We Get Work®: An Exclusive Interview with Scipher Medicine CPO Kyla Pavlina

Transcript

INTRO

Leveraging data is one of an organization's most valuable assets. Metrics measure market competitiveness and help ensure pay equity and compliance with federal and state laws and regulations.

On this episode of We get work®, we speak with Kyla Pavlina, the Chief People Officer at Scipher Medicine. Kyla discusses how companies can use data as a powerful tool to bridge the gaps between emotions and evidence when organizations discuss compensation and equity.

Our co-host is Sarah Skubas, principal in Jackson Lewis's Hartford office and co-leader of the firm's healthcare industry group.

Sarah and Kyla, the question on everyone’s mind today is how can data drive clarity and accountability and measure success when discussing compensation and equity, and how does that impact my business?

CONTENT

Sarah R. Skubas
Principal, Hartford 

Hello, it's Sarah Skubas with Jackson Lewis, co-chair of the Healthcare Industry Group. Thank you for joining our podcast series. I am thrilled today to have with me Kyla Pavlina, the Chief People Officer at Scipher Medicine. She has a passion for today's topic, is a dynamic leader and we're just really thrilled to have her join us today. So, thank you for joining us today, Kyla. 

Kyla is with Scipher Medicine, a precision immunology company. She's got a really extensive background. She has taken companies public. She's managed significant employee growth for various large companies, including taking a biotech company from 80 to over 1,700+ employees in a seven-month span. That could not have been easy. She's grown other large companies from 80 to over 5,000 employees, along with navigating international growth. So, we're really thrilled to have your expertise here today, Kyla. 

We are excited to talk about a topic I know you feel really passionate about. Let's jump right in. We're going to be discussing data, and really how to utilize it to de-emotionalize the discussions around compensation and equity that you have all the time, I'm sure, as Chief People Officer. 

Can you tell us just a little bit about how you first became interested in utilizing data as a Chief People Officer?

Kyla Pavlina
Chief People Officer, Scipher Medicine 

Absolutely. Thank you, Sarah, for the warm welcome. 

Data is one of the most powerful tools we have as business leaders. It bridges that gap between emotions and evidence. So, the thing that I like about it is that it drives clarity, accountability and measures success. When we're trying to make that positional move from HR personnel managers into business partners and really be an influential business leader, data is going to be one of the cornerstones that builds that trust and moves our profession into that space more readily. 

I go back, and I think about the original moments, mirroring finance about 15 years ago. Fifteen years ago, finance underwent this huge transformational change. They were accountants and now we look at them as business leaders. In fact, some of the most important second to that of the CEO. The CPO, our role is starting to go through that transition as well because we're no longer just the people or the emotional fillers. We don't do things after the fact. We're now being leveraged strategically beforehand, and data is one of the best ways to kind of make that change steady.

Skubas 

It makes perfect sense when you're talking about it, using empirical data to make decisions. It's totally common sense, but you're right. In the world of human resources or people work, we think about it more as a focus on the soft skills or those non-data-driven performance factors. It's a hard shift for a lot of people.

Can you tell us a little bit about how you actually go about utilizing data as a Chief People Officer to make those decisions?

Pavlina 

Absolutely. Great question. It's the one that gives us the ability to use it more readily. Three big things. I do this like clockwork when I'm looking at data. 

First is know your audience. What do they care about? What's important to them? Second is if you know the person, how do they receive the information? It's different when you're talking to your CEO or your board or your fellow colleagues that are other leaders. If you know that person and you know how they receive information, what I mean by that is sound bites, tons of data, what type of person are they and how do they digest data? Third is what are the patterns and personal value system of the person you're trying to influence or you're presenting the data to?

If you can look at those three and consider all three or four using data and trying to influence a decision, you're going to have more success. Always starting with what's my goal? What am I trying to solve? Who's my audience? Who am I talking to? What do they care about and what's their personal value system, if you have that close of a relationship?

The other key tip is that you always learn the best when you make mistakes, and it sticks with us the longest. This, for sure, is absolutely mine. Data is not a one-size-fits-all. There is not one piece of data I can look at you and say, hey, as a CPO, if you use this, you're always going to have great results. That's not true because now you're avoiding the audience, the personal and the value system that I started with. So, data is not a one-size-fits-all.

