27 July 2021

Workplace Stories Season 2, Integrating Inclusion: Use Both the Data and the Story

Dani Johnson
Co-founder & Principal Analyst
Stacia Sherman Garr
Co-founder & Principal Analyst

TL;DR

  • This is the 1st episode of our podcast: Integrating Inclusion, Season 2 of Workplace Stories.
  • In this episode, Stacia Garr and Dani Johnson of RedThread Research and Chris Pirie of LITNW interview Hallie Bregman, global head of people analytics at PTC.
  • Data is the heart of HR, but it only comes alive when it’s part of a narrative.
  • “I think there’s a lot of value when you have that human, who can interact with the computer, help add the context back into the computer, and that’s a lot of the work that I do.”
  • Diversity, Equity, Inclusion and Belonging (DEIB): It’s more than diversity reports and employee satisfaction surveys.
  • How do you make DEIB data usable? How can you use data to tell the story behind the metrics and the numbers?
  • A special thanks to our sponsor, Workday, for its support of this season!

Listen

Guest

Hallie Bregman, PhD, Global Talent Strategy and Analytics Leader

DETAILS

We love data, and we think it needs to be at the heart of all HR, especially in DEIB. But like this week’s guest, global talent strategy and analytics leader Hallie Bregman, we also know that data really only comes alive if it is part of a narrative. “I’m not going to give you data,” Hallie tells her colleagues at major Boston-based IT firm, PTC. “I am totally driven by data; I eat, sleep and breathe it all day long. But I'm going to tell you a story, and then I'm going to help you build a strategy around that story.” That is such a smart way to put it—and this is one smart lady with so much to say that’s useful about DEIB, people analytics, ONA, NLP and so much more. We knew Hallie would be an important contributor to this first official episode of the new Season of ‘Workplace Stories.’ We hope you agree—and find a way to use her insights to make your own DEIB ‘story’ a success too.

Resources

  • Hallie is a big LinkedIn networking fan and is happy to connect with people interested in her work there.
  • The website of her employer, PTC, which develops technology that helps industrial companies to create value for themselves, their customers, and the world, is here.
  • Hallie suggests that two organizations doing good work around both DEIB and people analytics are HubSpot and Rapid7; might be worth checking them out.
  • Find out more about our podcast helpmate and facilitator Chris Pirie and his work here.
  • Catch up on Season 1 of ‘Workplace Stories’ here.

Webinar

Workday will also host an exclusive live webinar at the end of this Season, where you can meet the team (Dani, Stacia and Chris) and join in a conversation about the future of DEIB in the workplace. You can find out more information, register for the webinar, and access exclusive Season content, including transcripts, at www.redthreadresearch.com/podcast and thanks again to the team at Workday!

Partner

We're also thrilled to be partnering with Chris Pirie, CEO of Learning Futures Group and voice of the Learning Is the New Working podcast. Check them both out.

Season Sponsor

We'd like to thank the people at Workday for the exclusive sponsorship of this second Season of 'Workplace Stories.' Today, the world is changing faster than ever, and you can meet those changing needs with Workday; it’s one agile system that enables you to grow and engage a more inclusive workforce—it’s your financial, HR, and planning system for a changing world.

As we start to tell the Workplace Stories we think matter, we hope you follow ‘Workplace Stories from RedThread Research’ on your podcast hub of choice.

TRANSCRIPT

Five key quotes:

Folks are much more interested in what that story is than what the number ever was unless there's some crazy benchmark they have in their head.

Let's say our engagement for our company, is great, it’s 80%, we’re really all happy. And then you're like, well, turns out 80% of my employees are white—so sure, we're all happy, but you're not really hearing the voice of those under-represented groups. And so it's pulling that out, and making sure you have a good sense of where everybody's falling in that range on all of your core metrics before you keep going.

DEIB buy-in: DEIB is a scary thing for some organizations, and data is a very scary thing for some organizations—and when you put those two things together, it's very, very scary for some organizations.

I describe people analytics as the perfect hybrid of all things that I love: it is people, it is partnerships, it is understanding insights and telling stories, and I like to pull that altogether.

When the culture is really data-savvy, you can get a lot more out of people's analytics sooner. And that doesn't mean that a culture that isn't data-savvy off the bat can't get that; it’s just going to take a lot more of that management, that thought partnership, and bringing people along on the journey, and that takes some time. It's easy to want to jump into some of the sexy analytics right away, but it's really important to help folks see the value, get used to it, and then start to make the business case to do things a little bit more advanced.

Stacia Garr:
Welcome to 'Workplace Stories' hosted by RedThread Research, where we look for the ‘red thread’ connecting the humans, ideas, stories, and data defining the near future of people and work practices.

My name is Stacia Garr, and I'm the co-founder and principal analyst at RedThread Research, along with Dani Johnson, who is also a co-founder and principal analyst at RedThread, and Chris Pirie of the Learning Futures Group. We're excited to welcome you to our podcast Season: this episode is part of our second Season called ‘Integrating Inclusion,’ in which we investigate your role in the Diversity, Equity, Inclusion, and Belonging journey that we believe is a critical force in shaping the future of work.

We talk to leaders, thinkers, writers, and practitioners about the current state of the art in DEIB, and we focus specifically on what people analytics, learning, leadership, and business leaders can do to move the conversation forward—and why DEIB is everybody's business.

Chris Pirie:

We’re very grateful to the people at Workday for their exclusive sponsorship of this Season. Today, the world is changing faster than ever. Meet those changing business needs with Workday; it’s one agile system that enables you to grow and engage a more inclusive workforce. Workday: the finance, HR, and planning system for a changing world.

