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revopsAf the podcast

Episode 28: Hiring Moneyball

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In this episode, RevOpsAF co-host and RevOps Co-op CEO Matthew Volm sits down with Jeremey Donovan, Operating Advisor to Insight Partners' portfolio companies, to talk about hiring strategies rooted in data-driven decision-making - what he calls "Hiring Moneyball." Jeremey shares insights from his extensive career in revenue operations, highlighting key takeaways on what makes a great hire in RevOps, sales, and beyond.

If you’ve ever wondered whether job tenure, background, or even prior sports experience matter in hiring decisions, this episode is packed with actionable insights to guide your approach.

From Engineering to RevOps: A Non-Linear Path

Jeremey’s journey into revenue operations was anything but traditional. Starting as a semiconductor engineer, he eventually transitioned into sales and revenue strategy, leveraging his analytical skills to optimize go-to-market functions.

"RevOps brings together strategy, people, process, and technology in a way that is intellectually stimulating and constantly evolving." — Jeremey Donovan

Like many in RevOps, Jeremey’s path was non-linear. Whether starting in engineering, consulting, or even geology, those with diverse backgrounds often find success in revenue operations.

The Data-Driven Approach to Hiring

Inspired by the "Moneyball" philosophy popularized in baseball, Jeremey applies statistical analysis to hiring decisions. Instead of relying on gut feel, he advocates for analyzing candidate attributes that statistically correlate with job success.

For instance, while hiring sales development representatives (SDRs), Jeremey’s research found that:

  • Recruiting backgrounds (e.g., agency recruiters transitioning into sales) led to higher success rates
  • Tenure of 2-3 years in prior roles was a strong predictor of retention and performance
  • STEM majors performed better, though they were underrepresented in sales hiring
"If you can get a few percentage points edge in hiring, it compounds across your team’s performance." — Jeremey Donovan

Do Team Sports Make Better Salespeople? The Data Says…

One long-held belief in sales hiring is that former athletes, especially those who played team sports, perform better. However, Jeremey’s analysis uncovered a surprising insight:

  • For SDRs: Team sports did NOT correlate with success, but individual sports (e.g., golf, swimming) did.
  • For Account Executives (AEs): Team sports WERE positively correlated with success, likely due to the collaborative nature of enterprise selling.

What Matters Most in CRO Hiring?

When analyzing successful Chief Revenue Officers (CROs), Jeremey identified a key trait that stood above all others: tenure in previous roles.

CROs who had spent at least two years in a prior role were significantly more likely to be successful. Conversely, frequent job-hopping was a major red flag. Surprisingly, industry experience - often considered crucial - wasn’t statistically significant in predicting CRO success.

"CRO job-hopping is highly correlated with failure. The best candidates have demonstrated staying power and progression in their careers." — Jeremey Donovan

Why Hiring Strategy Matters for RevOps Professionals

As a RevOps leader, hiring across the various GTM teams may not always be in your job description - but it should be. The right hires can significantly impact your ability to execute strategy effectively. Jeremey encourages RevOps professionals to:

  • Analyze their top-performing employees’ backgrounds to identify hiring patterns
  • Use data-driven hiring practices to optimize for success
  • Get involved in hiring decisions to ensure strong operational alignment
"Hiring isn’t just an HR function. RevOps leaders need to play a role in bringing in the right talent to set their teams up for success." — Jeremey Donovan

Final Thoughts

RevOps and revenue teams operate in high-stakes environments where every hire matters. Jeremey’s approach to "Hiring Moneyball" offers a compelling case for bringing data into the hiring process - whether for SDRs, AEs, or CROs. By leveraging historical patterns and predictive analysis, revenue teams can optimize for long-term success.

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