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There's an awful movie from the 90's called Days of Thunder that (despite its awfulness) has one really good point in it:

In the movie, the "wise" pit crew chief, Harry Hogge (played by Robert Duvall) educates the "overly aggressive" race car driver, Cole Trickle (played by Tom Cruise) on how driving in a more "controlled" manner saves his tires. This driving style keeps him from sliding too much in the turns and allows him to keep his speed. The results are faster times at a lower risk.

I like this analogy because it makes two key points: a controlled pace is more effective "long-term" than an uncontrolled one, and an uncontrolled pace actually creates physical (or emotional) wear and tear.

I've been thinking about sales onboarding and ramping a lot these days, and when this story popped in my head (from deep in the recesses of my bad movie memory banks), I couldn't help but think about "seller turnover".

I know this might sound like a bit of a stretch, so let me explain:

I believe there is a difference between the concepts of seller "turnover" and seller "churn". "Turnover" is the controlled approach of removing the least competent and/or under-performing salespeople from your organization. And I believe the more you are managing “turnover”, the better your long-term revenue. "Churn", on the other hand, is the departure of sellers because their level of frustration has exceeded their belief that they can be successful at this company. Because you are losing average or possibly even exceptional salespeople, their loss has a direct negative impact on your revenue in both the short-term and the long-term.

Leveraging Class-based Turnover Rates to Determine Sales Enablement Priorities In my last blog "Bubbleball, (Analytics for Seller Onboarding)", I introduced the importance of evaluating your seller's performance based on "class". In this blog, I want to show you how you can use an analysis of "Churn Rates by Class" to identify sales enablement issues and connect them to mid and long-term revenue performance.

For this analysis, I recommend using “Hire Year” as your class designation. Prologue - A comparison of turnover rates by class In order to give you a comparison that helps illustrate this point, I am going to introduce four different "turnover models". These models are simply different churn rates with an emphasis across 2-3 "classes".

Three of these models show a spike in unwanted churn affecting different segments of sellers. There are any number of reasons why groups of sellers might leave your organization in a "cluster":

  • New Hire Churn - Lack of early performance and a concern for their future performance is leaving both new hires and managers frustrated and challenged. Instead of "riding it out", they decide to go elsewhere.

  • Emerging Veterans' Churn - Losing your emerging veterans is typically the result of unwanted changes or reduced potential for success or income. Reduced territories, appropriated accounts, misaligned compensation plans, or a concern with their company's strategic direction (and their ability to profit from it) are all concerns that might drive a reasonably successful veteran to look for greener pastures.

  • Senior Sellers' Churn - It would be unusual to see this kind of churn; I presume it would occur only if the company woefully under-appreciated the impact of some dramatic changes. All of the examples listed above in the Emerging Vets section would apply. Generally, it would have to be a drastic change to drive these guys elsewhere: like a massive territory restructuring, sales strategy (from "farmer" to "hunter") adjustments, or significant compensation plan reductions.

  • "Controlled" Turnover - this model assumes that only the poorest performing sellers are removed due to low revenue generation and sellers are not leaving independently.

  • A couple additional things to point out about the models:

  • While the churn numbers "by class" can vary significantly, in each of these examples, the "average", company-wide Seller Churn Rate is only 16%. At 16%, a company will probably think that they are "in line" with their industry average.

  • However, as noted, while the churn rates across specific classes can spike significantly, and depending on which "generation" of sellers you're losing, the impact of their loss can have a significant impact on your mid-term and long-term revenue growth.

Step #1 - Create a Population Model Before we can begin the revenue impact analysis, we need a baseline. The below chart illustrates how your seller "population" can be segmented by class (in this case "years with the company"). In this particular chart, the ratios for each class are based on an actual company. (Total sellers was reduced to 100 to make it easier to illustrate the impact of churn). Please note that the company has a goal (or at least an "expectation") to grow the sales force by 10% over the next three years. When we apply a turnover model to the population model, the effect looks like this: The way this population model works, the "# of Sellers" in the "Start" year are reduced by the FY 2 Churn Amount for the next year. So, in the upper left corner, the Year 1 sellers (24) is reduced by the FY2 Churn of one (1), and becomes the Yr 2 "Class" with only 23 sellers.

Step #2 - Define your Revenue Spread by Class One more important step before we begin our analysis: we need to calculate what the revenue impact of each class is "on average". In other words, take your average revenue per rep (for this company, that number is $1.04M) and calculate the average revenue per rep by class (for "Year 1 New Hires" for instance, that number is $627K. $627K divided by $1.04M equals approximately 60%). You can see that Senior Sellers with over 7 years of experience are this company's top performing reps. But even in Year 3, their reps are generating an above average amount of revenue. (Please note that this model has nothing to do with "Quota". Just because Year 3 Reps were above average in revenue does NOT mean they were achieving their quota).

Step #3 - Apply the Turnover Models & Average Revenue to the Population Model to see the Impact of Churn This is the most important part of the analysis. We can now take the starting class numbers, subtract the turnover amounts by class, and calculate potential revenue based on how many sellers are left. Let's take a look at the different scenarios:

1) New Hire Churn A couple key points about what you're seeing: The light green boxes show the reduction of sellers most affected by the turnover model. The yellow boxes highlight important data to notice. This Churn Model has the highest total revenue (of the four models) with 136% growth over 3 years to approximately $141M, because the company is only losing new hires, who generate the smallest average revenue. This would seem to imply that this turnover model might not be a bad thing. This could be viewed as the "Darwinian" approach to onboarding. Let only the strongest survive, and those that do will become solid senior sellers. However, there may be a concern (best illustrated by the highlighted number "5" in the Yr 5 Class in FY4). This company is losing so many new hires that they may not be building enough Emerging Veterans.

2) Emerging Veterans Churn

  • In this example, the class years 4, 5 & 6 see the most significant reductions.

  • Revenue growth of 133% to a total revenue of $138.8M is still solid.

  • Looking at the three highlighted boxes, the loss of emerging veterans could be a long-term concern, but the overall number of senior sellers may insulate the company from any significant risk.

3) Senior Sellers Churn

  • This may be the worst scenario: total revenue of approximately $134M is almost 4-5% shy of the previous two scenarios.

  • Clearly, losing your senior sellers (if they are the largest revenue producers on average) would be a significant hit on short and mid-term revenue production

4) "Controlled" Churn The last scenario is intended to illustrate the difference between the previous churn models and a more structured churn based on poor performance.

  • Please note that the total revenue at $139.4M is the second best among all of the turnover scenarios.

  • AND, there is still a healthy pipeline of senior sellers and emerging veterans, which bodes well for future revenue performance.

  • Presumably, since this controlled approach would be focused on reducing the bottom 2-3 revenue performers per class, the average revenue (contrary to the other three scenarios) could actually improve over this three-year time period.

Conclusion Back to the Days of Thunder movie... in the scene I described above, the pit crew chief was happy to have made his point. His way was faster. After 50 laps, the controlled driving approach was a whopping 6 seconds faster. So, what's so important about such a minuscule improvement? It was the combination of better speed AND less risk of failure.

The analysis that I have shared with you is intended to provide you with two key insights

  1. First, by keeping a close eye on your seller churn rates by class, you can identify any trouble spots you might have with the overall team.

  2. A controlled turnover approach, reducing only a couple reps per class based on overall poor performance, will maintain or even improve your revenue performance overall while reducing the risk of losing too many of any one class of sellers.

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