Workday will also host an exclusive live webinar at the end of this Season, where you can meet the team (Dani, Stacia and myself) and join in a conversation about the future of DEIB in the workplace. You can find out more information, register for the seminar and access exclusive Season content, including transcripts, at www.redthreadresearch.com/podcasts: and thanks again to the team at Workday!

Stacia Garr:

In this episode, we talk to Hallie Bregman, who is global head of people analytics at PTC. With skills and experience, including data science, people analytics, and a background in psychology, Hallie is very well equipped to help us think through how to leverage people analytics to support an effective DEIB strategy. But having her passion for the topic and rich experience across multiple organizations, and no surprise, her insights are very practical, very real, and very thought-provoking.

You will not regret taking some time to hear Hallie's contributions to the Season. At the very least, you will learn which are the most valuable data sets and analytical approaches, who are the most critical partners in DEIB and how they can best work with the people analytics team, how to conduct a gap analysis and create a DEIB baseline, the role of analytics and program design and evaluation, and what she wishes managers knew about how to leverage data and analytics and the DEIB journey, and so, so much more.

Stacia Garr:

Well Hallie, thank you so much for joining us today for our podcast; you’re actually one of our first guests for this Season, and so we are so excited to jump into it! We'd love to just begin by getting a bit of a perspective on you and your work practice for our listeners, and then we'll go through a number of questions where we talk particularly about this idea of an ‘inclusion imperative’ within people analytics, and what does that mean? So, can we start off by getting a quick overview of PTC, its mission, purpose, and how long you've been there?

Hallie Bregman:

Yeah, so thanks; I’m honored to be one of the first, and really excited to talk about this today—something I'm super passionate about. I currently lead people analytics at PTC, which is a global technology company that works with customers in the industrial manufacturing space. We're about 7,000 employees, with over 90 offices across the world, so we really span the globe, and we’re really focused on helping our customers at the intersection of the digital and physical world.

Stacia Garr:

Very cool. And so you said that you lead people analytics? Can you tell us a little bit about your work and how you'd describe it, particularly for an audience that may not be as familiar with people analytics?

Hallie Bregman:

So I always talk about people analytics as really all data and analytics about the employees, right? So we think a lot about customer analytics: the world has very much leaned into big data and whatnot over the last decade or so, and we're seeing that rise in the people space, and the HR space, now as well. And so for us, people analytics is everything from reporting on our people to developing really strong insights of what's going on in the employee space, and then developing insights and actions to address those.

And so it's a really fun place to be. I love thinking about the inside of the organization as opposed to the outside, so it's a great space to be in right now.

Stacia Garr:

And how long have you been there?

Hallie Bregman:

My one-year anniversary at PTC was about a month ago, so I have passed the month! It means I onboarded remotely, as did much of our leadership team, and so it's been an interesting ride. I've been into the office just three times so far.

Stacia Garr:

Wow, amazing. Well, can you tell us a little bit about the problems you're trying to solve at PTC?

Hallie Bregman:

Yeah, so PTC is in an interesting time in its company growth. So the company is about 35 years old, and that means it's been through several iterations. And right now it's really going through a digital transformation as a business and really shifting from a software application to a SaaS platform company, right? So CAD—the space that we really specialize in and all things around CAD product, life cycle management, et cetera—is an industry that I would say generally follows many other industries in the shift to SaaS. So we've all been working in Google Docs for many years now; that’s not something our customers have yet done in the CAD design space. Now, especially with the pandemic, that's been incredibly important from an education perspective from distributed workers. We no longer have a computer lab at your disposal to go on and use the software.

And I say all of this is background, because it means we're thinking about a lot of change, not just for our customers, but for our people. It means we're talking about changing skills: so what folks were doing as engineers on software applications, how does that translate to the cloud? It means we're thinking about inclusion and diversity. And so that is obviously a hot topic and something we'll talk a lot about today as that, something that is really just in line of sight for all boards, for all leadership teams—how do we integrate that better into our workforce and make sure that our workforce planning accounts, our programs and projects account for it and make sure that we're really elevating and providing the platform for folks to have equitable experiences?

So lots going on, certainly, and we're a part of it all.

Stacia Garr:

Wonderful. And before we dive in more to that DEIB approach, I do have one question for you because a lot of people are interested in people analytics and what does it mean and the skills you need and the like, and so I just wanted to get a sense from you—what skills do you use to do your work today and how did you acquire them? And then we'll pivot on over to the DEIB topic.

Hallie Bregman:

Yeah, people analytics is a hot, hot space these days. I can't go on LinkedIn without seeing at least a new job posting every single day; it’s really just taking off. And that is so exciting to me as someone who actually didn't come from the people's space. So I think generally, people analytics grows out of one of two areas: either folks who are analytics and data scientists previously, or they're in the people space and they're kind of building in their technological skills. So I come from the former; I was a data scientist for many years on the customer side of things before moving into the people analytics space. And that means that I lean pretty heavily into technology, methodology, measurement. I also have a PhD in clinical psychology, so I describe people analytics as the perfect hybrid of all things that I love: it is people, it is partnership, it is understanding insights and telling stories, and I like to pull that all together. So some days you'll find me in meetings all day talking with people—and I think that's a big part of my job—and other days you'll find me in Python or Vizier or Workday, whatever tool that we are dealing with at the moment, thinking about reporting, thinking about insights, thinking about structuring business questions to help define and develop really cool analyses that might give us line of sight into things that we wouldn't have otherwise.

Stacia Garr:

Wonderful.

Chris Pirie:

Great set of skills; I’m sure you're in amazing demand, and I love your background in psychology and data—fantastic. Can you give us just some context here a little bit: I think you already touched on this a little bit in terms of transitioning to the cloud and to SaaS-based business, but what would you say are the forces at work on your organization that are driving them to take this topic so seriously?

