What’s in a role: Eric Knudsen, Manager, People Analytics at Namely

Lerer Hippeau
7 min readNov 16, 2018


By: Amanda Mulay, Senior Talent Manager

People problems are a major reason startups fail. But recruiting the right people for your team is only the first step. Business leaders and HR managers need to ensure new hires are set up to succeed in the long-term, otherwise great talent might end up leaving the organization for new opportunities. Companies that put their people first and invest in HR will have the best chance of building strong teams that last. That’s where Namely can help.

Next up in Lerer Hippeau’s talent series, “What’s in a role,” is Eric Knudsen, Manager, People Analytics at Namely. From how he prioritizes people in people analytics to how founders can build teams that last, here’s a look at his role at Namely, the leading HR, payroll, benefits, and talent management platform for businesses.

Amanda Mulay: Can you tell us a bit about your background and how it led to your career in people analytics?

Eric Knudsen: My first introduction to psychology was in high school. I had a teacher that got me really excited about learning about human behavior, so I set off in that direction heading into college at the University of Albany. I graduated with a degree in Psychology and jumped straight into a Ph.D program for School Psychology. At the time, I was interested in using tests and measurements to improve education because a lot of school psychology involves assessment aimed to identify ways we can help students excel.

It was a year before I realized what interested me most about education were its organizational dynamics, how you can use data to help people excel, and the ways groups of people and their interactions can help them rise to success. I took the opportunity to transfer into a different Ph.D program, this time in Industrial-Organizational Psychology at Baruch College. My passion for data emerged when I started work as a graduate assistant in the administration of the City University of New York. There, I helped put data into the hands of some of New York’s top public education administrators to help inform decision-making about teacher certification and curriculum overhauls.

In 2015, I joined the small but mighty People Assessment and Analytics team at JetBlue Airways, which was my first full step into the world of People Analytics. During my time there, I supported the development of tests and tools used to hire the best candidates for key roles, including pilots and ticket/gate agents. In 2016, I moved to Namely to help them build the foundation for an internal data and analytics practice.

Eric Knudsen

Mulay: What does your role entail and how do you typically explain it?

Knudsen: My first role, as Senior Analyst on the People Operations team, was more of true internal people analytics work. In it, I identified new ways Namely could leverage our internal HR data to improve our practices (think performance management, compensation, engagement, etc.). When an employee starts at our company, we learn a lot about them pretty quickly. Within an employee’s first year at Namely, we learn about them a minimum of six times (quarterly engagement surveys, a new hire survey, and their manager’s quality of hire survey). Through this we can track how the overall employee experience is, and how well our new hires are integrating and performing.

We knew there would be a time when our internal processes would be mature enough that we could take it to our product and clients. That way, the impact of this work would have much greater reach: the 1,200+ companies and around 250,000 employees using our platform. It was then that I pivoted to Business Operations as the Manager of People Analytics. Now, I explore, build, and test new avenues for Namely to empower our customers to make more strategic HR decisions by leveraging their data and insights about their people.

So the short version is that I used to help one company learn from its data to make better decisions about its people, now I get to help over 1,000 companies do it.

Mulay: How do you keep the “people” in people analytics if it’s so data-driven?

Knudsen: Back in 2015, we were not talking about using data science and machine learning to solve people and talent problems. But, over the last few years, machine learning and data science methods have exploded across organizations, not just tech companies working on fringe projects. We can use data to answer questions like: What’s the probability a person will stay at our company for two years? How long until we get a return on our talent investment?

In some ways, a background in psychology helps preserve the humanity, because the ultimate goal is to try and understand people. When you try to solve people problems without that context, you run the risk of making decisions that can negatively impact them. It’s important to remember that although we can learn a lot from and about them, people aren’t spreadsheets. It’s hard to predict what they’ll do and how they’ll respond to things. This is why having that context matters.

Mulay: How is your role unique within the HR space?

Knudsen: Few people have had the opportunity to work as an internal-facing HR practitioner at an HR company (essentially doing HR for HR), and then go on to use that experience in creating strategy, product, and business opportunity for that same company. My current role allows me to take what we’ve tested and learned from internally at Namely, scale it up, and blend in data science and machine learning to impact the work experiences of over 200,000 employees at companies we work with.

Mulay: What do you find the most challenging about responsibilities?

Knudsen: Staying abreast of changes in analytics, data science, and machine learning could be its own full-time job. New methods of analysis are constantly popping up, and it’s not possible to be an expert in all of them. So in real-time I have to balance general awareness of new methods with the prioritization of methods that will solve the problems we’re actually tackling today.

On top of that, sometimes old methods from specific industries are re-purposed in others. Take “survival analysis” for example: this statistical approach originated in medicine as a means of determining the various probabilities that a clinical trial patient will survive to different time points. In people analytics, survival analysis is now used to explore and predict the probability that an employee stays with his or her company to certain tenures. We can now learn if there are certain ranges of tenure when employee turnover accelerates or slows, and intervene to improve the chance that we can retain our top-performing employees.

Mulay: Any observations from your career and Namely on how to build/scale a company that puts its people first?

Knudsen: People are an organization’s greatest (and often most expensive) asset. The keyword there is asset. Traditionally, employee headcount was considered a liability. Companies are coming around to the realization that without their people, they would have no other assets.

This idea of using thoughtful methods to find and nurture the most talented people for each job must begin on day one in a company’s life. If it doesn’t, the company will scale to realize that no one, not the leaders nor the employees, are doing their best and most passionate work. Backtracking to correct this at scale is very expensive, time-consuming, and almost always fails. You have to think about people from the get-go.

Mulay: What advice would you give to other people who are interested in pursuing a similar career path to yours?

Knudsen: Quietly challenge yourself to learn more about how to move from the basic reporting many already know (averages and percentages) to the study of relationships (correlations), and some basic statistical testing (t-tests and chi-square tests). This foundation of statistics is essential to your growth as someone interested in moving from core reporting to true analytics.

Second, to the extent that you’re able, get involved with people data today. Perhaps you’re in HR, maybe you’re not. Either way, express interest and offer your support on projects that involve HR data. The earlier you learn the joys and pitfalls of people data, the better equipped you’ll be to have meaningful impact.

Mulay: Any advice for founders looking to hire someone to head up people analytics at their company?

Knudsen: Early on, I believe it helps for the person to have some training in psychology. Later on in the people analytics journey, you can bring someone highly-technical on board who can accelerate (and complement) the work done by your first hire. In the first days, avoid the urge to do too much too quickly. You don’t need a Ph.D-trained analyst to begin reviewing and cleaning up your employee data. Step one is to clean this data where possible, and build processes that keep the data clean. Once a founder and executives feel trust in their people data, they might consider bringing in a trained analyst to begin fulfilling reporting and analytics needs.

When this first analyst hire (and every later one) starts, they should be given the space to explore, experiment, and learn about your data before you lean on them for key projects. It can take a while for any analyst to learn the ins, outs, and quirks of new data sources. You’ll be glad you gave them this time when you don’t have to backtrack on a new metric you insisted they report in their first week.

That said, I do think that as a field, HR is still struggling to find people that possess both a technical skill set and rigorous training with people. It’s a difficult line for any candidate to walk. Often, the solution is to build a team of people that balance each other out. From this, you’re more likely to get the harmony you need to conduct effective people analytics.

Interested in a role at Namely? Check out current job openings here.

Check out past posts in our “What’s in a role?” series:

Kendall Kelleher, Internal Recruitment Manager at Vangst

Liying Wang, VP of AI Training Operations at x.ai

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Lerer Hippeau

Lerer Hippeau is the most active early-stage venture capital fund in New York.