(upbeat music) - You're listening to the HR Mesa. Your podcast with the perfect mix of practical advice, thought provoking interviews and stories that just hit different so that work doesn't have to feel, well, like work. Now, your host, Shari Simpson. - Joining me today is Josh Merrill, CEO and founder of Confirm. Josh founded Confirm in 2019 with the goal of fixing performance reviews grounded in the science of organizational network analysis.
Confirm empowers leaders with a true view of each employee's influence, impact, and actual contribution in order to retain their top talent. (upbeat music) Josh, thanks so much for jumping on the podcast with me today. - Thanks for having me. I'm excited to be here. - So I think it's fantastic you were able to join me and I'd love if you could kick us off by sharing a little bit about your own journey from Carta to founding Confirm and really what sparked that shift. - Yeah, absolutely.
So my co-founder and I have been doing Confirm for just about four years now. And prior to that, yeah, I spent six years at a company called Carta. I was the chief product officer there. It was a crazy rocket ship ride. I was the second employee. I left at maybe 600 employees, something like that. It was wild, yeah. And of course, I suffered all the problems of performance management kind of from both sides of the table as a manager and also as an employee myself.
And I think that what piqued my interest into sort of the core methodology that makes up Confirm and our platform was this idea at Carta that there was always this sort of shadow org chart, that there was the hierarchical org chart that we all saw, but below that, there was this network of people getting things done. And that network took a very different form and had very different connections than what we put in the hierarchy. And we always wanted to understand that.
And that actually ended up being sort of the core of what we do at Confirm. - So Confirm has this foundation in organizational network analysis. So for our listeners who might be new to this, can you break down what that means and how that shapes your approach? - Yeah, totally. So it's a mouthful. Organizational network analysis or ONA. So ONA is a way of understanding the flow of information, of decisions within an organization.
And it's a methodology that's been used in like academia and used in research for a couple of decades, but it's never really made it into the HR toolkit. And when you bring it into a performance management context, if you did a performance review, like based on ONA, the difference would be, like if you've done a traditional performance review, you're used to answering a lot of questions about yourself. And like, what impact did you make? How did you make a difference? What goals did you achieve?
Stuff like that. When you answer questions around ONA, you might answer a question like, Shari, who did you go to for help and advice? Who around you energized you or motivated you? We ask some questions, we ask questions like, who do you see making an outstanding contribution? Or who are you concerned needs additional support?
And it turns out that when you ask questions like that, of course you can pick anyone in the organization, but maybe you picked Bob as being a source of expertise for some really particular skill that he has. Well, maybe a lot of other people pick Bob too. And now we can suddenly go, oh, Bob is really an expert in this. A lot of people depend on Bob for this one particular skill. This is really critical, right? He may be a really critical employee.
And those are the kinds of insights that organizational network analysis can reveal that traditional reviews can't. - So how do you see that kind of changing the view of performance reviews and employee assessments as we see them today? 'Cause I think there's a lot of misconceptions about what performance reviews should or should not be.
- If you stay at any company long enough, you'll see them go through like multiple rounds of like their performance management process, 'cause most companies overhaul them every two or three years because they never land on something that they're satisfied with. And the reason for that is actually really structural. When you look at performance reviews, and I'm really talking about that traditional one to four, one to five manager rating, that methodology is a hundred years old.
So it was created by the US military at the end of World War I, brought into the workplace in the 1920s, when like work was sort of solitary and repetitive and we didn't have technology, we didn't have communication, we didn't even have telephones. Now, of course, like work is completely different. Like work happens over Zoom and Microsoft Teams and Slack. We work in these networks and we're collaborative and we're creative and cross-functional.
And so the way that we work has totally transformed. The way that we measure that work is still frozen in time. It's still just one manager's point of view. When in reality, we have all these stakeholders, all these people we're working with. And the reason why we get excited about organizational network analysis is it's a way of measuring work in the way that work is actually happening, which is collaborative, cross-functional in networks.
- Well, and there's only so much your manager can see, right? - Oh my God. I mean, I tell you, like when I was in college, they taught me to manage by walking around and like no one has shown me how to do that over Zoom. - Right? - There is so much that happens that, and I can't be in every Slack channel, like I can't see the DMs, right? There's so much that happens outside of the manager's visibility and more of that is happening than ever, right?