Hallie Bregman:

So PTC has gone through an interesting transition—not just as a company and a business, but also from the people perspective. In the last year, we brought in a new chief people officer, Jill Larson, who's really driven a digital transformation in the people space as well, and that led to me founding our very first people analytics team at PTC. So I am part of an ecosystem that is really thinking about transformation and technology across the entire employee experience; I think that is unique to founding people analytics teams who often come into an established organization with leadership and then are building people analytics on top of that; we’re really, co-developing, co-creating the experience for the employee in its entirety right now.

So it's really an interesting time to be a part of this, and that means that I'm focused on everything. I have my hands in every pot, from thinking about our performance experience and what does that mean analytically, from thinking about our technology evaluations and saying, ‘Hey, this tool might be really great, what are the reporting capabilities, what data can I get out to develop more insight?’ And then on the other hand, I spend a lot of my time answering some of the simpler reporting questions to help get folks to dip the toe in the pool and say, ‘What does this mean? What is data, and is it as scary as it's often perceived to be?’ Helping folks enter that.

Chris Pirie:

That's interesting. I know you've done this work in other organizations, and I wondered how the overall culture, the sort of work culture, organizational culture in your current employer, how does it impact the work that you do?

Hallie Bregman:

I have seen a number of different organizations go through this, and it is incredibly different depending on the organization. And so, as I mentioned, PTC is a 35-year-old company, it's been around a while; that means there are some people here who've been around a while, right? And so that's different from a new hyper-growth company or a startup, or some of the spaces in technology where things are just changing at lightning pace. And so what I found is when the culture is really data-savvy, you can get a lot more out of people analytics sooner. And that doesn't mean that a culture that isn't data-savvy off the bat can't get that; it’s just going to take a lot more of that change management, that thought partnership, and bringing people along on the journey, and that takes some time. It's easy to want to jump into some of the sexy analytics right away, but it's really important to help folks see the value, get used to it, and then start to make the business case to do things a little bit more advanced.

Stacia Garr:

And I would think that's especially the case, you have that with analytics broadly, but when we focus on this intersection with diversity and inclusion, I would think that's even more so the case.

Hallie Bregman:

Absolutely. I think even organizations that are quite advanced in their analytics, if they are not historically advanced in their kind of equity and inclusion efforts, I think we've seen a range of different companies in the last a year with the rise of all kinds of things; we really see that some companies are more ready for it, some companies are in that dip your toe mode, right? We talk about people analytics and getting used to the data, but it also means getting used to saying some things that don't always feel good, seeing some things in the data that don't always feel good, and then being more thoughtful about including that in a process, and not as an afterthought. So a big part of the efforts that I make are building in not just people analytics to the process, but people analytics with a focus on equity in every analysis that we do.

Chris Pirie:

Can you tell us who are your critical partners in this effort?

Hallie Bregman:

I think this also depends a little bit on the company and the culture. So in some companies it's going to be your HR business partner organization—they are often your bridge to the business. They’re the folks who are kind of most adept at understanding the business problems and translating them back to how the employees experience them. I think in some organizations, they're actually going to be the business themselves. So a lot of the leadership within the business when folks are really adept at having these conversations and thinking about things with a data-savvy lens, and also a lot of the champions for DEIB work sit out in the organization. We like not to think that HR or the people team owns diversity—oftentimes that's where the chief diversity officer sits—but we want to be working with the people who can help us escalate and expand this work and build it into business operations, and sometimes those are the people who are right on the front lines.

Dani Johnson:

I have a question about buy-in: DEIB is a scary thing for some organizations, and data is a very scary thing for some organizations—and when you put those two things together, it's very, very scary for some organizations! So how have you gone about either in this role or the one you had before getting buy-in from the different groups in order to convince them that it's really necessary to do this?

Hallie Bregman:

Yeah. And I think, again, that there are cultural differences in how you do this, but I think number one, your best friends have to be your privacy partners, right? Security, privacy; they’re not the people you go to last, they're the people you go to first. You want to have them involved in the co-creation of this work so that they understand the business case, the reason, the security concerns, and how this is going to help improve the employee experience and the business.

I really think about this work as twofold, right? There's lots of research out there showing that the business case for DEIB work is great—that the people that have more women or underrepresented minorities on their board or in their C-suite have better bottom lines. All of that is great, but all of that is very business focused. I think there's also a really important component to this, that is the people, right? The experience of the people. And we want it to be for both reasons. It's if just for the people, the business doesn't have a stake in the game. And if it's just for the business, the people don't have a stake in the game. So I think of this really as a bridge that involves all people. The people we're collecting the data from, the people we're giving the insights to: who is that? Sometimes that is just leadership, sometimes that's the entire organization, but there's a lot of stones to turn over before you can really get started with this work in getting legal and privacy on board.

Stacia Garr:

I love that focus first on legal and privacy. I know we've got some follow-up questions to this, but as you know, we've been doing research on DEIB and analytics, and I've heard a range of approaches from people. And some of them have been like, literally ‘I hate legal.’ They are just so anti! And then they go on to recognize the importance, et cetera, et cetera. But I think the mindset around this: these are partners that we bring along from the beginning to make sure that we do the best work in the way that's most appropriate and that keeps the organization safe. I think that's a beautiful mindset.

Hallie Bregman:

Yeah. A hundred percent. I've done it both ways where I went to them first and I went to them last and I find it to be much more effective. Even if they say no initially, just like you're bringing everybody else on the journey, usually you can bring them along as well.

Stacia Garr:

So Hallie, can you tell us about the types of DEIB questions you're trying to answer, because there's a range of challenges that we have as an organization. So for you, what are you focused on right now?

