18 August 2020

People Analytics: Aligning to Business – Q&A Recording

Stacia Garr
Co-founder & Principal Analyst


  • This Q&A call addresses the importance of business and people analytics alignment.
  • Question: What are Data Ethics?
  • Question: Legacy Corporate Systems versus Small Vendors?
  • Question: How can people analytics measure Skills?
  • Question: How should orgs apply people analytics during COVID-19?
  • Question: What about APIs and non-Traditional data sources?

In this week’s call we discussed the important role of people analytics in organizations. We grouped questions into three areas around people analytics: business alignment, tech, and COVID-19. We  reviewed the five pillars of business-aligned people analytics and discussed recent trends in organizations. We touched on data ethics, which is an increasingly important topic.

There were many great insights shared on this Q&A. Thank you to everyone who attended and participated live. We hope you join us for the next Q&A call. https://player.vimeo.com/video/447568466

Video Contents & Questions Asked

You can jump to the following locations in the video using the timestamps on the video and in the chapters menu (next to the full screen icon).

  • 0:00 Introduction
  • 03:58 Overview of Questions
  • 05:27 Business Aligned People Analytics Summary
  • 07:02 Five Pillars Research
  • 23:22 Trends in People Analytics
  • 30:32 What are Data Ethics?
  • 41:10 Legacy Corporate Systems versus Small Vendors
  • 45:21 How can People Analytics Measure Skills
  • 51:05 Applying People Analytics During COVID-19
  • 54:56 APIs and Non-Traditional Data Sources

Q&A Call Transcript

Introduction (0:00)

There we go. Alright. So for those of you who I haven’t met on Stacia Garr, Co-founder of RedThread Research. So, since you’re here, you probably know who we are, but we are human capital research and advisory firm. And today we are going to be covering this topic of people analytics. So I’m joined today by Priyanka Mehrotra. Priyanka, do you want to introduce yourself. Hi everybody. I’m Priyanka Mehrotra. I am a research leader at RedThread Research. So for those of you who haven’t joined these calls before this is actually our third one, and this is something that we started really as kind of a trial over the course of the summer in advance of the launch of our new membership in the fall.

And the purpose of these calls is to really kind of have an informal conversation about some of the questions that we get about the research. And some of the things that we’ve heard from you that you’re interested in talking about, but then also to kind of, you know, use the research as that foundation of the conversation, and to build it out, and bring you all in, to get your perspectives in on some of the questions that are top of mind for all of you.

I mentioned the research membership, so we are actually going to be launching that in September. And so these calls will be a part of that research membership. And there will be one more that’s free before the membership actually takes place. And, and basically what we’re doing with the membership is just putting in place a relatively small paywall so that we are able to continue to fund the research.

To date we’ve been using a sponsorship. And so we’ll probably still be doing some licensing of the content, but we want to kind of move to a broader base of support. Because number one, you know, one of our biggest priorities in launching RedThread was that we do unbiased, high-quality research. And so the membership will allow us to do that. So that’s kind of where we’re going. But if you have any feedback on these calls or anything we can do to make that type of membership more valuable, please go ahead and let us know. So, with that one to go ahead and first start with some housekeeping.

So Priyanka, can we go to the next slide? And for those of you who have been here before, like I see Max, he’s been here before, a few things. One is we’ve been trying to make sure this is a safe space. So this, you know, there isn’t any, any judgment here. We’re really just trying to kind of come together and share ideas and to learn from one another. We ask and as part of that, making it a safe space that you, you can certainly share some of the ideas that you’ve heard from here. But as, since you don’t kind of generally specifically attribute them when you’re doing that sharing we do, however, I should say put the recording of this on the website, as well as the transcript, but we don’t identify in the transcript who, who said what? So want to make it a safe space.

Second, share your ideas. As I mentioned, a few moments ago, that’s really what makes these calls work is people sharing your ideas. And as part of that, as I mentioned for those of you who first joined, we ask you to turn on your video, if you were able. I understand that as, as we were saying, some of you are not able to, but it just makes it a little bit more personable and makes it easier for folks to connect. Along with that we ask that you say your name and your organization before the first time you speak, just so people have a sense of kind of the perspective that you’re coming from.

You can certainly raise your hand to speak there’s that capability within zoom, but also you can, you know, I’ve, I’ve got a decent view of, of you all, so you can also just wave or just unmute yourself and start to talk when there’s a good break. And then also I want to encourage you to participate in the chat. I have the chat up. And so if you’re not able to jump in for whatever reason, you know, screaming children or dogs or cats in the background I’ll make sure that I’m following the chat and we can incorporate that as well.

Overview of Questions (3:58)

All right. I think that’s all that I had. Priyanka. Did you have anything? No, I think they’re good to get started now Okay, perfect. Alright. So next slide. So we had just received a number of questions. We’ve grouped them into these four buckets. So, the first being around business alignment, second round tech, the third round COVID-19, and then finally around ethics. So, I should maybe start by just sharing the, kind of the perspective that Priyanka and I bring to this has been our focus on people analytics across the last two years of RedThread.

So our focus on research has been in people, analytics technology. We’re in the middle of the second version of that study right now. So getting vendor demos and briefings, literally every day, many of them multiple times a day, I think we’ve got two later today. And then also we’ve been doing a series of interviews about the role of people analytics in business alignment and responsiveness, and really kind of the org of the future.

