People Analytics: Making People Data Work
Part of a series | People Analytics Series
One of the keys to effectively leveraging people analytics is staying curious as you learn. Your questions are likely to keep getting better, and so will the insights. Here's how to know you're allocating the right amount of time and resources to your initiatives.
People analytics give organizations insights into their business operations that can benefit both their employees and the bottom line. Before taking action based on those insights, it's essential to understand where your data comes from and how it can and should be used.
In the first part of our conversation with Amin Venjara (AV), ADP's General Manager of Data Solutions, we talked about how to start using people analytics.
This discussion expands on how to get your data right and use your analytics system effectively.
Q: What are the core HR Metrics that you need to get started with people analytics?
AV: The core HR metrics are 1) headcount, 2) hires and 3) terminations. With these basic building blocks, you can start to see what is happening with the people in your organization.
Hires and terminations are the beginning and end of the relationship with employees, and headcount reflects their path and time within that relationship.
Headcount and hires are fairly straightforward, but it's important to know who's getting counted, who isn't and why. If your data is incomplete, you can then adjust if needed.
Terminations are more complex because figuring out why people leave is not always easy. Often, we see organizations tracking voluntary departures, involuntary departures and 'unknown.' Unknown means you don't have the data.
Knowing why people leave is valuable because it helps you understand what you can control, what you can't and where you may have issues to address.
Think through what you want to know and how best to collect that information. Make it a metric of consequence and help people understand why the information is important. Structure the reasons people leave in your system so they give you meaning.
Also consider who is collecting and recording the data. People who are leaving, their co-workers, managers and HR may each have a different perspective and interest in the answer.
Some organizations rely on self-service to save money, but it doesn't save money if you're giving up intelligence. Turnover is expensive. It's worth thinking strategically about the implications of trading important and useful information for convenience.
There are lots of possible reasons why people may leave a job. You don't need to track them all in infinite detail. Focus on the ones related to work and where the employer can make a difference.
Q: When you're creating a new data field in your people analytics system, what's important to think about before you start putting in the options?
AV: First, figure out what you want to know and why. Then determine what data you need to answer the question and how that data is created and recorded. What is the business process that creates that data? Who puts the information into the system? Who should?
For example, how do you track race and ethnicity? Does the information come directly from candidates or employees or is someone else trying to figure it out and input the data?
You want the most accurate information and the highest likelihood it will be input into your system so you have the data you need. Focus on your metrics of consequence — the information that is most important for the analytics you are starting with.
Q: How do you figure out the options that you want to track?
AV: When we define options in a field, we want them to be mutually exclusive and collectively exhaustive (MECE).
Mutually exclusive means you don't want more than one answer to apply. It keeps your data clear so you don't have to try to figure out where there might be overlap and how that's affecting the analysis.
Collectively exhaustive means your options cover the possible answers so you don't end up with no answer.
The best approach is to get specific with individual fields and then look broadly at what other information you are collecting. Start by asking these questions:
- If I want to know this answer, what information would I need?
- Do we have this information already?
- If not, what's the best way to get it?
- If so, does it work with our system, and is something missing?
- Once we know the answer to the issue at hand, what else will we want to know?
A good people analytics system and the right solution provider to back it up can help you make it all work. You don't have to figure all of this out on your own. Once you get the data and configuration processes done, the fun part starts.
Q: Everyone wants to go straight to the fun part. How do you start using people analytics?
AV: Find your coalition of people willing to do a pilot project and start with a project they're excited about. When you're choosing the subject of your pilot, start small. Stay focused on value and opportunity. You want quick wins to show how people analytics and insights can make a difference.
Look at what the organization's strategy and priorities are. Think about what your leadership will find valuable. This helps drives adoption of the analytics and then action on the insights.
Set up a feedback process to get a sense of where your pilot team has questions or desires, where they may need additional data and what they are learning.
Once your initial pilot program is running, pick a new issue for another group that will be excited to play with the system. Stay on top of the feedback. Make sure you have the right data and it's as complete as possible. And choose analytics that will make a real difference so you get leadership buy-in.
Q: How do you build from there?
AV: With the right tools, you can design the system the way you want it and focus on different issues as you get more comfortable with the process.
When you run into something that doesn't match what you know, it's usually a data issue. It's not you. Ask for help. You are not alone. It's normal to feel a little overwhelmed at first, but there will likely be lots of help in the system. Make sure you have a solution provider who will be there for you.
The key is to stay curious as you learn. Your questions will keep getting better, and so will the insights. You'll get a clear picture of where you are and what is changing.
As you gain experience using big data for people analytics, it's likely that you'll get a faster and more complete view into how your initiatives are working and where you should allocate your time and resources. That's what makes a difference in the bottom line.
Meaningful insights about your people and processes are hidden in your people data. We'll help you find them.