Hallie Bregman:

There are a range of questions, and again, I think different parts of the organization are thinking about different parts of that range. So I always start with saying, you can't do any good solid DEIB work from an analytics perspective without a really strong self-ID campaign. You have to have who is part of your organization in order to be able to understand and assess equity, representation, inclusion, et cetera. And so doing that from the get-go is really important, but you also can't just provide labels and say, ‘Hey, can you fill this out?’ Because what if the label that somebody identifies with isn't represented?

And the best example of this is always the EOC field for gender, right? This is government mandated, we’ve all reported on this for years. It is male female. Well, we all very well know that there are lots of folks these days that do not identify as male or female, be it transgender, nonbinary, genderqueer. There's lots of different labels. So making sure that you're from the beginning, working with ERG who’s working with the people to make sure there's representation in those labels. Once you're able to then do that campaign, and that's a big part of actually where we're at in our focus at PTC right now, is when you can start to get those rich insights about anything, right? Whether it is who works here at my company, or how does performance compares for different groups, are folks satisfied the same depending on their representation, their identification: are they as engaged? Are they as happy? Are they as happy with their managers? All kinds of questions you can start to think about, but it all really is depending on that self-ID component.

Dani Johnson:

How do you go about getting that information?

Hallie Bregman:

Yeah, it's a tough one. In some places, I know companies that are like, yeah, let's ask everything: sexual orientation, religion, caregiver status, the fundamental to that. Everybody asks again, these are government mandated in the US: gender, ethnicity. We got that. Now we know we have to improve on the gender question, but then what else are we going to ask? And so again, I think this is partly a technology question: so what can your technology support you asking? Are you going to do this in a survey form? Are you going to do this in an HRIS system? What is legal comfortable with you asking, what compliance: different industries have different regulations, so there's a little bit of gray area here.

The other thing is what if you're global, right? What applies with a global perspective? What do you have to target different regions? So I think there's a lot to consider, but generally it's something that is being proposed more and more these days, and we have full support for doing it here at PTC right now.

Chris Pirie:

Can you talk about your approach to, I think what you called in an earlier call, ‘gap analysis,’? I think is like baselining, perhaps. But I thought that was really fascinating how you go by that. Can you talk about that process?

Hallie Bregman:

Yeah, absolutely. So once you have that self-identification information, most people start with just who works here, right? What's our representation like, and I would say until a year ago, that was often where people stopped—we know this is, this is our composition. But I think that there’s really different facets of the DEIB experience. Who works here? Okay. We've gotten past that. That's the easy stuff. Then there's the relatively easy stuff. Then there's the, what do we already collect and ask about our employees that we aren't currently considering diversity inclusion as a lens on? So I think about, again, I always say performance, but that's a big one at a lot of organizations, engagement, inclusion, turnover, hiring—these are all metrics that you're already likely tracking that are a part of your process that you have not yet taken a look at how they relate, how they fall for different organizations for different identifications. It's not at the aggregate.

Let's say our engagement for our company is great: it’s 80%! We're really all happy. And then you're like, well, turns out 80% of my employees are white—so sure we're all happy, but you're not really hearing the voice of those underrepresented groups. And so it's pulling that out, and making sure you have a good sense of where everybody's falling in that range on all of your core metrics before you keep going.

Dani Johnson:

You mentioned looking at the stuff that's already there. We're a really big fan of taking data that's already there so it doesn't cause an extra lift on the organization. What have you seen as the most valuable datasets?

Hallie Bregman:

I think engagement and performance are two of the major ones. And I think this is also culture dependent. If engagement is a once-a-year survey that isn't really integrated into your company culture, it may not be the most important metric to look at. Sometimes, a lot of companies have moved to more frequent pulses, or continuous listening or moments that matter; that’s when I think it starts to be a bit more impactful. From a performance perspective, similarly companies doing annual performance reviews, depends on how much hinges on that. Right? So if pay is based on that, if promotions and internal mobility and opportunities are all based on these processes, they start to be really important to focus on. And so those are the two that I always call to light, but certainly there are others depending on the company, recognition being an interesting one as well.

Dani Johnson:

You mentioned a really interesting thing, which is sort of the time between you collecting data, so engagement and performance generally often happens just once a year in organizations. We have found in our research as well that it takes a while for data to become useful, it’s not always immediately useful. How do you deal with that? And how do you manage the expectations of those around you that may be expecting more from that?

Hallie Bregman:

I think this is all perception, and I sometimes describe it as building the muscle, right? You can get away with, with your employees, asking them for their voice on a regular basis without doing too much to start. When you start doing that on a repeated basis, and then they're like, okay, now didn't I just tell you this, are you asking me the same thing again? Now you start to be like, okay, we either have to talk about the actions we're taking, or if we're not taking actions yet, we have to actually sit back and say, should we be asking this again? Because maybe things have changed with nothing happening, but how meaningful is that? We all moved to remote: nothing happened except for COVID, right, for us all to go remote, but would it have been helpful to ask some of the same things we were asking before, again, once we were remote, if nothing had changed within the company? I don't know; probably not. I probably would have focused more on the things that had changed and that shift to remote in that time. But some surveys will ask a question, did your company act upon this, the results of this survey? And that tends to be a really interesting indicator around response rates and whatnot. It's a tightrope to walk.

Dani Johnson:

You bring up a really good point; if you're not going to act on something that you're asking about, then you're setting expectations that could be very damaging exactly.

Chris Pirie:

Along that vein, I think the sort of interesting question here around analytics to understand the problem and the kind of issues that we have and to get a real deep sense of that, but then something has to be done, right? Action needs to be taken, some kind of programs need to be run. How do you see the role of analytics in the program, design, execution and evaluation? Is that all part of the lifecycle of the work you do?

Hallie Bregman:

It certainly is for me. And I think some of that is my passion for the work and my interest in being a part of the work end to end, but also in the role that analytics plays along the way. So usually you start with a business question, you help answer that with some data and some insights, and then you start to craft a program. And, as you're crafting that program or that response, you have additional questions, and you're like, ‘Okay, so I know this was the insight, but what if we thought about it this way? How would we do that—I can go back and pull in some different data, or think about it a little bit differently, or pull another slice, and have input into that process.’