So, which we’ve been said, the org of the future is now the org of now. So, we published a study an article just yesterday on that particular topic. And so we’ll cover a little bit of that today. But again, this isn’t a webinar, this is a Q & A, so we’ll share what we have and then we’re looking for you all to kind of jump in. All right. So then Priyanka, why don’t we dive into the first Q&A that we got?

What does Business Aligned People Analytics look like? (05:27)

First Question: What does business aligned people analytics look like, and just to add a little bit more detail into that, how do you think successful organizations are doing this? Yeah, so this one, I think really aligns pretty well. Priyanka, if you want to go, I think it’s on the next slide to this study that we released back in June. And this was a study called the five pillars of business aligned people analytics. And we did not put, we did not put this question in guys like this really came in from somebody it’s not like a ringer, you’re thankful for it. And so so what we, what we learned in that study was a few things.

One is that a lot of organizations, and even though I think it’s close to 80% of large organizations have the people analytics team, we know that most of them say that it’s not as effective as it should be. And so when, and in what they’re doing right now is kind of on the left side of this bridge, which is this ad hoc data reporting. We then talked to, quite frankly, some of the smartest people analytics practitioners that we know, and tried to understand what it was that they had done.

And what was interesting, and I guess someone expected is that none of them started off really with this kind of great executive mandate and, you know, this sense that they were truly business aligned. They all kind of started on the left hand side of the, of the bridge. And some of the things that they did to get to the right, are the five pillars that we have here. So I’ll give just like a 20 second overview of what those are and then maybe pause and kind of get your alls’ reactions and thoughts.

Five Pillars Research (7:02)

So the first one we say is be a business partner, and that one seems terribly obvious, but what we actually meant here was don’t just be trying to align to the business, actually be a business owner. So meaning coming to the table with thoughts that are at the same level as the part of the business that you’re serving, having new ideas, really understanding the P & L of the business and what makes a business tick.

And so, if you have that understanding saying, okay, you know, I know that in this part of the business, you know, product is what, you know, these particular set of product managers are, what drive the business to its success. So here’s what I’ve done to understand what’s happening with these product managers.

Just as an example, or, you know, in a different part of the business, it might be marketing that really is driving the success, but really understanding what, what are the levers of the business, why they’re important and then focusing analyses and insights on those levers without always having to be kind of told, Hey, well, would you go and do this analysis for those parts of the business? So that’s what we meant by one, two was think like a sales rep.

And this was maybe I think my favorite finding from the research, which was not that you should, it’s not just a matter of going in and saying, “Hey, we can, we can do these things for the business,” but one of our interviewees talked about mapping out the business mapping out who is in the business, the impact that they could make on the business broadly and the things that mattered to them, and then focusing on those people first. So really like a sales rep going in and opening up a new business that was critical to kind of getting people analytics, traction to being able to drive business results.

The third one is delivering products, not projects. And so I think we’ve been hearing this one increasingly in the people analytics space for awhile, which is this idea that when we take on new projects or new work, excuse, they need to be scalable. So it’s not a single product project, but actually a product that will be continually used over time and can be incorporated into business processes.

The fourth being provide context-specific decision support. So that means, you know, just getting that greater level of granularity in terms of what the business needs and not trying, not providing kind of general, “Oh, across the business broadly, this is what we need.” But instead having a bit more of a laser-like focus on different parts of the business and understanding when things change, what the differences should be for the business should do. And then fifth being democratized, personalized insights. And you’ll actually see this thing show up again in another piece of research. So one that we launched yesterday, which is this idea that you need to be taking advantage of the scale of the business. And, and the fact that you have people throughout the business, who can make really important decisions if they have the right data and making that information available to them to make those better decisions. So that certainly is managers, but it’s also employees increasingly.

So I know those longer than 20 seconds, but that has the overview of what we learned from this particular study. Does anybody have any comments or thoughts on what maybe resonated with you or things you’ve seen come alive in your own work or practice? Yeah, I think for me, maybe I can speak. I might’ve missed introductions so briefly I’m, I’m head of people analytics at ICRC. And I think for me out of these, the biggest challenge is number three because I guess where we are is a pretty standard maturity level where yeah, our customers are not yet fully on top of their, of their data.

One of the questions they want to ask an answer to the point that they come to us with a very mature request. So very often as we answer the questions that they came with, we find the question on the way. And yeah, we, we, we cannot start by delivering a product. It has to be a project first where we, where we find we better understand what they need. And at some point after a couple of months after a couple of iterations, it becomes something that could look like a product. Yes. And, and for you, what does that kind of process look like? Cause I think that’s pretty common of what people experience, right. If somebody wants a specific answer and then you kind of have to figure out how do you do that scale-ably across the organization. So what does that journey from the individual question to potentially more of that productized version look like for you?

