How to Start Using People Analytics

Part of a series  |  People Analytics Series

A woman sits at desk looking at people analytics on a computer

Leveraging people analytics might seem like a heavy lift, but getting started can be simple and straightforward. Here's some helpful guidance on establishing a strategy and understanding the data you need to get it right.

You have your basic metrics and reports on headcount, turnover and retention, cost to fill, labor costs and probably something on engagement, performance and diversity. You've been wanting both a more comprehensive picture and more detail on specific issues.

It would be great to see how your organization compares to others in your area or industry, but you may be unsure about what's involved or how to start. You're not alone.

To help clear up uncertainty and confusion around people analytics, we asked Amin Venjara (AM), ADP's General Manager of Data Solutions, to explain how to get started. Amin spends a lot of time figuring out how data can offer insights, help with compliance and give organizations a competitive edge in talent management. Here are his thoughts.

Q: First, what is "people analytics" and why does it matter?

AV: People analytics is using data about workers to make more effective talent management decisions. It's important to remember that each data point represents something about a human being. A good people analytics system should humanize your analytics.

People analytics matter because humans are complex and not always easy to understand. Surveys are great for learning what people think, feel and say. People analytics help us understand where people are, what they do, how they fit together in an organization and how organizations compare.

Fundamentally, people analytics help you know whether your talent and HR initiatives are working. For example, you spend countless hours and resources recruiting, hiring and training people. Do you know how many stay? Do you understand who's leaving, how soon and why?

People analytics can help you get to the answers so you can see if your investments are paying off.

Q: How does an organization get started with using people analytics?

AV: People get excited about all the data and want to jump in and see what they can learn. I can't blame them. I would too.

A more effective strategy is to step back and look at what you want to know and why it's important to you. Then pick your top priority and start with one question.

Lots of organizations are concerned about turnover and retention right now. Before you can dive into analyzing turnover, you need to make sure the data you already have is the right information to figure out what you want to know. Data is often tracked in different systems or programs and may be great for a specific report, but it might not be as useful for your people analytics system.

For example, headcount is an important metric for understanding turnover. You want to know how many people work with you, where they are and when there are changes. Information about your full-time employees is pretty straightforward, and most everyone gets that right. But what about contractors, or interns or seasonal workers? Are they included in your headcount numbers? Do you want them to be?

Including these more temporary workers can help you understand how many people it takes to get the work done. If you use internships for recruiting, you might also want to know whether interns become full-time employees down the road so that you know whether the internship program is working.

One of the most important parts of getting started with people analytics is thinking beyond what you know and beginning to imagine what you would like to learn next.

Q: Using your headcount example as a place to start, what are the steps to getting it right?

AV: Begin with running your normal report on headcount. Then get a headcount from your people analytics system and see if they match. They often won't. There's nothing wrong; it just means the two systems count roles or people differently.

When there are discrepancies, figure out where they are and how you want to handle them going forward. Think about what matters to your strategy. Then configure the data in both places so that they match how your company works and what you want to know.

For more on this, read Data Cleansing: Why It Should Matter to Organizations.

Q: What if you aren't sure what you want to know because you're new to analytics and don't know what's even possible?

AV: What you want out of a people analytics system is the ability to get valuable information quickly.

Start small. Pick something you already know the answer to. The best way to get comfortable is to work with data you can verify is right. Don't worry about the fancy metrics until later.

If a metric is something you normally look at and use, you will naturally figure out how to get it right in your people analytics system. Data is always imperfect before it's perfect. Focus and monitor it over the course of a few months. Once people are focused on it and working with it, the data will improve.

That's why I like to use headcount as a starting place. It's easy to figure out and know if you need to make adjustments. Headcount is also the foundation for many important metrics like turnover, open roles and time to fill. Then determine your metrics of consequence.

Q: What is a metric of consequence and where do you find them?

AV: Metrics of consequence are usually hiding in plain sight. They are the things you already track because they're important to you and the things you want to start tracking because they may help you make more effective decisions.

More is not always better. Pick the most important metrics for your organization, such as turnover, and make sure you have the data you need to learn more.

With turnover there are several metrics that are core:

  • Voluntary turnover: Overall turnover just tells you how many people have left. It won't distinguish between the people you let go (involuntary) and the ones who quit (voluntary). Voluntary turnover is where you want to focus for retention.
  • New hire turnover: When people take a new job and then leave after a few months, it's an opportunity to understand why and address any problems.
  • Top performer turnover: These are the people you least want to lose. If top performers are leaving in droves, you want to know and get to the bottom of the issue fast.

To get answers on turnover, you need to track voluntary and involuntary turnover, monitor when people leave compared to their hire dates and determine who your top performers are. Most organizations already have the data on the first two. Figuring out how to designate and track your top performers will probably take more work. What does success mean in your organization? Who is (or should be) valued highly, and why? How do you measure someone's contributions? What are the consequences of making these determinations? Will salespeople seem more important than the administrative assistant that makes everything run?

This is where humanizing data is essential. How you define and use metrics of consequence isn't just important for the organization's success — it can make a difference in people's careers and lives.

Meaningful insights about your people and processes are hidden in your people data. We'll help you find them.