And so I think when we talk about data-driven work, it's not a 1.1 response: it also, sometimes isn't even a number, right? It is an insight. And so one of the things I say a lot is, ‘I'm not even going to give you a number. I'm not going to give you data—I am totally driven by data, I eat, sleep and breathe it all day long—but I'm going to tell you this story and I'm going to help people build a strategy around that story.’ And that's where I think the partnership work gets really powerful. Instead of focusing on, ‘Well, our turnover rate was this exact number.’ Have we shifted it? Let's think about the big picture: what are we really trying to solve here?

Stacia Garr:

One additional question—you mentioned engagement and performance, and in doing that work and you mentioned recognition—I think that there can certainly be sensitivities when we intersect that with DEIB. We did our first research around performance management and women in January. It was right before the pandemic hit. And I remember at first feeling like, I've done research on performance management for 10 years, and so this question of gender and performance management, I was a little hesitant as a researcher to go down that train and quite frankly, I had no vested interest in whether there were biases or not. But I can imagine that if somebody has been running performance management in a certain way for X number of years, and here comes in people analytics and saying, ‘Hey, you'd probably got some bias here,’ that that can be a hard thing for folks to swallow. So can you talk to us a little bit about how do you manage that relationship, that partnership, with bringing those insights in that story around what's happening here to folks who certainly haven't looked at this before and may potentially have some sensitivities around it?

Hallie Bregman:

I think we all feel ownership over the work that we do and we want to believe that we've done the best work we possibly could. And I also think that's a little naive, right? We've, we've all realized that in the last year, especially; I’ve heard people talk about meritocracy—I just actually read an article about a CEO of a well-known analytics platform who said, ‘We're not going to focus on hiring on diversity, even after all this, we're going to focus, hiring on merit, who are the best people.’ Well, that is a very biased statement, because merit is how you measure merit? It's often by pedigree and who has access to pedigree. And so I think changing the assumptions is actually one of the most critical things we can do to help everybody assume there is bias in everything; as good as our intentions are, as good as the work that we have done is, and trust me, we have done some great, great work, there is still more to do.

And so when I think about partnering, say with the person who thinks about performance management, it is not coming at it with a critical lens, ‘We have done this wrong.’ You can make people defensive so easily if you come at them, right, you want to come with them. And so it's, ‘Hey, what do you think we could do better? Hey, let me go look into that.’ And performance and engagement are two ones I bring up a lot because I think there's some really rich insights in the text that comes with those processes. And so they often say performance, you go in, you write this whole paragraph, your manager writes up a whole volume of work on you, and then you get boiled down to some rating. You are ‘meets expectations.’ And I'm like, wow, we just lost so much of the richness of that person, and so can I go in using something like natural language processing to actually look at, are there language differences when we're describing men versus women to go off, the example you shared, Stacia, right? So are we talking about strengths differently for women than we are for men? Are we talking about things differently for people of color than white employees, et cetera? And I think that's where you start to get some of the hard data that's really hard to dispute, right? So when you go back with the performance management group and you show them the results, and you're like, ‘We're seeing this, this is not necessarily the problem of the process itself, but it is the problem of who's filling out the results. What can we put into the process to help work that, to help pull that back a little bit, so that next time we're not seeing so much of that discrepancy?’ It's very much a partnership.

Stacia Garr:

Two things I love about that: one is the systems thinking of it, so we're not putting the blame necessarily on an individual manager or whatever, but we're actually saying, ‘Okay, how do we design the system so that this works better for all?’ Which I think is a meaningful shift. The second that you alluded to is natural language processing, which not necessarily all of our listeners are familiar with but I'd love to talk a little bit more about what that is, because the technology there has changed quite a bit in the last few years and particularly the commercial viability of some of this technology that can be bought off the shelf. So can you explain for folks a little bit more what that is, why it's important and how you've seen it change—particularly as you think about what you have to build in-house versus what you need to buy from external providers?

Hallie Bregman:

I think this is something that's been in the news a lot. I talk about ONA (organizational network analysis), I feel like that's the hot topic today. I feel like NLP was just like a couple of years ago and still has so many interesting applications, but natural language processing is taking words and turning them into insights. So what we often have called qualitative data—the interviews, the texts, the conversation—it's not a number, a number is really easy to analyze. What is the meaning of one, three and five? It's three. There you go. Now, what is the mean of plus minus 106? I don't know the plus or minus, like these are words. So what's the sentiment around them? What is the actual text?

So there's a number of different natural language processing techniques that can do things as simple as count the words: How many words did you use? Then they can count each unique word. So how many times did it say ‘Hallie,’ how many times did it say ‘Blue’? And then you can go on and push it even further and say, ‘Let's talk about the themes. What are the themes coming out of these words?’ Because when I say ‘high performer,’ you might say ‘high achiever,’ and somebody else might say ‘strong potential.’ Well, those words are the same, but we probably meant something very similar. And so that's where I think you start to get some real interesting insight into what's being discussed.

Now, there's some dangers here. When you think about automation with natural language processing, and this has often come into play in the space of recruiting, where we're taking resumes, hoping to run them through these algorithms and pop out models that predict who's going to be the best employee, how we can make this less biased, only to find out that we trained the model on data that was biased in the first place, and so we're perpetuating the bias and the system, right? There are certainly some of those things that come into play that doesn't mean natural language processing is not useful, or isn't productionizable, there's probably some that's possible, but I think we're in a place where we're still learning how to do that in a way that helps take the bias out of the system. But from an insight-generating perspective, I think there's a lot of value when you have that human who can interact with the computer, help add the context back into the computer, and that's a lot of the work that I do.