Employees are more collaborative and more networked than ever. And the manager is seeing less and less. - Well, and also sometimes the employee doesn't know what to share back up to the manager. Something that they might think is minute, like, "Hey, Bob helped me with this thing," or, "Bob's this resource." I might not think to tell my supervisor that, like, "Hey, I worked on this project, but Bob was really a valuable piece of information."
So this whole concept of ONA is really interesting to help surface some of that stuff. As you think about this process and performance management in totality across generations, across different DEI metrics, here at Paylocity, we call it DEIA, our A stands for accessibility. Can you give us an example of how maybe Confirm has helped companies navigate that specific challenges in the DEI space? - Oh, absolutely.
And to go back to your earlier point and tie it in, the system that we have today that's totally manager-driven requires everybody to be sort of their own self-promoter. And the reality, especially when you take a DEI lens, is not everybody is conditioned or trained to self-promote. It's a different skill from actually doing the work. And what we see over and over again, we hear this all the time from our customers, is ONA will sort of reveal the quiet voices in the room.
Like, we call them the quiet contributors now. I've read about like quiet quitters, but there are these quiet contributors who, like, they're people who, you know, they're not the ones that are always speaking up in meetings but they may be doing so much behind the scenes to get their own work done, to enable the people around them to get their work done. And if they haven't developed that skill of self-promoting, they're gonna be overlooked.
And that's a real problem because companies are missing out on a lot of the hidden gems and a lot of the superstars that are really, really crucial because self-promotion is a different skill. So the DEI implications of what we do are tremendous. And that's what we see over and over again is these quiet contributors being elevated.
- Have you uncovered any surprising data as you've done this process with organizations or trends that have come up that you just kind of just, I don't know, were not what you expected? - Oh my gosh, where do I even start? So this is what we see actually, this surprised us at first, but we've seen it so many times that now we understand why this happens. When we start working with an organization, they're usually doing like a five point manager rating scale or something.
And I can usually go in and say, so tell me if this sounds right, 90% of your employees are a three or a four, meaning they're like meeting expectations or exceeding expectations. They say, yeah, everyone's a three or a four in this organization. And there's a reason for that. And the reason is managers don't like to give ones and twos. So if a manager gives a one or a two, now they've got to have a tough conversation, it's uncomfortable, HR is gonna get involved.
If that person is terminated, now I've got to go find a replacement and I'm recruiting. So better to just give those people a meets expectations because no one's gonna blink, right? The same thing happens on the other side. If I have a really star performer, someone I think is really exceptional, well, I don't wanna give them a five, right? I don't wanna give them the highest rating because I'm gonna look like an easy grader. And what if I'm wrong?
What if they're just managing up to me but other people really don't like them? Or what if there's something I don't know about this person? So I'm gonna hedge a little bit and I'll give them an exceeds expectations. That's much safer. And what we see over and over again is the moment that customer starts working with us and they get that organizational network analysis data, the manager sees it too. The manager sees it, their manager sees it, HR sees it.
So suddenly you can't shield the underperformers anymore because the data is known. I mean, you may have somebody who, when we ask a question like, who do you believe needs additional support or attention? You might have a dozen people calling this person out and saying, hey, this person has some problems that really need to be addressed. We can't hide that anymore.
But on the flip side, you may have a really star performer that everyone is pointing to and saying, yeah, we really depend on this person. They're exceptional. That also gives air cover to the manager to actually give that five rating that they would have held back on. And that's what we see over and over again when we work with new customers is suddenly the organization isn't all meeting or exceeding expectations.
All of a sudden there's some people who really need to improve and there's some people who are doing really exceptional but have been flying under the radar. So we see that all the time. - How do you ensure that that data-driven approach doesn't introduce any bias? - Well, I think it's important to acknowledge that bias will always exist. Like there's no way to eliminate bias. The best that we can do is to reduce it.
And so I would say there are a couple of things that ONA does that are really powerful in reducing bias. But I'll just answer your question first by calling out how biased the current system is, right? Because you have one person's point of view, the manager's point of view that's gonna determine everything about this employee's future at the organization, their development, their compensation. And when we look at that, in fact, it's such an easy system to game that we have a word for it.
It's called managing up. - Right. - You just have to convince that one person that you're really great. The reality is when we look at the research, and this has been documented for the last 20 years or so, that about 60% of a manager's rating is bias. It's attributable to the idiosyncrasies of the manager. What that means is when I rate somebody in a performance review, my rating actually says more about me than it does about the employee. Which is crazy, right?