The last tip with starting to use data and making that transition, because it's not something that's been the history of HR, which I affectionately call people ops or POPs, is it shouldn't be rigid. It should not be rigidly applied. It's always your strongest tool, but it cannot always be used for everything because it doesn't always work in every situation. You can't just port a theory, a thought and a data and move it amongst businesses, people you're trying to influence, or employees and think it just, it works. There's not a recipe, unfortunately.

Skubas 

That's really going to be relevant to our listeners. You're melding the worlds of what we think are more traditionally business operations with those soft skills that we know are critical because we can't just put people into data points. People are more complex and that component you were talking about in terms of knowing your audience, that's where those key soft skills come into play and being really mindful about it. People get scared about utilizing data too much when we're talking about, I love that, POPs or the HR realm. 

If you could break it down a little bit for our listeners who might be newer to utilizing data or thinking critically about how to utilize data. What data do you actually gather? How do you get that data? What are the benefits when you've seen the data come together in the POPs world?

Pavlina 

Absolutely. I love that you're using POPs. It makes me so happy.

Skubas 

I'm going to totally take that word as my own now, I love it.

Pavlina 

It works with Laszlo Bock's book, Work Rules!. We were like the personnel, I call it affectionately the pooper scoopers, and we've moved into the third cubic business partners and it's people operations. So, it sticks quite heavily. 

To answer your question, data empowers them to move beyond instinct. It truly transforms organizations when applied correctly. If it's a newer person to using data or oftentimes you don't have the systems that allow you access to data, I would always recommend the unsung hero of the PeopleOps team, which is the ops analyst. You have an HR analyst who used to be HRS admin, and then it's slowly moved into this place where you're actually able to mine data, put data together and make it make sense. Definitely start with your talent inside your team. Who is your data person? Oftentimes in the PeopleOps departments, it's missing. That's why I call it the unsung hero. Start with a person that's going to help get the data because it's not going to be you who's going to be able to do it day in and day out and make these changes as you're using it to influence. 

Before you collect that data, spend time---again, first is your talent, then you're going to spend time with a question: What am I trying to solve? Then you look at your three things such as audience and personal value system. One of the reasons that you start with the data analyst and then move into the question you're trying to solve is because, as humans, we have confirmation bias. So, what happens is we tend to believe so strongly in our own positions that we find information to continue to approve what we believe. To truly look at eliminating confirmation bias, data is one of the places to start because you can't really argue with it as much. Now, that's not the rigid thing that I said earlier; it can't be rigid, but at the same time, if we're looking to de-emotionalize and we are looking to remove confirmation bias, data is going to be another place you hit as one of your cornerstone tools to start to influence. 

The last thing that I think resonates best with CEOs is you can measure success, you can hold yourself accountable and you can adapt accordingly. I don't know about anyone else, but there's no project that works and comes out with flawless results. There's always a change along the way where, ooh, we thought this, and it's not really working, or another unintended consequence happened and we're having to course correct. If you're managing your data along the way, it's going to allow you to adapt faster and more accurately.

Skubas 

I love that. You mentioned equality and looking at it to avoid that confirmation bias and utilizing data in that fashion. If you're looking at compensation metrics, that's data a company or organization has. That feels like one data point that you can utilize to make sure you're making database decisions. Obviously, in the world of pay equity that we all live in right now, pay transparency issues and increasing state regulation around these issues, it's obviously a key data point that you're going to be looking at. 

Are there other types of data that you can gather in an organization that you find can be really helpful to this data-driven decision-making other than perhaps compensation?

Pavlina 

Absolutely. It's a good question. The easiest way to describe this is I'm going to give you a time when data worked for me and when data didn't work, and it's not necessarily in the compensation realm. 

The question that I started with on the one time, well, not the one time, the many times that data worked is are we equally investing in employee benefits worldwide? So, at CrossFit we had 5,000 employees worldwide. 54 % of that growth was international. Quite frankly, the laws in each country and what the cultural norms or expectations are quite different. The question for the executive management team as they tried to acquire and retain the talent was, what are we investing in them and what are we getting as a rate of return? That's an easy one for CPOs. We look at attrition rates and how long it takes us to bring in people. But how are we motivating and moving along our A-players? Let’s look at the benefits and the fringe things for them as far as 401k all the way down to maternity leave, or I'd like to say parental leave, depending on where you are.

