Unlocking Business Success Through Workplace Intelligence with Tyler Marcus: Gradmor Product Profile

Started by Tyler Marcus and Ava Potts in 2017, Gradmor is a workplace intelligence platform that aims to empower the people behind your organization to scale your business growth. I spoke with Tyler to discuss the importance of measuring employee impact to drive growth and productivity in the workplace.

Getting Started

How did Gradmor begin?

My wife and I started Gradmor like six years ago now, actually. We always wanted to do something in the people space. We always had a passion for talent, understanding how to make talent better, and how to make the workforce more enjoyable for people.

So originally, we started mostly around recruiting, particularly consulting in terms of analytics... So a lot of consulting work with various different... actually a lot of recruiting firms, helping them use data in a better way. And then that slowly turned into working with consultants, managing consultants and partners, and providing them a resource to use analytics. So that's how we started the company. And then from there, it's evolved into more of a workplace intelligence platform where we're tying back data with behavioral science.

What were you doing before Gradmor?

I was in marketing. So my background in college was in research at the University of Wisconsin. I was in the research program there and I helped several professors with data analytics and data science. So one function of my background is helping a professor in sociology use data analytics to determine different ethnic groups and entrepreneurship in the US. So that was the main focus of his research at the school.

Then the other side of it was working with a political science professor who did polling, political polling, state polling in Wisconsin on election races and helping him with data on that side. 

So that was my role in the research program there. And then from there, I went into marketing. I went into finance first. For a year or two I did financial data analysis work for an M&A firm. But I wanted to do something more creative... So I went to marketing and that was around the time when Facebook added SEO and SDM become like more and more of like a thing. So I started to work for different startups. Now we're doing marketing campaigns and running data campaigns and doing all of that. And then from there I went into Gradmor after doing that for, you know, I would say six years or so.

Why the leap from marketing to talent?

So my experiences at the startup world were a lot of the companies I felt like were using data with marketing and sales, but I felt like a lot of their actual business problems were around people and growth.

So a lot of the companies I worked for, I would say two of the startups like hired, raised a lot of money, hired a bunch of people and then like overhired or like didn't care about the people and they crashed.

And that's what led this experience to wanting to start something in talent. Because it's just that experience of... if you were using more of an analytical approach or you had more of a scientific way to understand your workforce, you wouldn't be making those decisions that they made around that.

So that that's why we transitioned. And that's why I always want to do something on the people side.

Growth Through Data

Very interesting. You mentioned starting out your work and even working specifically with recruiting teams using data in a better way. What are the ways that you see are most common in companies using data or lack thereof and then what do you think it should be?

So one, is what I find is a lot of them are just not looking at all. So... the data is just not being used right? 

For example, one of my customers was hiring a bunch of recruiters, right, for the recruiting firm. And they were just having this consistent every six months churn of recruiters, right, and just when you got down to what their hiring process was, it was very... "oh we thought this person was great and super awesome in interviews and we hired them." And you know, that just become an unstable way to go about it. And so what I was helping them with was figuring out in the most simplest way, what were the trends that led to better performance.

Actually, at their company, it was really about hiring people that had either a sales background before, like retail sales, like someone right out of college because most of their recruiters they were hiring were right out of college. When we did a data analysis we showed that hiring people that worked as like a sales associate at like an H&M, right, that was a key trend for being a better recruiter to the company. 

The other thing was actually someone who had done sports, and was like an athlete in a Division 1 school or Division 3... anything competitively. So those were the two most noticeable factors of success in the company and so...  my first dabble into that was just looking at simple things like that and then the other bucket I would say is people that are using data but they're just not using it in a way that connects back to business outcomes or revenue outcomes. So a lot of times they find.. Companies will be like "oh we have recruiting data. It tells me how many applicants we have and, you know, how many people are in the funnel or how many people we hired." That's great information, but it's not something that's meant to optimize how that helps your bottom line. How does that drive better performance from the people that you hire?

So you're using it more in an operational way instead of a predictive or more analytical way. I would say those are the two things I noticed... It's taking it from zero to one or from one to eight.

Why don't companies do that?

I think... It's my theory that it's a few things. One, I think that people don't realize the impact of talent analytics or data in the same way that people see it when they do marketing analytics or sales. Because I know from my marketing background, even in the earliest stage startups, we had a Salesforce CRM or a marketing HubSpot where people are already using data. And marketing is a very data driven function now...

But when we think of talent, people don't think about the data and how that can be used. It's just not natural in how we think about it. I think that's a key reason. I also just think that people don't really understand how valuable it can be. I think they just think of data as like... head count. Because when I've had these conversations, especially early on, they're like "oh, we just use our data to show our headcount distribution." Like, that's awesome. But when I was in marketing, we were using our data to show how can we drive more conversions to a better price on Facebook ads? How can we get more people to sign up for our events... And we would just use data to figure that out...