Well, first of all, I have to say I’ve been two and a half months in my role. So I was in the international committee of the red cross previously, I was in Nestle. So it’s a it’s, I don’t have a process yet. And I think it depends a lot on who you’re speaking with because some parts of the HR organization are more mature and they might already have done things on their side and they come with something that’s already pretty, pretty mature and pretty advanced. And then you can answer more, more effectively and more quickly come to a product. But I think there’s a couple of things that that we learn. I think when we, on people analytics to try to clarify as early as possible, when you start a conversation with someone about a question that they want to answer such as: what data do you have? What data are we going to base this on? And how solid is this data source? Who’s going to be my main point of contact with you as we, as we go along and explore this this issue to make sure that the data we use is correct and that the answers we give are business relevant? And eventually what is the end product looking like? Is that just a one-off question that you’re asking now? Or is that something that you’re going to need to answer on a regular basis? So I would say in general, the more you can flesh out these questions at the beginning of a project, the more you can start off the right way and save a lot of time later. Yeah. And then in the article we just published yesterday, we talked a bit about ABN Amro and how they do this.

Priyanka. Did you want to share a little bit of their story about how they do the the contracting process and how that can help with delivering products, not projects? I was actually thinking about a different example in my mind, but what actually came to me when you were talking about asking questions in the beginning of the project, my instant thought went to Kraft Heinz because this was a recent example that we heard. And that was specific to context to COVIC specifically. And though they spoke about it specific to COVID. I think it applies more naturally through all project cycles and initiatives that people analytics are taking, which is in the beginning, before you start undertake any data collection, data analysis project. You talk to the leadership to understand why exactly are they looking to collect that data, what are the insights that they’re hoping to get out of it, and what is going to happen with those insights. How actual those insights going to be, what is the value that employees actually get going to get out of it? So having that clarity in the beginning, not only puts a lot of shows thoughtfulness going into any initiative, but it also helps clarify the process through the way as well. I think that that’s a very important point that you brought out. Great. How about others? What else, what else kind of jumps out at you from this? Or is it a particular challenge?

Max Blumberg consultant. Most of the clients we’ve worked with them. This is from having people analytics for four more years than I care to remember long before it was called people analytics. I thought I was doing my first project. I, I thought it was a PhD research question that I was answering. And I’m really pleased that I haven’t lost that perspective because that is how I still look at, you know, I’m just solving it. But I find that just to go back to a Priyanka’s idea there about speaking to the executives, the Kraft Heinz example, is that we really increasingly insist on going back to corporate strategy when we’re doing it. And we get a lot of strange looks and a lot of pushback, and we even lose clients at that point. But we know from experience that unless the people analytics strategy, is aligned with the corporate strategy, you’re going to do some bad things. And people say, well, you know, what, what relevance, you know, maybe the HR strategy needs to align with the corporate strategy. But people analytics. And there are some really obvious points of alignment. One of them is what are the core competencies and the non core competencies of the organization. So if you spend your whole time fixing engagement and attrition with art looking to see, is that a priority? You know, is it more important than innovation? You know, yes, it’s costing us $30 million a year. Yeah. Lack of innovation is costing you a a hundred million dollars a year, you know, which is even more.

But people, analytics folk are often afraid to look at that. We go for the familiar engagement retention, maybe a bit of productivity if you’re brave, stress, etc. So my view is that I agree exactly with what you say. I would be more explicit and say, go to the corporate strategy. What are the core competencies? And here’s a great example, by the way, I had one very large, well known brand name. And the head of people, analytics took it to heart and went to the ex-co and said, you know, I’d like a list of, of our core competencies and non core competencies. And they didn’t the company hadn’t actually articulated a list of those. And this guy, he was a guy, took it on as a project was promoted through the organization for it saying, you know, wow. And, you know, the ex-co was saying, we’ve never said that, and here are them. And then from Bose, he ensured that every people analytics recruitment. So if a core competency, if you’re in a development house like Microsoft, you know, presumably developers that are developing Windows 10 or your operating system, or a core competency for you. Therefore your recruitment processes, that address programmers are really critical. Whereas those that address your transactional financials are not core. So you can’t just have one recruitment process for everybody, if you want to get into the core, non-Core. So there’s a great idea for understanding what is at Microsoft: programmers right now. We have a whole suite of people analytics project. So that would be my input go even higher.

Yeah. I have kind of two add-ons to that. One is I think that you speak really well, Max of the the difficulty I think that people analytics has. Because it kind of rests in this uneasy place where often it reports into HR. But you know, when I take off my people analytics hat, and I put back on my HR and all the research I’ve done over the years on HR business partners, and HR operations, and you know, everything else. I mean, we spend all the time talking about how, you know, HR itself isn’t aligned to the business, or has challenges aligning to the business and the terribly hackneyed phrase of having a seat at the table and all the rest of that. So if you think of people analytics to your point, trying to align to HR strategy, which we already spend all this time saying it’s not often aligned to what the business is doing.

It’s highly likely that people analytics is going to get itself into trouble because of that. Now we, the uncomfortable place to your point, I was just, if you go around and essentially around them and you go to the business, people analytics has to deal with the politics. Obviously, if the relationship with HR while trying to pursue kind of what is potentially what is most valuable for the business. So it’s a tough place to be, I think, is the thing to acknowledge. But you know, when these conversations that we had, and this is actually, I think it’s going to be the final article that we’re going to do all these interviews, we’re going to talk about the people analytics operating models and what those reporting relationships maybe should look like or how you should think about them differently. Because I think that’s critical to people analytics success is understanding how to manage those relationships.