This mattered as the role and responsibilities were different everywhere, right? I always think Australia and China were two countries that permanently etched in my brain because it was so hard for me to make that data work. But our business line provided a certificate and courses. So, what happened was there was about, probably a thousand employees that had the exact same job, but they were in different regions. So, the laws that I had to use to apply to them and how I was going to motivate them looked quite different but we wanted the same output in every region. The other risk was, and the reason we asked the question, what are you trying to solve for is we didn't want people to move. We don't want people to be in regions that are most beneficial and lucrative to them because we needed them to be in different regions where we were teaching the courses and the certification process. So, we had to look at everyone. Here’s the process and the data that I gathered.

Talent first, what is the talent doing? What's their job description? I know we hate talking about those things because that's a document that's, we can talk about that at another time, but I have a big problem with job descriptions that are too rigid, too lengthy, and we've just completely lost our audience, and they become too legally focused. We can say that as attorneys, we can look the other way to make it a little bit more motivational.

So, talent first, what are these people doing? Do you have the talent on your team? Do you have your HR analyst? Did you have the system to collect the data? The second is the system. How are you collecting the data? If you're working in Excel, it looks markedly different than if you're working in Workday or if you have a homegrown system because your business is so big that they made an HR system. So, looking at your system second, and then your process third.

When I think of process, I think of the legal requirements and the cultural expectations, because they oftentimes don't match. But you need to track both of them. That's a large data set when you're talking about 5,000 people internationally, eight countries at the time, and the laws were the same. We even classify them the same. So, you have these pieces of data and need to take the employee benefits, employee costs and the employer benefits. There are two different costs for what the law requires and what the cultural expectations are. It starts to tell a story because you start to see patterns. 

First, you're going to see patterns, hopefully in every region that has the same law, that they're following the same things. The cultural is different. I'll give you one example for this exact same situation. 

Australia had 11% which we call 401k. They do not call it that there. In the United States, for example, we don't have to get 401k pension. It's a benefit. You can match; you cannot match. It's a leveraging tool, but it is not a requirement. Australia, one of the rules we were facing at that time was 11%. So, 0 % in the United States to 11 % didn't mean I was treating these two groups of people exactly the same. Looking at the investments of what the employee was receiving and what the employer was paying, and then how did we right-size that data? So, if I have to give you 11 % pension and you're in the United States and you have zero, I'm going to find another way to keep you invested, rewarded, engaged, and to keep you from moving to Australia because that would markedly change our ability to continue to be successful. That was the time that data worked. 

Skubas 

That's great. I was going to say, particularly for the healthcare industry right now, Kyla, employee retention is a huge issue. Healthcare employers are now more often than not navigating into the space of remote workplace where they never had before. There have always been brick and mortar employers. So, thinking strategically and utilizing data kind of leveraged that remote workforce, whether it be within the US or outside, which is a new trend for the industry. It is a really relevant and a really critical way to look at that. I thought that was a really great example. 

It's a really interesting thing because my gut as outside counsel, not in the trenches like you are, would be that leaders would love this data approach. They're businesspeople, so the touchy feely or what they think HR is doesn't always resonate with them. But it’s multifaceted and that’s a really great example of understanding what matters to the employee base is going to help you get to the right legal compliance issue on something like a classification. But it's utilizing the data to get there in maybe a different way than you thought, requiring a little bit of creativity around that data as well. That's a really great example. 

 I think you've touched upon it, some of those pitfalls or lessons learned in using data to de-emotionalize discussions. Is there anything else that you've learned, where data took you down a wrong path that you think our listeners may benefit from other than what you've already shared? I think it's been really helpful.

Pavlina

It's a good question. I think of the pitfalls again, look at your talent system. All the stuff I said before, know your audience, what's your question, what are you trying to solve? But just like the CFO transition and the CPO transition it's about not being rigid. It's a gap or a bridge between the gap of the two and being able to adapt accordingly is probably what's going to be the most helpful. 

