR Analytics Academy and has extensive experience in the application HR analytics. Connect with him on LinkedIn.

Leave a Reply

Your email address will not be published. Required fields are marked *