There are two companies and I can mention one because you’ve mentioned it already, ABN AMRO, and another one that are kind of saying we are, if business partners aren’t, this is about going around HR and going wherever you need to go. People analytics functions, firstly are pulling themselves slightly away from HR, number one, which is no bad thing. And secondly, they’re saying if business partners, aren’t going to give us the information we won’t, because they’re not sufficiently analytical and elicit quantum, but that is not a requirement you need to be analytical is a requirement. Then we’re going to create our own, and I’m seeing a new job title in at least three companies now called a people analytics partner. And that’s interesting. So the people analytics partner does what the business partners should have done.

And people are saying, well, maybe business partners are on the wrong part of the business, maybe they need to be in the people analytics part of it. So that just speaks to your question. That’s how they get around the HR restriction. Yeah. Yeah. And I’d say one thing really quick. Yeah, no, you probably want to move on to. We’re fine. We’re good. Okay.

And I’m Kristy Muir year for those of you who don’t know me with Instructure, I head up strategy and operations. But I like this, this dialogue between Max and Stacia. And as I said, as I think about data strategies, I was just reading the four worlds of work in 2030, this global workforce of the future report. And it was really interesting because I think that as we see more people, analytics, strategies grow and develop, I think we’re going to see, I think we’re going to see different strategies. It’s not going to just be, you know, one size fits all. And I think that, you know, you have companies that have an innovative corporate strategy and it’ll align with that. You have companies who have like a people matter most strategy, and it will align with that. You have people where, you know, maybe they’re you know, like a code of boxy or they’re doing good in the world. There’s, there’s just so many different strategies. And that really, that report got me thinking a lot in line with this, as well as just to what the future of those HR analytics look like, people analytics look like and how all of the strategies are not like it’s not going to be a one size fits all. And I think it’s going to determine a lot of, even the future of HR tech landscape of the future of that.

Yeah, I completely agree. So one of our interviewees for this particular article actually said that the era of one size fits all is dead. Data moves us beyond best practices to practices that we know based on scientific evidence work in our organization, in a particular context. And so I think that is speaking exactly to what you’re saying, Kristy. There may be, you know, even to use Max’s example, you know, within Microsoft, there may be one part where you have a focus on, on innovation. You know, and then you’ve got another group that’s just like trying to keep windows operating for all of us.

And the skill sets and the way that you manage telling those different parts of the businesses is different. And so, you know, I think the data provides us now the ability to do that much more effectively than it ever did in the past. But if we’re stuck in the old model of quite frankly, models that are just kind of, you know, summaries and really straw men to get us started, or straw women. You know, that is a, I think we are then under-serving the potential that data has to help us make better decisions. What was the, what was that article? I was looking it up. I hadn’t read it. I was just on your website. It’s the five pillars here. I’ll pop it in the chat. I’ve got it. Okay. Thank you. Yeah, absolutely.

Trends in People Analytics (23:22)

And I think in the interest of time, we should probably move on to the next question. So, the second question we have here is what the major shifts and trends are we seeing? So we, I mentioned these interviews that we’ve been doing, and basically we started the beginning of the year. Everybody’s muted, maybe. Sorry. Okay. So we started at the beginning of the year and with this study, where we were like, okay, we had just finished the responsive organization research, which I I’ll talk about here in a moment, but we knew that people analytics was an important component of the responsive organization. And then when we talked about the responsible organization, is all about how organization now, mind you all, this was January. Okay.

What the research was all about, how organizations can respond to volatility and change, because, you know, we’ve been talking about volatility and uncertainty and you know, all this complexity for years. And so we did this study and so we was people, individuals. So we started these interviews. What’s the future of work? What’s people analytics role in this? And then COVID hit. And we said, you know, the future of work is not the future of work, it’s really now. What we thought was all this need for being able to adjust to volatility and changes now. And so that is what this piece of research really looked at. And so, you know, what we thought was something we were going to be talking about happening in five years. So I started happening at this moment. So what, what we found here, if you want to go to the next slide, Priyanka is this, this model of responsivity. And so when we talk about responsivity and gonna go ahead and pull up the definition, make sure I tell you guys, right. What we said.

So, responsivity is: the ability of organizations to recognize trends in their operating environment and effectively turn possible disruptions from those trends into a distinct organizational advantage. And so we said, okay, well, what does that look like? What do organizations that do this well do. And so we found four lenses, which are there on the bottom: respect, distributed authority, transparency, and growth, and then trust. And for this particular piece of research, we said, how does this especially apply to people, analytics leaders? What should those teams be doing in order to meet these changes and trends that we’re seeing happening with COVID? But also, I mean, we’ve had black lives matter, you know, we’re only in August, I’m sure we’re going to see something else major.

Cause it seems like that’s what 2020 is all about. So it’s really, you know, how can people analytics help us respond to that change as you can see here, you know, each of the specific things and some of them aligned to what we just talked about with regard to sharing information, that’s, that’s distributed authority. But also a lot about transparency and growth. How do we provide information to people broadly and then give them a supportive environment so that they know that they should grow and have the ability to make decisions. And then on kind of both sides, we have respect, which is making sure that employees feel heard, which we’ve heard a lot about during COVID. And then trust making sure that people feel like they’re part of the community. And so in this research we talked about how does people analytics do this. I just, again, to be so Priyanka, doesn’t keep yelling at me. I’ll stop there. Is there anything here you guys want to talk about in terms of what we’re seeing with regard to how organizations are responding to this moment? Or have you seen any examples of this happening in organizations?