Stacia Garr:

And I think that some of the most powerful insights that we see, particularly when we look at DEIB, right—I alluded to some of that performance management work that we had done before, and in a lot that was reviewing work that others had done far more laboriously—that was seeing things like more critical tone often towards women, or less constructive feedback, more vague feedback being given to women and then seeing a correlation between vague feedback and performance scores or promotion rates. So, I mean, I think that there's just a wealth of information that we can look at. We were looking at women and the research actually is quite a bit worse for underrepresented minorities, and then you have intersectionality of those and just it gets even worse, but it's at least giving us a way to articulate the problem. And when you tell people to give specific constructive feedback, that is something people can do something about as opposed to just, ‘Hey, women tend to get lower scores, sorry about that.’ Like, that's not, that's not terribly actionable.

Hallie Bregman:

Yep. Another example, when you write a job description and in every job description for a while is saying, ‘We're looking for a rock star or a ninja.’ And we're like, well, that's all gendered language, or ‘We're going to have beer and pool in the office.’ That's all gendered language. And so easy things to tweak to make those a little bit more inclusive.

Chris Pirie:

I think one of the things that we're trying to do with this Season is help leaders kind of understand what tools are emerging and what techniques are emerging to do good work in this area. And you mentioned ONA, for example, you might want to just do another one of your crystal-clear explanations as to what that is, but do you find that part of your role is helping managers and leaders ask the right questions and just understand what kind of techniques are available to them rather than just going to the dashboard and comparing my score to my peer’s score, which sometimes happens, I believe?

Hallie Bregman:

A hundred percent. So I'll start with the second part of that question, which is helping frame the business question: well, it's all I do, it feels like most of the time. People come to me and they want to say, ‘What's my turnover rate?’ (I use that as the routine example), but the ultimate question is actually, ‘Am I seeing an uptick of people leaving because this one manager left?’ They're not actually looking at turnover rate: they want to look at this very specific question and to bring that up to another level: ‘Have I lost team morale? How do I rebuild that, and is this a symptom of it?’ Now I have something to work with that I can go beyond just that, ‘Well, your turnover rate is 15%: you’re like, okay, what does that mean?’ So a big part of it is helping ask the questions.

I always say that you don't want to come to me and say, ‘This is what I want, do this analysis for me.’ I want the question because I know, hopefully, a lot more about the field of opportunity, what the techniques are, what the data is, and can bring different perspectives to it, as opposed to, if you get super, super-prescriptive. Organizational network analysis is, again, a super buzzword now, as is skills, skills, skills! But ONA, or organizational network analysis, actually looks at the degree of connectedness across employees in an organization—it doesn't have to be employees, but that's our use case here. And so what that helps do is figure out using either active, which is generally a survey, or passive, which is looking at calendar, email data, who is connected to who and how frequently are they communicating, who is elevated the most. So, for instance: Is Hallie connected early on to people who are more senior to her, is she connected to people outside of her organization, not just her team but have kind of a broad reach? Is Hallie a single point of failure that everybody always is coming to Hallie, but what happened if Hallie wasn't here? What happens if Hallie left? Right. So there's lots of interesting questions you can ask.

I think one of the best DEIB applications is around, again, kind of strength of network, especially in onboarding—our underrepresented folks, the research has shown underrepresented employees don't get as well connected and they aren't mentored as often, they maybe don't have the reach, and therefore, when it comes to performance management time, they're getting rated lower than their colleagues who had all of that investment. And so this is the place where you might implement a program to help facilitate connection, mentorship, sponsorship, amongst new hires who are of underrepresented status, so that they can develop and build that network, which seems to be a real sign of success in the future.

Stacia Garr:

I think we also tend to see an application of ONA with particular leadership programs that are looking to develop individuals. Have you seen that—can you talk a little bit about what you've seen?

Hallie Bregman:

Yeah, so when folks go through a leadership program, the hope is that they will be successful, they’ll stay, they'll have broader connections. And being able to actually measure that, ‘Hey, here's a group of people, similar roles, similar levels who didn't go through a leadership program; here’s a group of people who did. Do their networks look different, right? Has this intervention actually changed things?’ We're actually hosting a panel. The Boston people analytics meet-up group is hosting a panel on ONA just next week, and I was just on a prep call earlier and some really, really fascinating applications, and it will be interesting to see how this kind of becomes a more mainstream thing over time. Also ethical concerns.

Stacia Garr:

For sure. I think the thing that's exciting, though, is we are always asked the question about how we measure inclusion in particular? And we've been looking a lot at the engagement surveys, and some organizations have a belonging index or an inclusion index, et cetera, but the thing that I think is exciting about ONA and this application is as you can actually see, are they included in the network in a similar way or an equal way, and are they actually getting the access to certain power levels in the organization that we know are necessary to kind of bring people up within the organisation? So I think it's not just a perception thing, but it's actually what is really happening. Of course, security concerns, but I think the opportunity for a really good inclusion metric is here.

Hallie Bregman:

Absolutely. And I think this is one inclusion metric that I would actually support being an inclusion metric. I often really dislike when folks are like, let's have a diversity scorecard, or let's have a diversity metric, because I think what it does is it silos it—it takes it out of the general set of metrics and things folks are looking at on a regular basis. That doesn't mean that you shouldn't look at some of these with everything else, but I don't like that there’s so many diversity scorecards right now. I feel like I get another email every other day, this one's got a diversity scorecard, that one's got a diversity scorecard. And I always say the things on those scorecards may be interesting and helpful if they were in the context of the general business and the general employee perception; I really hate the silo approach that often happens in this space.