Find your allies. You will always find an ally in data. There is someone somewhere on the executive team, oftentimes it's the CFO because this person is oriented to dollars and bottom line. Find your allies in data and the people that when you speak to them about it, it resonates with them, and they feel strong about it. 

The other interesting example in some of the businesses I have is scientists often and founders or doctors who are very much in this space. Oftentimes they are less looking at the instinct and the emotional and they feel much more comfortable in this space. You're probably going to find some allies there. So, the champions and the supporters of data are going to be your people function partner, right? To help leverage more data and more influence. Yeah, I think it's the allies. Absolutely.

Skubas

Kyla, attrition is and remains a huge concern for the healthcare industry. How have you seen data work or not work in evaluating attrition data, if you've done that?

Pavlina

It's a great question. I'm going to give you an example of one of the more difficult times or one of the learning experiences I had with collecting attrition data. 

I had a comp committee chair who very much cared about regretful loss and not regretful loss. Where we started was something simple as regretful and not regretful. As we went through the data and learned the circumstances, it ended up being way more complex because there ended up being three in each regretful and not regretful. The way we learned was actually just by doing it and adapting on the spot. The board and the comp committee looking at attrition cared about a group of people that was the talent they wanted to retain, but that wasn't everyone at all stages in the business. If the business shifted, there's oftentimes a talent pool that is less important to them at the moment. Again, know your audience. So, it probably took me four to six bites of the apple working with her to ensure the regretful and not regretful was put in a way that she cared about when she cared about it. It's just another reminder of not only is attrition important, data is important, but again, adapting to her audience and then making sure they're getting the information they need so that we can help influence the right decisions.

Skubas

I'm just wondering; we've touched on the benefits, the sources of data, and comp benefits. Is there anything else, any other sources of data that you find really interesting or that you want to touch on? I think we hit a couple of great examples there. 

Pavlina 

It's more of the unintended consequences, which are the times that you do something wrong and you learn, that sits and resonates with me. It's undoubtedly, I'm almost a little bit embarrassed to say it because it was the first time we went, oh duh. We've got 12 states that have paid transparency. That requires us to post job postings with a range, the band and more information about compensation. 

Well, when you have employees in several states, oftentimes, there are similar families, bands or exact roles. If you haven't done an entire analysis internally of how that maps out, your long-term, A-player talent engineer who's been sitting with the business for five years sees a posting in California for the same role making at or the same amount that they're making. Oh, you have a problem. You have just demotivated one of your A-players. The pay transparency when I worked in this space is not just knowing the states and the rules that applied, but it has to be used to look at the entire analysis. Most of us have businesses and employees too big to memorize. That goes back to your HRS analyst and person who's going to start breaking it down so that you don't fall into any situation where there's an unintended consequence where you demotivated an A-player in a different state.

Skubas 

I think that's a really great example, Kyla, because so many clients struggle with that precise issue, pay transparency and the information out there. So, reconciling those challenges is going to resonate with a lot of people in the industry who are navigating an increased remote workforce where they've never had to deal with that. I want to ask you a final question for now.

For some of the listeners who may not have any experience in using data in the way you've done it, are there any final recommendations to get started that you would share with some of our listeners?

Pavlina 

No, I think it would just be what I mentioned earlier as far as what are the questions you're trying to solve, who's your audience and what's important to the person and their value system. Don't be too rigid. Be able to adapt and listen. 

The most portable piece of advice while using data, not only for CPOs, but I think for any in a leadership position is really listening to listen, not to be right or not to come up with a response to be right but be willing to be influenced and learn. Oftentimes you will find exactly the right solution. That fine line between that bridge and that gap of using two sides of your skill set is what's going to make you able to use data when and where you want and what helps the business drive success more often.

Skubas 

Wonderful. Well, thank you so much, Kyla. I really appreciate you sharing your insights. It's been really illuminating, particularly for somebody like me who doesn't deal with the day-to-day decisions that you're navigating and learning how to utilize the data to have those critical discussions. 

I loved your insight, particularly around the flexibility of utilizing data in the world of human resources, or POPs, as I now will call it for the record.

Pavlina

Yay!

Skubas 

You should copyright that. Thank you so much for joining us here today. We really appreciate it.

Pavlina 

Thank you so much, Sarah. I appreciate it tremendously. Take care.

OUTRO

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