I am seeing the pallet devolving to a very small number of people in most organizations. So, organizations are discovering that they can get the same amount of work done with one third of the workforce where people are being, especially from group or corporate perspective. And I guess that makes for much better responsivity when you’ve got a smaller team, that’s my observation.

Max, do you think that is happening because of you know, just to be blunt where many organizations are reducing head count and therefore you know, it’s just a consequence of having fewer people around? It’s an accident. It’s a shocking, but accidental discovery. I don’t think anybody was expecting if they just said we can’t afford to keep this many people on. So do you know the usual systems people put on know one, one half of salary or whatever it is for a period. And then we’ll let you know, at the end of four months, what’s happened to footfall, etc. And the core team were told, get on and do as best you can.

Folks will understand if performance isn’t what it was. Performance didn’t decline at all. As far as the group processes where it was a real shocker, it was a shocker to me. Apparently it wasn’t a shocker to all the companies, but to some people at the companies saw it. But so yeah, it, wasn’t, it’s a great example of a kind of an A/B experiment unintended. You know, cause you couldn’t have done that at any other time, but it’s amazing. So small teams create great responsiveness at the best of time. So maybe the lesson in here is something about smaller, more proactive teams, something like that, or for people analytics. Yeah. One of the companies we interviewed and we can’t say who they are. But they basically have a people analytics leader embedded with most of the business. It’s an incredibly organic organization in that they they kind of have a centralized people analytics team, but it’s, it’s not that big. But really instead what they do is they basically have all these people analytics leaders out there in the business. Because the idea is that people analytics so core to how you run the business, but you can’t have someone who’s kind of only tangentially related. But, but the second part of that is they believe that these small teams need to make the decisions.

And so that’s why you have to have the people analytics leader there. So kind of the it’s not one of the things we talked about this with this research was how we’re moving potentially away from an incredible focus on just efficiency for everything and instead more towards responsiveness. So things that we may have in the past thought were inefficient, like having a number of small teams, where there could be redundancies in our new world, they can make us more responsive. And ultimately that may make us more efficient. But it’s a very different, you know, distributed way of thinking about things versus the hierarchical way, which for the last, you know, 40 years we’ve said, that’s the most efficient way to run a business. So it’s very much a mindset shift.

What are Data Ethics? (30:32)

I have a question.

Yeah, Kristy. One thing that I actually think a lot about you have under respect, keep the people in people data and under trust, ensure data ethics. I think so much. And I think even going back to your previous slide, there’s no one size fits all and how the corporate strategy works. There are absolutely corporate strategies where it wouldn’t keep the people in people data. And it wouldn’t, I mean, what are data ethics? That, to me is a big question that I’ve been thinking about.

Yeah, well, we got that question actually. So, so I don’t think we actually have a slide on our thoughts on it, so I’ll just kind of talk and then Priyanka jump in here. But you know, we’ve been, some of our research has been sponsored by the folks over at 222 which is a consulting firm that focuses on people analytics. And one of the things they’ve done that we think is cool. And we don’t like, I’ll talk about Max’s stuff if I think it’s cool. I’ll talk about anybody who’s cool.

So I just mentioned the sponsorship in the interest of transparency. But they worked with their folks to come up with a data ethics charter. And so basically this is a charter that organizations abide by that, that is being on GDPR compliance and gets that, you know, what are the types of things that we should do or shouldn’t do when it comes to people data? So for instance you know providing clear insights to employees on what’s done with their data when it’s collected is one component.

A second component of it is having a data, what do they call it like a, basically a data board to review all the decisions about how data is used and to make sure that it kind of meets their standards. So, you know, for instance, if what they were doing ended up on the front page of the wall street journal, which is, we all know happened last year for some companies, would they be okay with it? Would their employees be OK with it? You know, kind of that sort of conversation because it’s not, it’s not financial data, it’s data about individual people and and you know, whatever, no matter what your strategy is, there should be something, some things that are kind of okay, in terms of what you are analyzing and what you’re not.

The goals may not be things are the end results and decisions may not be things that make everybody happy. And for some people may not be, you know, they may not consider it ethical, but the way the data is handled and the way we think about the data is kind of the, the key thing. That’s kind of on the practitioner side, on the vendor side, we spent a lot of time talking to vendors about their role and their responsibilities when it comes to data, ethics and privacy.

So the reason we’re talking to them is, one overall, this is obviously to your point, Kristy, a new space for a lot of people. They haven’t thought about the ethics of, of all this, but the vendors are dealing with people who are probably new to this space all the time. And so the vendors coming in with a perspective on what’s ethical and appropriate and is at least a starting point to help kind of form the basis of how our industry is thinking.

And so we’ve been pushing on them because vendors, automatic response tends to be what we do with customer wants us to do. And I get that, but the customer often doesn’t know what they should do. And they’re looking to some guidance, particularly around people analytics, cause people are very much looking into partnership relationships with people analytics vendors. So they’re looking to the vendor for some guidance. So we’ve been pushing the vendor to provide some guidance and obviously the, the, the range of what they provide varies.

