Retaining top talent with data: A Q&A with Kraft Heinz’s Global Head of People Analytics, Serena Huang

Editor’s note: This interview originally aired in May 2020. Since then, Serena Huang has changed roles and is now Global Head of People Analytics & HR Technology at PayPal.

During the height of the pandemic, many businesses relied on essential workers to stay afloat. None felt the pain of losing high-performing employees more sharply than those in the food supply chain. For Kraft Heinz, keeping a pulse on employee well-being became a top business priority. They launched a number of health and wellness surveys to track employee happiness, collected textual comments to understand the nuance of employee experiences, and turned to people analytics to find meaningful patterns in the data. To understand how the business transformed all this data into an actionable employee retention plan, ThoughtSpot’s Cindi Howson sat down with Kraft Heinz Global Head of People Analytics, Serena Huang. Read on for insights from their conversation on The Data Chief.

Cindi Howson: I think that data can reveal huge gaps we have in diversity and equity, which in turn can be a force for change. Do you agree with this?

Serena Huang: I agree. We can't improve what we don't measure, right? You see a lot of job postings for chief diversity officers in various companies that didn't exist before. Not that diversity inclusion wasn't important, it just wasn't talked about at the same level. It wasn't demanded at the same level. Data is now going to be part of that conversation. I think companies who are using this correctly will be ahead. They will be able to see opportunities in the data and make action plans to address any gaps, versus companies that may be less mature and don't know their problem areas.

People data is very messy. Having done the people analytics leader role for four companies now, it's not easy. You have to pay a lot of attention to data quality before you can make useful analytics. At least in parallel, address some of the data quality issues as you go. Part of that comes from standardizing processes so that you are talking about the definition of a human capital metric the same way. We've been on this journey for a long time at Kraft Heinz, so I see focusing on data quality paying off for us.

Cindi: How do you strike a balance between clean enough yet directionally accurate data?

Serena: We start with the problems at hand. I like to tell my internal clients, "Don't start with data, start with the problem that you want to solve." If you have a retention problem, you want to look at your turnover data for employees. Don't boil the ocean and try to make sure every single data element in your system is accurate; focus on the turnover issue at hand.

A lot of times, we will do that and then clean up the data. This will mean a review of what is incomplete or inaccurate, and then a cleanup effort that will last for multiple weeks or months. Then we build analytics on top of that, whether it's beautiful dashboards or something more advanced. But I think focusing on the problem will drive the effort to clean up the data. It's not a fun job; there needs to be a business purpose.

Cindi: How have you balanced the conflicting incentive of collecting employee data to measure what matters, but not leveraging it against employees?

Serena: In various companies I've been with, something that we always ask ourselves is, what's in it for the employees? Whenever we're collecting an additional data element or pushing folks to go into the system to update something, if there's nothing for the employees, it's probably not going to get done. We need to make sure in our communication that we're clear on how the data will be used and how it will provide benefits to employees.

For example, a lot of times you want to ask employees about their preference for career growth. What kind of jobs are you interested in? Are you able to relocate geographically? Are you mobile? Tell us a little bit about your experience before joining this company. All these questions are great data for the company to have, and it helps employees. If we know their career interests, then we can provide better matching with opportunities that exist, maybe one;s employees didn't know about. We also have to be clear on how it doesn't become problematic for employees who may say, "I'm not mobile right now, but I might be later." This is not going to be used against you, as our stated intention for the data makes clear. 

Cindi: At Kraft Heinz, you've done some very interesting analysis on how to measure employee wellbeing. Can you tell us a little bit about that?

Serena: Sure. Earlier in the pandemic, we started our research and found employee wellbeing to be important because we couldn't see them in person. It's hard to know how people are doing in a small box on the screen. With our leadership team's support, we launched our first global health and wellbeing survey. We found that people were starting to get stressed with the overall uncertainty and spending more time at home. Some people were working remotely for the first time in their lives. These were all adjustments that our employees were having to make. We realized from the comments employees provided that there were additional things that we could do.

Since then, we have expanded upon our benefits program from the EAP, employee assistance program, to providing fun things like yoga lessons at work. I led a meditation that was available to the whole company last year. These are little things that we were able to do, based on the feedback the employees provided. It didn't solve all the problems of this last year, but it made their lives a little bit better. 

Cindi: The other thing that your team did was mine textual comments from employee surveys. Can you tell us a little bit more about that?

Serena: On all the surveys we've designed, we've allowed employees the opportunity to comment. Not, "At the end, tell us something you'll want to share," but after each question. The benefit of that is we'll ask a specific question, and then we know what the comments will be related to. It's easier to have targeted comments that will be more useful than open-ended questions at the end of each survey. 

We do a few additional things to see positive, neutral, or negative comments on different topics and questions. A lot of times we'll see themes around meetings, time zone challenges, workloads, or the challenge of staying connected with others at work. We're able to look at the themes from the comments and apply sentiment analysis to see which comments or topics are trending more favorably. That's been insightful compared to what we did in the past.

Cindi: Any interesting insights or external data that has given you better indicators on how to retain top performers or who might be churning?

Serena: I think a lot of companies are paying a great deal of attention to this topic because we know externally the surveys are showing somewhere between 20% and 50% of employees are going to look for new jobs after the pandemic ends. I know from experience at Kraft Heinz that the easiest data points to look at are internal ones, whether it's compensation, job history, or team dynamics. External factors are equally important. There's a pull and push factor when it comes to someone staying at a company. Something that I've found helpful is to look at measuring how competitive this job is externally. In other words, how likely will someone poach your talent?

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