Running an Employee Base Audit
If you can value your company based on your customers, surely you can do it based on your team?
There is a bagel shop in New York City that I hate. It is called Apollo Bagels. I’ve never actually eaten there, but I walk past the line on 10th almost every week and shake my old, scroogey head. A bagel at Apollo Bagels ranges from $6 for a bagel with cream cheese to $17 for a smoked salmon sandwich. In order to eat one you must spend approximately 30 minutes waiting in line. The delivery website has, I kid you not, more t-shirts for sale than options for Bagels.
Down the street from me is a store called Bagel Bob’s. One of two stores, and running for over 20 years, Bob’s is an institution as far as I’m concerned. Their website uses Comic Sans (classic, perfect). I’ve never waited for more than 3 minutes but the store is always bustling. More importantly, a loaded bagel costs between $3 and $11.
Now, imagine you’re working in private equity — Big Sandwich, if you will — and you’re on the M&A team deciding whether to acquire Bagel Bob’s or Apollo.
At first glance, venture capitalists and investors might argue that Apollo is the better bet. It has more customers, a faster growth rate, and maybe even a higher contribution margin because its mouthwateringly high prices. Of the two companies, Apollo is the one that would probably be pitching itself as a tech (or better, AI) company in its investor documents.
But let’s take a step back. Bob’s, despite its slower growth, might actually be the better, less risky investment. Why? Because a substantial portion of its customer base comes back time and again. We’re talking about local office workers who swing by three times a week, a steady flow of hungover NYU students between classes, and neighbourhood regulars who’ve been loyal for 15 years. Plus, Bob’s offers much higher value for the money and, let’s face it, a $17 bagel? In this economy?
When we evaluate these businesses through the lens of customer-based corporate valuation, factoring in customer retention, and the frequency and consistency of its repeat purchases, Bob’s starts to shine. Bob’s isn’t going anywhere anytime soon. Apollo, on the other hand, derives a significant chunk of its revenue from one-time purchasers — think of all those tourists who visit once but buy two t-shirts — increasing the risk that it could fade as quickly as past fads like frozen yogurt shops or the cronut craze.
Sure, Apollo’s customers might be buying t-shirts and its brand might be more buzzworthy on their socials in the moment. But in terms of predictable, recurring revenue, Bob’s has the edge. Its customers don’t just come back — they practically have their own booths.
So while Apollo might dazzle with its rapid growth and social media clout, Bob’s represents the kind of stable, loyal customer base that can be a goldmine in the long run. It’s the difference between chasing the next big thing and investing in a proven, dependable classic.
The Customer-Base Audit
I’ve been lucky enough to meet some incredibly talented people in my life, and one of them is Professor Peter Fader. Pete is a marketing professor at Wharton who has spent decades obsessing over a deceptively simple question: what makes some customers more valuable than others? While most businesses were focused on their products and their quarterly revenue, Fader was watching the customers — studying their behaviour patterns like a biologist tracking migration routes. Frankly, he’s probably partly why a trendy bagel shop in Manhattan can charge $17 for a salmon sandwich.
But what makes Fader interesting isn’t just his academic work — it’s how his ideas have seeped into every corner of modern business. His big insight from my POV is that the value of a business isn’t just about what it sells today — it’s about who it sells to and whether they’ll come back tomorrow. It’s why Amazon cares more about your second purchase than your first. Customer-Based Corporate Valuation, co-written with another brilliant human, Professor Daniel McCarthy, argues that we’ve been valuing businesses wrong. Traditional valuation looks at a business like a black box: money goes in, products go out, count the difference, do some multiplication. Pete and Dan’s research says we should be looking at the customers themselves — their habits, their loyalty, their likelihood to bring friends.
Pete and Dan suggest we look at three key areas to understand the health and value of our customer base:
- Recency: How long since a customer’s last purchase.
- Frequency: How often a customer buys.
- Monetary Value: How much a customer spends.
I’m often inspired by leaders outside of People and Operations, so when I read Peter’s book “The Customer-Base Audit” (CBA) my immediate thought was, “I wonder if we can apply this to HR?”
The Employee-Base Audit
Here’s what happened when I started thinking about employees like Fader thinks about customers:
Just as customers are the foundation of any business’s revenue, employees are the core of its operational success. This is where the concept of an Employee Base Audit (EBA) came to mind.
This lens changed how I thought about:
- Recruiting (are we acquiring the right “customer” [employee] profiles efficiently?)
- Onboarding (how do we increase early satisfaction?)