Dani Johnson:

It's a really interesting point, and it takes us to our next group of questions that we want to talk about. How do you make DEIB data usable? And one of the biggest questions that we have there, DEIB data can be very scary for lots of organizations. So how do you communicate it broadly, and who gets to see that data and what kinds of considerations are made with respect to that?

Hallie Bregman:

I think this is another question that comes down to culture. I also think this is a space that is moving, moving rapidly, in general especially with the human capital disclosures that have been mandated since last year. And I think we've seen in this first year of disclosures focus on disclosure too much but I think we're looking towards that. I think, going back 10 years ago when Google and Facebook and a couple of the bigger companies started posting their diversity reports on their websites, they were disclosing the makeup of their organization. That was about as far as it went, and I think research has shown that generally just doing that, doesn't actually move the needle. But we actually, and I especially have this philosophy, that everybody's a part of this. And I don't really believe in the idea that this is a secret and we're gonna keep this to ourselves. There are certainly legal implications for some of this getting out. And so you can go as far as you can go. And I think we're going to keep pushing the legal boundaries of going further and further. I know internationally, and there's some really interesting pay equity regulation in Germany, where folks can actually request and get access to kind of their pay compared to folks in similar roles. And obviously not identifiable, but generally something that they can actually see: ‘Wow, I am being underpaid. Wow, I am being paid fairly or paid similarly to others.’ There's a lot of this black-box effect that makes people question how things are going because they just can't see it. And so as much as I can, I believe that everyone sees something. Some people see everything, but everyone sees something. And whether we start with representation, who's at this company, who’s here, what am I giving? And then we start to go a little bit further. Actually, we're going to show you engagement scores across the company for all of these different underrepresented groups—again, never identifiable, but showing, ‘Hey, folks aren't feeling as good if they are of certain identities.’ Again, that's how the industry is moving, especially driven by these disclosures.

Dani Johnson:

I love the idea that everybody sees something. We're all about pushing data down as far as you can, and that encompasses everybody seeing something.

Hallie Bregman:

We actually use a platform called Vizier, and every single person in my company has a seat, and I did that upon immediate launch, so we did not start with the top and then roll it down. Launch went to everyone immediately. And that was really important. Now, obviously there's different security models, there's different regulations, but everyone got a seat at the table on day one. And I think that's really how we want to think about our employees, and particularly in the inclusion space.

Chris Pirie:

You're really making me think about trust and how important trust is in the overall journey, and at all levels. That's really, really interesting.

Dani Johnson:

You talked a little bit earlier about the story, and I loved that: not everything can be reduced to a number, so tell the story around it. Talk a little bit more about that. Do you tend to get push-back when you're just telling a story? Do people embrace it?

Hallie Bregman:

So I think this is partly why I actually gave everyone a seat at the table, right? So if they need a number for reporting purposes, they can go get that number themselves. If they're coming to me and my team, we're really going to be focused on insights and story. And I think if you tell that story well, usually there are some numbers that are part of it, but not always—depending on what the story is. The folks are much more interested in what that story is than what the number ever was, right, unless there's some crazy benchmark they have in their head, which benchmarks, they are whole another problem in many ways. Folks are really receptive to telling a story and it also humanizes it. If you can bring it down to ‘Let me tell you the story of Hallie and what her experience might have been like. Well, she might have come in, she might have experienced being connected to a couple people, but not enough, and so she wasn't super happy; she wasn't getting projects. Therefore, her performance suffered; therefore, her pay suffered, and after a year, she left because things weren't going so great’ You can kind of put a context to it. And when somebody thinks about a person, we all know how powerful the story of a person is. If you know a person who's gone through an experience, almost universally, your perspective changes on that experience. And so, I think that's really where storytelling comes into play. I think it's something that we hear a lot in the people analytics space Just about every interview I listen to, people are like, ‘I'm telling the story, I'm telling the story,’ but I think it is so true and so important to this work that it's worth saying every single time.

Dani Johnson:

I love that. In particularly, in the DEIB space, it has to be humanized or it doesn't have any impact at all. A number is very impersonal—a story actually promotes change.

Hallie Bregman:

A hundred percent.

Stacia Garr:

And I think that one of the things that's been the most interesting is in some of the research we've been doing, a lot of the people who are the women or underrepresented minorities have talked to us about their experience. And it's kind of been obvious why they're interested in this topic, but on the flip side, we've also had a lot of white men who are also interested in this topic. And I think every single one of them, at some point, unprompted, in these interviews have said to me, the reason I care so much about this is because either, typically I'm the father of a couple of daughters, and I want this to be better for them, or I've watched my wife struggle with this, or I have a friend who I saw go through X, Y, or Z thing: it’s always someone very close to them and it's always very personal.

And so if we think—to Dani's point about this, in the DEIB context—making this personal, about real people to whom these things are happening and that you feel a connection to, even if it hasn't happened to you—it completely changes the conversation.

Hallie Bergman:

It's definitely super impactful. And if you've gone through something similar yourself that you can relate to even more so.

Stacia Garr:

We’re going to move on to another question about this communication side of things, and it's really about managers and what do you wish that managers and senior leaders knew about this data and how to leverage it on their DEIB journey?

Hallie Bergman:

I think last year, right when George Floyd was killed, I had never had so many requests for diversity data—I need the diversity data. And I wanted to look at everybody and say, ‘You know your teams, right?’ Me showing you this data, isn't going to change it. But also what are you going to do with diversity? Like, I can show you, ‘Okay, we've got some people here.’ What are you going to do? How is that going to help? And there was a lot of interesting discussion around, ‘Well then, what do I need?’ And ‘Oh, if we don't have that yet, then how am I going to get that—we need it right now.’

And I spent a lot of time helping folks understand that slowing down was actually the best thing we could do, and be thoughtful and look big picture and think in partnership with our chief diversity officer, with our broader teams—our chief diversity officer came in after that, so it wasn't always there to begin with—but I was like, well, you're doing the same thing that this other group is doing and they're wanting the same thing, so how can we leverage each other? How can we build experiences that are centralized, standardized and customized?