It's just, I just don't think it's thought of that way... Even though I think nowadays people are starting to see the value of it, it's just that it's a little bit later in the cycle of adaptability.

Validity Studies as an Entry Point

For the layperson, describe what a validity study is and how can it be used?

Most of the work we do now revolves around behavioral assessments with PI, Predictive Index, right? And understanding how certain behaviors and performance relate to each other in a way. A validity study would be taking behavioral assessment data of your current employees, okay, looking at the performance data and determining and finding trends to see what we see what leads to better or worse performance within a role, right, or within the study itself.

So what that provides insights into is what is your team makeup and what behaviors are leading to better performance within your company. So you can use that to make better decisions around training, hiring, and the like.

What are some of the most popular examples of outcomes of validity studies?

It gives you an insight into what leads to better performance... within a role. What is leading to worse performance? So not just focusing on top, but are there trends into what is leading to people underperforming?

And it tells you also the impact of that from your business outcomes. So, you know, how is that impacting your company's bottom line? Then it also will give you insight into what is statistically significant. It will highlight, hey, these trends are not only happening, but this is a statistical significance... So you know with confidence that this is true right? So it tells you that information as well and then it will also give you just insight into what can be done to improve that or what you need to do to get the number up.

Could you maybe speak a little bit about the evolution of validity studies, why it's important, and who could consider them?

Yeah, so... validity studies were back in the day, or like years ago, it was really just carried in the enterprise, right? Because they had the tech, and the wherewithal, and the data to do that. Nowadays... mid-market companies can do validity studies as long as they have enough employees in a specific role to make it worthwhile. From my opinion, at least 50, let's say in the same role, but preferably at least an 100 headcount qualifies you for validity studies. So that is number one. It's just a fact... The value is actually big because even within a smaller company, if you're a 300 person tech company and you have an 100 person sales team...  what we find is even in that size company, they're producing sometimes a hundred or two-hundred million dollars in revenue in that sales team itself... Even being able to know that if I hire, you know, next year twenty people... instead of 35% of them being top performers now I have the potential to make half of them be top performers. That could be eight to ten million dollars... So even on a small scale as long as you have the right headcount you can see the business impact right away. So that's what, you know, I find is critical.

In the smallest validity study I've done has been for like sixty. And that was for a company that only had like an 180 headcount... But they were selling to pretty big enterprises, so, you know people in the top 10% of sales of that company were producing $6 million, people in the bottom 30% were producing a million. So if you're hiring twenty new reps, that's important. They were looking to hire an SDR team and if you're hiring an SDR team for the purpose of turning them into account executives... so even for that feed, making sure the people you hire people who have the right mindset and right behavioral makeup to be successful. 

We can do a study and it definitely has business outcomes that can be hugely impactful.

Let's shift gears a little bit and get into the value prop of Gradmor.

So one, we find that validity studies are great because I find that understanding the team, the makeup, also understanding where this can have an impact, and showing those numbers right off the bat can give clients a good feeling that this matters to them.

Because I feel like the first set of resistance is like, we're not sure if this works for us. We're not sure if - what if behavior doesn't impact performance. So before getting into the platform, just understanding that yes, there is differences between top performers and bottom performers with their behavior in a statistically significant way means a lot. So that's the first piece.

Then when we get into the platform, it's really understanding how we can apply data from the validity study into a business practice or into a new routine. So most of the time when we do a validity study, based on results, we'll recommend solutions depending on what that focus of the study is. 

We have three key solutions around our platform. So one is a hiring intelligence solution, which is really about providing insight into how you can hire more effectively based on the validity study, right? 

Two is performance. So what can you do for the current team performance based on other data that you have. Whether that's productivity data, sales and enablement platform data... How you can change what you're doing from a training or onboarding standpoint or performance standpoint to make sure your current employees that you hire will perform better.

And then third is retention issues. Sometimes the studies will focus on retention.... It measures it and gives them insight to that. That validity study should be done once a year. Honestly it could be done every six months.

A Gradmor Demonstration

Can you show us around a bit to give us a sense of the platform?

Sure! All right... So I'm just going to walk you through quickly our three solutions, just covering each of them.

So one is the hiring intelligence solution, one is performance intelligence, and one is retention intelligence. This is all based on an account executive example. Note that this can be done with different teams as long as there are performance metrics around a team... So it doesn't just have to be revenue numbers. It could be performance management scores. I've done this for engineering as well.

So first thing I'm going to touch on is how we integrate with The Predictive Index. So when people use our solution for hiring intelligence, it's about giving them more insight into who to hire and who not to hire. And just providing them... with that specific insight, right? So what happens with PI... Your people will fill out a behavioral assessment. The job target will tell them, hey, they match the target or they don't. But what we find is when we've done validity studies is there are a few things that happen. One, sometimes a lot of people don't fit that job target... So what will happen is you'll only have 8% of applicants or 5% fit that job target exactly, right?