But what I’ve noticed is that vendors who come from outside of our industry. So let’s say they were in marketing, or there’s an incredible amount of people who come from security, which I’ve observed which is kind of interesting. But the people who come from outside of our industry are very into the individual data. Like we’re gonna, we’re going to give the managers all the information on who’s going to turn over in the next three months, based on our trip model. Like I, as an analyst and like, that’s, you know, put that in the hands of a manager who doesn’t know what to do with that and we all of a sudden have a whole bunch of problems, right? The vendors who have been in our industry are much more like, well, we need to think through what are the implications? What is this like for that person who’s manager suddenly got this information and maybe isn’t handling it very well.

So what, how should we be thinking about that? So seeing seen a significant difference between new vendor or vendors from outside the industry coming into our space, and those who’ve been here historically. There’s lots of things that are good about vendors coming from outside our space. So I’m not trying to throw them under the bus, but I have noticed that difference between the two. And I think it’s something for folks to kind of be aware of when they’re doing this partnerships, cause their ethics and privacy base, I think is a little bit different than people who have been historically in the HR space. So that’s kinda my initial response Kristy to come at that question.

Yeah. I really appreciate that. Thank you.

Yeah. What are, what are others seeing? To those who are working with vendors? I think I can start with that probably because we’ve been doing so many random briefings. And I’ve been particularly excited about this because last year when we published our study on people, analytics, they specifically call out a few things that we think windows can really improve upon, which is a good, a better user experience, more advanced, natural language processing capabilities, better data integration, and more individually passive data. And I think we’re starting to see that this year increasingly with vendors that we have accused of done briefings with.

So we’re starting to see a lot of improvement in user experience, how the dashboards are being built, what the visualizations look like. They’re definitely much prettier this year, for sure. We’ve seen some great advanced natural language processing capabilities and vendors that we were not expecting to see this year. So that was a good surprise. We’ve also seen vendors starting to open up their platforms. Using a lot of API is connecting to nontraditional data sources.

So I think that’s definitely been a that’s that’s upgrade direction. I think the risk seeing some of the trends moving in. I love your idea about educating the manager’s station. So I think ethics, you know, who, whose ethics are we going to use? I remember having this out at a conference somewhere the CEO’s ethics? The committee that you spoke about? Who’s so, you know, I think it’s gotta be a collective thing, but it’s so real what you’re talking about. Because one company at the moment would love to do its organizational networking analysis. And I absolutely dead keen as most of you I’m sure are on, on passive data. You know, and there are huge issues about doing passive data analysis. Cause people don’t know that they’re being tracked and that it’s being used. I’d advise against it, but that’s “Max ethics.” You know, I’m an old guy from another generation. I’m not used to being tracked other than my own, my own watch tracking me. Gen Y and gen Z at the conference didn’t seem to have that much of a problem because black, the lobster they’ve grown up in the water and the heat’s been turned up slowly. And it’s all I know is a life of being tracked. But, you know, I would say at the very least just use that as an ethical example, I would say at the very least, if you’re going to use passive data, do an active survey as well, even if you’re not going to use the results.

Just so that employees feel like they’re part of it. And I think that’s a huge part of ethics. Is that the involvement and, you know, Jonas, you you’re a Nestle person. I remember when Jordan came in and took over the the Fitbit work that was a huge issue and had long discussions about is it right? And Jordan said, you know, max, I would never do anything bad with the data. And I said, you know, Jordan, as I know and love you, I don’t think you would, but what about the person who’s going to take over from from you? And so there are a whole bunch of, as, as you say, there are whole, you need to have a manifesto that’s going to last longer than one manager and bring more managers into it. It’s very tricky. Yeah. And I think that’s the, for me kind of from where I sit in the space, that’s, that’s the thing that worries me the most. A lot of us go to these same people, analytics conferences, and we know each other, it is a community. That’s one of the things I love about this space is it is a community.

But as you know, I see all these kind of new folks coming in and I sound like totally, nimbyism here with our community and I don’t mean to be, but I think we do need to, for those who have been here and we think have good intentions to codify, what are the things we think are right? And maybe they will change, you know, to your point, maybe gen Z is just like, who cares. Right. But that should be a conversation that shouldn’t be an assumption, I think, is that the point that, that we’re trying to make with all of this, because we don’t know what’s going to happen in this. And we all know how powerful data is or data are, I guess, the proper way. So we think that that’s part of what we’re driving to cause right? The ethics aren’t going to be the same everywhere and, and they shouldn’t be, there’s going to be different standards, but being clear on what we think as an organization is okay, and what we think is not, and what we’re going to go to employees for. I think, you know, if it kind of goes to the lens on the far right and around trust. And if you guys haven’t read it, there’s a really great book out there called. Who can you trust? I can’t remember the author.

I remember I remember seeing her a few years ago, but she is, it’s just dynamite. And the thing that’s struck with that kinda stuck with me the most, and it’s actually reinforced by Edelman’s trust barometer is that organizations right now have the strongest amount of trust from people compared to any other entity, more than the government, more than religious institutions. Actually maybe not more than small government, but, but all other government. And this is worldwide study. And so we have an incredible position of importance and if we start to lose that trust we can lose it with, with bad data practices. So I think it’s a really important role that we all have in organizations. So. All right. I’ve been on a soap box for awhile.