- Development (what’s our retention strategy?)
- Alumni & “Halo” (can former employees behave like brand ambassadors?)
An EBA is a systematic review of your organisation’s workforce using principles which I’ve adapted from Fader’s CBA. It involves analysing employee data to uncover insights about tenure, engagement, retention, and development to better value your business and the work of your People team.
Core Metrics behind an Employee Base Audit
Employee Acquisition
The first step in an Employee Base Audit is understanding your acquisition patterns. The key things we’re looking for here are:
- Time to hire
- Cost per hire
- Quality of hire
- Organisational connectivity (or ONA)
Employee Retention and Attrition
Just as Fader emphasises the importance of retention in the CBA, employee retention is a critical piece of the EBA. Initially the cost of an employee supersedes their value, so getting an extended time to “pay back” this initial investment is crucial.
- Internal promotion retention rate
- Regrettable attrition rate per 10 exits
Tenure and Productivity Patterns
Analysing tenure in relation to productivity requires us to look at our employees as they follow different trajectories — some peak early, others show incremental growth, while some may plateau.
- Performance score quarter on quarter for at least 1 year
- Goal, KPI, or OKR achievement
- ARR per head
- Quota achievement in revenue generating roles
Even better would be to get a holistic, unbiased metric that quantifies employee quality over time — something more accurate, more democratic, and less prone to bias or gaming (e.g., pulling forward sales from future quarters to “hit the number” this quarter using generous discounts that did not happen to get flagged). This is where I’m really interested in the work that Incompass Labs has been doing. Using Assisted Assessments, Incompass leverages AI, machine learning and network analysis to produce an instant, fair, unbiased employee quality metric for each and every one of your employees. To learn more, check out their website here — I am really impressed by this team and what they’re applying from Marketing into HR.
Employee Segmentation
Just as CBA segments customers, an EBA can help you analyse employees based on tenure, performance, engagement levels, and career trajectory. Instead of looking at headcount, start looking at “cohorts” — groups of employees who joined around the same time. The patterns can be fascinating. Same role, same compensation, wildly different outcomes.
The most insightful cuts are usually:
- Start date (quarterly cohorts)
- Department
- Level
- Source of hire
- Manager
- Geographic location
- Interview feedback
Running the Audit
First, you’ll need to gather data from multiple sources. I’ve created a simple template for you here with the fields I think are most helpful.
When I first started analysing employee data with a more commercial lens, I expected to find simple patterns: people join and they either improve or leave. What I found is some are sprinters — they burst onto the scene, delivering incredible value in their first six months, but then hit a ceiling. Then there are the marathon runners. One of our engineers at Whereby, for example, seemed fairly steady in their first year. Their performance reviews were solid but not spectacular. But every quarter, they improved by small, steady increments. By year three, they were leading some of our most critical projects. They hadn’t just grown in skills — they’d built deep institutional knowledge that made them consistently valuable.
This is where the magic of segmentation comes in. Instead of just labelling people as “high performers” or “needs improvement,” I created a graph where the vertical axis shows current performance, and the horizontal axis shows their trajectory (are they accelerating, shifting back and forth, plateauing, or declining?).
I then added two more dimensions: the size of each person’s bubble showed their tenure (bigger bubble = longer tenure), and if I was feeling fancy the colour intensity could represent their revenue impact.
When I ran this initially I noticed that our highest performers tended to cluster in three distinct groups:
- the “rapid risers” (smaller bubbles, high performance improvement)
- and the “seasoned anchors” (larger bubbles, steady strong performance).
Now, if you’re running this analysis yourself you could identify the source of these cohorts and what may connect or unify them outside of just tenure and performance. For example, were the rapid risers were hired from specific competitors or through employee referrals. The seasoned anchors could be those who have all gone through an internal crisis or major manager change that forced them to level up.
Doing this kind of analysis should lead to valuable insights about what actually predicts success in our company. It shouldn’t just about past performance or years of experience, but finding where the best performers share certain patterns and where you could take intervening action.
Peter Fader changed how we value businesses by showing us that customers aren’t just transactions — they’re patterns, behaviours, and potential. What if we looked at our employees the same way? Think of it as Fader’s customer analysis framework, but turned inward. Instead of studying how customers buy, we study how employees grow. Instead of tracking purchase patterns, we track career trajectories. Instead of customer lifetime value, we measure employee lifetime impact.
So much more work to do, and what fun it is to do it!
Ok that’s all from me, folks. 👋
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