So this gives them more insight to make better decisions around people that are not that exact fit. Because what we found is that when companies are using PI with the job target, is that they are actually more or less not sticking to that exactly... They're kind of like on the edges and using it as a guide... So what this tool does is it will actually give them more insight into the candidate. So for example, let's take Ashley here, right, who is an account executive who applied... Our hiring model suggested that she's preferred... meaning that our model says that based on her makeup, she is likely to perform well in this role. Then we give her a match based on the group that she matches. In this case, she matches high performance group one. I'll get into those in a second. What it also tells you is people that are not recommended based on the model, so like Casey Park over here, not recommended low performance group three. So based on our model and our validity study analysis, we can give them insight into if they match or don't match the candidate.

So let's go back to high-performance group one. As we can see here, this gives insight into this profile in a sense that she fits a somewhat cooperative, somewhat extroverted patience group... It will also tell you what percentage are high performers at this company. In this case the group is at 80%, which means that 80% of the people that fit this exact combination are performing very well... It also gives them interest in the PI profiles that it matched... It will give them some examples of people, right? Alton over here, Herman on the team, so they know more or less where they match. It will also give them a bit more group insight into the person as well.

So like in this case, patience and relationship building, resilience, and customer focused approach are like the key highlighters of this profile... So the way this usually works is we find this information will get passed along with the PI information to the hiring manager. So when they interview, they have this insight, right? So they know that so they can make better decisions within that process. Because what we find is a lot of times is people, when they make decisions on candidates, it's like they either really, really like a candidate and they're like, yes, I want to hire them or there are ones they really don't like. And then they have this like 80% where they'll like them but be unsure. This gives them the ability to ask the right questions around that.

Tell me a bit about how the various ways that engagements are structured in Gradmor.

So we usually start with a study or report... either based on retention or based on performance. So if the company is like, look, we have a retention issue. We're going to look at your retention numbers and profiles of those people and behavioral assessment results and do that. If you want to look at performance, and most people tend to start there, then we're going to focus on that.

So validity studies are the first engagement... and that will depend on pricing... and on headcount... If there's any customizations, like... we want to use a model that balances quota attainment with, you know, productivity... well that's extra money because I have to create a model for that now. So it depends on that. But most of the cases, say it's one KPI report, so that deliverable is just a PDF. And that's really just meant to get an understanding of like, is this a valuable thing? Is it working? What insights are we having? Can anything be done? And that will give them an ongoing tool that they can integrate with The Predictive Index and with other tools... to provide them insight into their use case that they have, right?

Also, pricing depends on headcount. With the hiring one, it also depends on the candidates they have coming through because if the company has thousands and thousands of candidates,  it's more data, more processing. And then also, it depends on the amount of times, if it's going to be updated quarterly with the validity... And then the other piece is that tracking tool where, you know, if a finance team or a Head of Ops wants to know, every quarter,are we on track to hire and make the right hires, that is also included. So everything starts at $15K, but that can go up depending on those factors I mentioned...

You shared the price of $15K per year on the software side. What would you say is the ballpark price for somebody to do a validity study?

So that ranges between 5 and 15, depending on the complexity and headcount... we've had engagements about 50 just because, oh, we have three hundred person headcount, oh, we want it quarterly, oh we want to track - just stuff that adds up.

And what about integrations? Are you integrating with platforms or are you taking like data dumps?

Depends. Some platforms I can't integrate with, for example, some of them don't have a good enough API or they don't allow it. So we have to do a data dump quarterly. That happens sometimes. Other times I can integrate directly if they have the API. So I would say it's about a 50-50 split, it can work both ways.

What other data points have you found success with?

Productivity has been really good... The amazing thing about PI on the hiring side, because people do the behavioral assessment, is that works for that really well right. Because a candidate fills it out and it correlates well. See if I do productivity, they don't know like a candidate's productivity... But productivity works super well when it comes to retention and the performance if they're just assessing a team from their stat standpoint. 

I've done a lot of stuff with engagement data. Whether it's like pulse surveys or things like that to figure out what is driving performance. 

One company - we did this for their productivity - they were like, people are still productive at our company. Like, well, the problem is they're productive in the wrong area... And I'm like, well, the reason is, is because you're focused on the wrong number. You need to focus on these numbers.

Yeah, so in some ways, you could help them determine what truly are KPIs.

Yeah, not just like their vanity metrics. Because I find there's a lot of vanity metrics with this stuff... especially around like hiring.

The Importance of Data

The insights shared by Tyler highlight the transformative potential of workplace intelligence in today's business landscape. Gradmor's evolution into a workplace intelligence platform, with its emphasis on validity studies and actionable data, offers a promising path for companies seeking to optimize their hiring, performance, and retention strategies. By leveraging talent data effectively, businesses can unlock new levels of success and create a more productive and engaged workforce.