Not to say that everything needs to be customized a little bit. Oftentimes there are needs, but sometimes there aren't. And so I think helping people see that, well, what do you want to do? And how can you help your team? And then how can you help the organization? Is there something unique about your team's experience that we need to target, and let's figure out what data we have or can collect to help understand that, or is there something similar about your team, right? That is like other teams in the organization, and can we partner and bring everybody together to again look bigger picture?

One of the biggest, biggest challenges in this work is sample size. So by definition, underrepresented minorities are small, right? And so we do not have volumes and volumes and volumes of data. And when you start to slice and dice, ‘Hey, I just want this team, I want to know all these things.’ And I'm like, you've got a sample size of five; I can't give that to you, we can't do it! And so it's taking that. It's helping helping bringing people along, but not just throwing the data at them to shut them up.

Dani Johnson:

It sounds like you do a lot of counselling!

Hallie Bregman:

Maybe it's why I'm a psychologist.

Dani Johnson:

I think that combination is actually really powerful.

Hallie Bregman:

It's an interesting space. I think I also just wanted to say, Stacia before, you mentioned something about intersectionality, and that that's another one that I'm thinking about the size of the data and everybody's like, we gotta do intersectionality—yes, we do, and we have to be able to trust really small sample sizes if we're going to be talking about that. So if you're going to say ‘Well, but this is only three people?’ then why did you even ask me for it in the first place? And so it's helping people see that, that three people, may only be three people, and that is certainly not big enough to be statistically significant, whatever, but it's three people's experiences. And if we're going to build and add a fourth person with those identities and add a fifth person with those identities, what are we going to base them off of? Let's start with the three people we have.

Stacia Garr:

Yeah. A lot of requirements for flexible thinking.

Hallie Bregman:

Absolutely.

Stacia Garr:

To start to wrap this up—I see our time has amazingly floated away!—can you tell us, are there any organizations out there that you admire in terms of how they're approaching this topic of DEIB and analytics?

Hallie Bregman:
I think—probably to beat a dead horse—at least in the Boston area, HubSpot just shines: their head of people analytics, Vincent Greco, is amazing, Katie Burke, their chief people officer, is amazing, and they paved the way for so much of the work and so much in the inclusion space, especially in this area, but I think well beyond the Boston area as well. I always keep an eye on another great company in the Boston area, Rapid7, very culture focused. I definitely admire.

Stacia Garr:

Wonderful. Is there anything we should've asked you about today that we didn’t?

Hallie Bergman:

Oh gosh, a million things and nothing at all; I think this has been so fun. It's really a conversation that I could just have all day long because I feel so, so passionately about, and I'm so excited to be a part of the transformation in this space and hope that in five years we can all sit back down and look at how much we have done in thinking about inclusion in the employee experience.

Stacia Garr:

Absolutely. Well, how can people connect with you and your work?

Hallie Bergman:

Yeah, so LinkedIn, I'm a big LinkedIn fan, so feel free to connect with me; I try to post as much as I can, but I always love connecting with others so definitely reach out, shoot me a note.

Stacia Garr:

Wonderful. And then our final question for all our podcasts is really related to purpose, and I really want to ask why do you do the work that you do?

Hallie Bregman:
It's a great question. I just feel so passionately about employee experience. And I think the data, the culture, there's lots of components that go into that, but I think I feel passionately about it because I am an employee, and I relate very much to it. And I understand all my peers and relate to them, and I think a lot about how we might make this a better way to work for everyone—not just those of us we can reach day-to-day.

Stacia Garr:

Wonderful: Hallie—thank you so much for joining us today; it has been our real pleasure to learn a little bit about you and your world, and thank you so much for being so generous with your time and thoughts.

Hallie Bergman:

Thank you so much for having me.

Stacia Garr:

Thanks for listening to the 'Workplace Stories' podcast, brought to you by RedThread Research. Share your thoughts or ideas for guests and topics by sending an email to hello@redthreadresearch.com, and consider sharing your favorite episode with a friend or colleague. As always, thanks to our guests, our sponsors, and thank you, our listeners.

Chris Pirie:

We’re very grateful to the people at Workday for the exclusive sponsorship of this Season. Today, the world is changing faster than ever. Meet those changing business needs with Workday; it’s one agile system that enables you to grow and engage a more inclusive workforce. Workday: the finance, HR, and planning system for a changing world.

Workday will also host an exclusive live webinar at the end of this Season, where you can meet the team (Dani, Stacia and myself) and join in a conversation about the future of DEIB in the workplace. You can find out more information, register for the seminar ,and access exclusive Seasoned content, including transcripts, at www.redthreadresearch.com/podcasts: and thanks again to the team at Workday!

Written by

Dani Johnson

Dani is Co-founder and Principal Analyst for RedThread Research. She has spent the majority of her career writing about, conducting research in, and consulting on human capital practices and technology. Her ideas can be found in publications such as Wall Street Journal, CLO Magazine, HR Magazine, and Employment Relations. Dani holds an MBA and an MS and BS in Mechanical Engineering from BYU.

Stacia Garr Redthread Research
Stacia Garr
Co-Founder & Principal Analyst

Stacia is a Co-founder and Principal Analyst for RedThread Research and focuses on employee engagement/experience, leadership, DE&I, people analytics, and HR technology. A frequent speaker and writer, her work has been featured in Fortune, Forbes, The New York Times, and The Wall Street Journal as well as in numerous HR trade publications. She has been listed as a Top 100 influencer in HR Technology and in D&I. Stacia has an MBA from the University of California, Berkeley, and a master’s degree from the London School of Economics.

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