That we still rely on that system. But what's so powerful about ONA, fundamentally it's the power of sample size. So if we look at an employee, maybe we ask that question, who do you go to for help? Or who's energizing you? And a dozen people point to the same person and say this person is really motivating. This person is an expert. Or we ask that question, who are you concerned about? And six people point to the same individual. That's the power of sample size.
And that's sort of what tells us that, you may have a bias, I may have a bias, but at the end of the day, we're sort of averaging it out through sample size. The silly analogy that I like to use is, if you've ever been to like a county fair and you see one of those giant gumball machines, and they ask you to guess like how many gumballs are in the machine. Well, most people are gonna guess wrong, right? But if you actually look at where those guesses average out, it's frighteningly accurate.
And we actually see the same thing with ONA. One or two nominations may not swing the difference, but when you really see sample size, you can be very sure that what you're looking at is reality. - You mentioned managing up and I kind of chuckled, obviously you did hear me chuckle, but because I think about, in general performance reviews are, they're broken. There's no great approach across the board. We all know that, they've been broken for a while.
You hit the nail on the head with, they were invented to measure something else that we're not measuring now. And I've always thought it was curious how we talk about expectations in a role. So you get into a new role, they sit down, you might have a copy of your job description, but that's usually separate from what your expectations are to perform in that year. And so you're working against these expectations, but you don't really know where you're going to land.
Nobody had the really honest conversation and said, if you accomplish these things, you'll be a three, you'll be a means, you do this, you'll be exceeding you, this you'll be outstanding. We're afraid to have those conversations. Like you mentioned, how does taking an ONA approach change that expectations conversation on the front end when somebody walks into an organization? - Totally. Well, I think the first thing I would say is, that meets expectations.
Like, we all love the idea that like, if an employee does X, Y, and Z, that that means they're meeting expectations. And like, if I'm meeting expectations, I'm good, right? I'm safe. Especially in this recent environment of a lot of layoffs. And the reality is not that, right? The reality is like, I can get a meets expectations rating and a month later be part of a riff, right? That's just the reality that we're living in today.
And what I would say is, when companies do, if a company does a riff, for example, what they're really trying to do is like, they're trying to reduce the headcount, obviously, but they're also trying to sort of reduce the collateral damage, reduce the collateral impact of having a group of employees suddenly leave the company. And so what are they gonna do? They're gonna look at the employees who the fewest other people depend on, right? Or who aren't perceived as making a great contribution.
They're essentially gonna try to get to the data or try to get to the point of view that ONA actually could give you in a very quantifiable way. And so I think that when you talk about, when you talk about sort of that performance conversation, it's not about like meeting expectations in terms of sort of checking a list of checkboxes. It's really about how can you maximize your impact in this organization? How can you enable more people to get their work done?
How can you energize more people, be an expert to more people? And that's the true underlying reality of how work happens today. I think maybe the employer employee contract has changed a little bit. So my father worked for the same company for 45 years and then retired. That doesn't happen anymore. But that contract has fundamentally changed. And it's not about hitting a list of checkboxes. It's about maximizing impact.
- I've been at Paylocity now seven years and I feel like a dinosaur because you're absolutely right. People don't say it at companies. My dad had two jobs he stayed at over 20 plus years each. You're right. That doesn't exist. People are moving two and a half years, three and a half years. Often that's the only way to get a big compensation change and some of those things.
I really like this approach though to think about performance management differently, especially as we think about Gen Z and the workforce and some of the things that they're expecting out of us as HR leaders and managers. We often start to hear questions very early on within the first few weeks of employment. How do I get promoted? How do I succeed? How do I make an impact? Can I work on these other projects?
So having this type of visibility into that type of performance definitely can have a huge impact. I'm curious as you think about the rapid evolution of technology in the workplace, especially, we've seen a lot has happened, especially coming out of COVID and that COVID's gone. It's gonna be here forever, but we saw this digital kind of transformation happen really quickly for a lot of people.
How do you envision this future of HR analytics, particularly in the context of managing diverse teams and performance management? How do you see that changing or maybe what are some things you're excited about that could come down the road? - Oh, gosh, I mean, there's so much. I think that, so you're totally right. I mean, the way that we're working has already transformed, especially since the pandemic.
Like if you weren't using, Zoom or Slack or Teams before the pandemic, you're definitely using it now. And we're spending more time doing work from remote places. We're not in the office as much anymore. And that trend of technology coming into the workplace and changing our lives is just gonna continue. We have AI coming in. More and more of us are using chat GPT.