How do Legacy Systems Compare with Small Vendors (41:10)

How do you think the legacy corporate systems, like SAP, compare to some of the new, small, but mighty competitors? Oh, SAP, our friends. So, so let’s move on to the next slide for those of you who haven’t seen this. This is our from last year study, people analytics tech study are how we looked at kind of the whole people analytics landscape. So just to orient you really quickly and on the X axis on the left hand side, we have what we called frequent analysis.

And on the right hand side, we had continuous analysis. So tools that are looking at data every day, giving insights every day versus on the left hand side tends to be more like monthly, quarterly, that kind of thing. On the Y axis on the bottom, we have data creators. So they’re creating data by things like surveys on the top data aggregators are pulling in data from other places. I think this year that’ll be did it integrators cause we think that’s more accurate. But anyway and then in the middle of the Y access centers, those vendors who do both. So with that kind of background, you can see number one, there’s tons and tons of the small, but mighty vendors. And then number two, the big vendors tend to kind of be we’ve got SAP on here.

Workday was not on last year study for a number of reasons, but we’re actually talking to them today, so they will be on this year’s study. And then our friends at Oracle just don’t seem to want to play. So but I think that the thing is that the, the bigger vendors are kind of good at being able to bring in certain data from a lot of different sources, and most many of them their own because they’re such big ecosystems. T

hey’re not necessarily so great all the time at pulling in data from other sources. Maybe we’ll get proven wrong about that today when we talked to Workday, but but they, they tend to be really good at that. Because they often, if company has all of their systems with like an SAP success factors you know, they obviously can kind of bring things in a bit more seamlessly than some of the others. But, you know, as is typical with larger organizations, their level of innovation tends to be slower.

Their ability to kind of turn out new ideas tends to be slower. And, you know, they’re I guess I would say that our partnership tends to be not quite as strong as some of the other smaller players, because they’re just so big and there’s so many moving pieces. They obviously offer plenty of really great things. But I think that those remained the bigger, bigger differences. And so then it comes back to you as a practitioner and organization.

What is it that you need? Do you need kind of some of these more innovative approaches do you need by contrast to move that, you know, like SAP is our system and so that’s just kind of who we need to, to work with because that’s kind of what we do here as a company. So it really comes back to the type of partnership I think that folks need and from the vendor and the type of capabilities that they need. Which I know is a little bit of a punting of the question, but I think that it’s hard given, you know, we’ve got 37 vendors on this graphic. It’s hard to speak with more specificity than, than that. Given kind of the question. Is there any specific questions on vendors from what we learned last year or what we’re learning right now? I have a lot of questions, but maybe take up too much time.

What was that Max? Oh, okay. Well, we’ll just leave it there because I do want to, I am sensitive to time and I see that you all put the book, who can you trust in the, in the chat. That’s awesome. Thank you. Alright, let’s go ahead and move on.

How can People Analytics be Used to Measure Skills? (45:21)

How can people analytics be used to measure effectiveness of upskilling and reskilling for increased business performance? So I almost said to Priyanka, let’s not, let’s talk to this question cause it can take up the entire hour. So I think there are a few things. We know that there are a few different models that organizations are using for building their skills taxonomies. So one is kind of a top down model. You know, this is what we think are all the skills that are out there.

The other is more of a bottom up model. So kind of looking at all the skills that are out there and starting to group them into different, different families in the like. I think that, so those are kind of the two models. The benefit of the latter is that it’s more organic. It can be more relevant and up to date. It also requires much bigger kind of competing power, quite frankly, to kind of continue to be getting that information. On the other side, it is probably a bit more stable. It’s probably a little bit better “organized,” but it also tends to be more static and slower to, to keep up with the times.

There are lots of vendors out there who can help you do this. We’re actually working on a big list of it right now. I think we’ve got 15 on it right at this moment. But but you know, some of them that others have mentioned certainly IBM and Degreed and MC and all the labor market analysis vendors, they, they’re all kind of doing this clerical. We spoke with them yesterday. The challenge that we see for all of these is that they either rely on somebody identifying the skills themselves saying that I have these skills or some somewhat imperfect assessments of their skills.

And so right now I think that the assessment mechanism is one of the nuts we have yet to crack. And so when we talk about that, the measure of the effectiveness of these efforts, I think that’s one of the things we’re going to have to get better at before we do this really well. In the moment with what we have right now, I think we’re kind of mediocre at this. And, and that’s part of, we’re actually starting a study on this to try to figure out how we might do this better. But if you assume that you, that your efforts are adequate in terms of the measurement, think then it becomes, okay. Well, how do you make sure that you’re matching this against specific interventions that have been happening in the organizations or specific initiatives and making sure that your measurement at the change in skills is happening at the right point in time? We haven’t seen folks doing this very well yet. So that’s kind of where we’re, I’ll leave that again in the interest of time.

Has anybody else seen folks doing this? No. No. And I think if anything like the skills, taxonomy and the intervention and exactly how that lines up with the assessment, I think for me, that’s the crux that I struggle with with skills is that I don’t know if there’s actually going to be a good answer. This one vendor you didn’t mention is eight-fold. So, I mean, they have, I think it’s 2.8 million different skills identified. And the approaches that you mentioned the top down and bottom up, I think where that should land, where it’s going to land is in skills ontologies as opposed to taxonomies.