I have an Apple Vision Pro right next to me, which is kind of another wave of technology that like in a couple of years, we're all gonna have to adapt to that. But I think what's sort of getting missed in all of that is the way that we are working is transforming. And it's changing more rapidly than ever, but we're still just gonna get that one to five manager rating at the end of the day, right? Like the way we're actually being measured on the contribution that we make, that's not changing.
That's not changing with the technology. That's not changing with the way we work. I mean, when you talk about, for example, Gen Z, asking a question like, well, how do I get promoted? It's a very fair question. And the reality of the system that we work in today is that my ability to be promoted depends first on having a manager who will advocate and influence on my behalf relative to all the other managers who are trying to do the same thing for their teams.
So first you say, well, okay, well, that's out of my hands. That comes down to having a manager who's influential. Then the second factor is, how well did I self promote to that manager? Because they have to believe that I'm worth going to bat for and then somewhere down that list is my own actual contribution, right? My own actual work.
And I think that if you were to take a clean sheet of paper and say, let's start over with performance management, I think what you would say is, my contribution should be first. That should be the first thing that matters. And then my ability to self promote or my manager's ability to promote and advocate on my behalf, that's all way down the list. Should be my own contributions that matter most.
And the reason I get so excited about ONA is it's the only performance management and performance measurement methodology that actually gets to that. I haven't seen any other methodology get closer to actually measuring the contributions of any one individual than ONA. - Walk me through kind of the typical scenario if somebody engages with Confirms Insights, how has that changed a company's approach to talent retention or team structuring? - Oh gosh, yeah.
Well, the first thing I would say is, number one, you have more information at your fingertips than you ever would have in the past. So suddenly I can see all those quiet contributors, the people who don't speak up in meetings, but they're doing so much behind the scenes, suddenly they're lifted to the surface. So are problematic employees, people who maybe are good at managing up, but they have sharp elbows and people don't like to work with them.
When we look at our data in Confirm, when we look across all the companies that we've worked with, what we typically find is that about 15%, one five percent of employees are gonna create about 50% of the impact. So 15% of employees will create about 50% of the impact, about 5% of employees will create about 50% of the problems. And for the most part, company leaders have no idea who these people are. So that's the first thing to keep in mind is suddenly I have data to be able to work with.
The second is I now have like directionality and context around that data. So when we ask a question like, who did you go to for help and advice? We're gonna ask you, what did they help you with? And so you can actually give us some context or how did you see them make an outstanding contribution? And what we find from that is it adds a layer of nuance to every single individual's performance in a way that traditional ratings can't.
So if I were to say that this account executive is meeting expectations, well, that may be true if you kind of average it out. But if I look at the ONA data, what I might see is, oh, they're really helpful to all the other account executives, right? They're helping them get their work done and close deals and helping them prospect or whatever. But then the customer success team just hates working with this person because they hand off their clients in a really bad way.
Right, so you actually get like polarization, you get nuance that totally disappears when you have to just flatten everybody to a single number. And when you have that, suddenly you can make decisions with a lot more visibility, a lot more context that totally would have been lost in a traditional method.
- So I wanna ask one final question that's a little off topic, but I'm just, I'm curious, for those that might be listening who are aspiring HR tech entrepreneurs, what's one piece of advice you have for them about blending technology and data and still keeping that real human aspect of HR? - Oh, gosh. Well, I try not to give advice, but I will tell you what, maybe what I would tell myself or maybe what sort of gets me up in the morning, which is, you know, startups are hard.
And what keeps you going or say, what keeps me going is the mission of what we do. And the mission of Confirm is to rightly recognize everybody for the difference they make at work. That's like what we do, that's why we get up in the morning. And what brings that to life for me is when I hear stories from our customers, like, oh my gosh, I had no idea that Mary was helping so many people and making such a big impact, we promoted her.
Or I had no idea this person was creating so many problems, they were creating a toxic environment, we let them go. That's actually changing things for the better. And those stories, that's what keeps me going, knowing that we're out there in the world and making a difference through our mission. - Josh, I absolutely love that. Thank you so much for sharing a little bit about Confirm, but more importantly, teaching us about ONA.
I think it's just a fascinating concept and it's definitely gonna be interesting to see how the performance management methodology changes over the years as we make this shift to a more holistic view of what the employee is and the impact they have. So thanks for chatting with me. - Thanks for having me. (upbeat music) - I hope you enjoyed today's episode. You can find shownotes and links at thehrmixtape.com. Come back often and please subscribe, rate, and review.