So that the relationships, not only between the skills themselves, but between how those skills are categorized it all exists in the same model. And then you can build use cases off that whether those are learning use cases or career mobility or hiring or diversity and inclusion. I mean, that, seems to me where all this is headed. Yeah. That’s a great point, Brad, thank you for, for making it. And I especially do love what eight-fold is doing.

So the thing that they do that I think is very cool is they play with skills inference. So if you have you know, if you’re good at one type of programming language, you’re likely also good at these other skills. And so you, as an individual, don’t have to identify that, which is really I think helpful because that’s something that, you know, people are notoriously not great at thinking about as kind of some of these adjacent skills.

The other thing that eight-fold does that I think is great is they apply that across obviously all people, but when you’re searching for people, they don’t limit to the verified skills they limit, they include the likely skills. Which if you look at that from a diversity perspective, diverse people tend not to list nearly as many skills as of majority population folks. And so when you include the likely skills, you get a much bigger talent pipeline than you would, if you just looked at what somebody actually puts on their resume or their LinkedIn. So I think that it’s it’s has a lot of power, a lot of potential. Yeah. Thank you very much, Brian, for mentioning that.

Sure. Speaking again. Ian Bailey did some wonderful work at Cisco. I think with LinkedIn and they had a wonderful visual dashboard of skills and competencies which I don’t think ever was productized or made available as far as I know. But it’s an internal tool, so it might be worth asking Ian to show them to you.

How has People Analytics be Applied during COVID-19? (51:05)

Yeah. Priyanka. Thank you. Okay. Let’s I know we’ve got just five minutes, so Priyanka let’s go ahead. Alright. So here we come to some COVID-19 reasons. What are some of the interesting ways people analytics has been applied during COVID-19? So if you all have a chance to look at those two articles that we’ve put into chat we have within each of them people analytics during crisis or people analytics during COVID-19. So we’ve got lots and lots of examples of kind of everything that we’ve been talking about today.

But I think that just to maybe tie back to what we were just talking about, the, the skills example, and one of the most powerful examples you think of this working well during COVID was came to us from Thomas Rasmussen, who was at National Australia Bank until just very recently. And basically what they were able to do because of the strength of their skills profile, skills data. They were able to look across all of their employees and figure out which ones had the skills to work more directly with customers. Because as you can imagine with being a bank, so obviously not just a health crisis, but an economic crisis for many, and they were getting many more calls from their customers asking for help. And so they basically were able to redeploy,

I think it’s 700 people within a week from kind of non-customer facing roles, but had customer experience over in the customer-facing role so that they could support their customers during COVID-19. So, you know, we’ve seen a lot of, a lot of studies about using more engagement and pull surveys and all the rest of that. But I think that one was a really powerful example of using skills and just having that strength of skills to actually meet business needs during COVID. So I’ll maybe leave it there because that’s a lot of examples.

Okay. Tiffany, you put in an example here had the same. Do you want to talk about that? Are you able to talk about that Tiffany from chat? Can you hear me? Yes. yeah. We’re a relatively small financial advice firm in Europe and Canada, and because we are organic and sort of grown, we try to keep tabs on who has any sort of licenses or who can serve clients. So when we had to shut down all of our suburban and rural branches and clients couldn’t get-face to-face access with their branch team, we immediately pivoted so that the thousands of home office employees who had the certifications became frontline, investment helpers, answering phone calls and driving service.

So that trades didn’t have to stop just because we couldn’t get that face to face interaction. So that was, that was really a, a huge help for the client base almost immediately when everything’s sort of shut down at a regional level. That’s awesome. Cool. Thank you for sharing them. No, I I’m glad that the question came up and, and the original response actually made me think, “Oh, you know what, we did that too. Wow.”

I wouldn’t have thought of that as a people analytics function, but that’s exactly what it was. Yeah. Yeah. It’s amazing to see all the ways that people analytics has been applied in the last four or five months call. Does anybody else have anything on this that you’ve seen? Okay. Well, well we’ll move on then. Priyanka, was that our last one because I think we covered ethics already. Oh yeah, we did. Actually. That was the last question. So in case anybody else has anything to add in the last two minutes, more than welcome to.

APIs and Non-Traditional Data Sources (54:56)

Quick question, when you were talking about the APIs and non-traditional, what was the word you said? I forget. What, what, what do you mean by non-traditional APIs? I meant APIs from non traditional data sources for vendors who don’t, who have not been typically looking at certain data sources in the past for us to starting to look at. So for example, one of the vendors that we spoke to yesterday is being focused on labor market insights data mostly now they are starting to think about other data sources, such as bringing in voice channels, data from voice channels and analyzing that. Bringing in financial services data.

And we’re seeing a lot of engagement and experience vendors also start to think really deeply about how can they pull in performance data and learning data to bring a holistic employee experience platform to the users. So, in the sense that they’re increasing the number of places where they’re pulling in and analyzing data for to bring a more holistic picture for the user. That makes sense. Thank you. Yeah.

All right. Well, I think we’re right at time today. So thank you all so much for a wonderful conversation and the engagement. If you have any other follow-on questions, just go ahead and send them along. And if you have any feedback on how this went we’d love to hear that too. So we’ll say goodbye for now and have a great rest of your day and a good weekend. Thank you very much. Thank you. Take care.

Written by

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.

Share This