Luck is one of five factors that define a salesperson’s success, a concept I introduced in a post discussing why you should assess luck’s influence when interpreting sales results. In this post, I’ll explain how to quantify luck’s influence.

How lucky is my top salesperson? The idea of quantifying luck’s impact on performance is a well-researched area, with contributions from Tom Tango and others. One way to apply these ideas is to gather data on performance across many salespeople, measure the variance and then subtract out the variance you would expect if the results were totally driven by luck.

This approach is best applied to transactional sales processes with binary outcomes: a win or a loss. Sales processes that fit this model include insurance agents quoting on new business, and inbound telesales reps attempting to retain customers canceling a subscription.

Let’s walk through an example for two telesales teams that sold small-business lending and credit products for the same company. One team operated on an outbound basis (cold calling), the other inbound. On the inbound team, calls led to sales 45% of the time, and individual salesperson win rates ranged from about 40% to 55%. Outbound was much less encouraging: Outbound dials led to sales less than 1% of the time, and no salesperson exceeded a 2% success rate. The graph below summarizes the distribution of performance relative to the average win rate for each team:

luck graph part2c

To understand how luck influences each sales team, we must estimate the expected distribution if the variance in sales outcomes were random. Imagine that instead of salespeople, we staffed the call center with robots, each one programmed to manage the customer conversation in the same way. We wouldn’t expect the robots to convert precisely 450 out of every 1,000 inbound calls. Just as a batter interacts with different pitchers, a salesperson interacts with different customers, and those customers serve up a lot of unpredictability. 

We estimate the expected performance variation due to luck by applying the binomial distribution and estimating sales performance if luck drove the observed results entirely. 

You can see the distribution of actual performance is wider than we would expect if luck alone drove the results. And that’s a good thing from the salesperson’s perspective—suggesting that salesperson actions affect outcome. We can complete the picture by subtracting the variance from luck (the expected distribution) from the overall variance. Doing so suggests the following:

  • Inbound: About 15% of the performance distribution in the measurement period is attributable to luck, and about 85% is attributable to the salesperson

    inbound luck 
  • Outbound: About 25% of the performance distribution in the measurement period is attributable to luck, and about 75% can be attributed to the salesperson
    outbound luck 

There are no differences in “opportunity” across salespeople—calls are randomly distributed; the selling effort, as measured by call volume, was consistent across salespeople. Thus the salesperson’s contribution to the performance variation—85% for inbound, 75% for outbound—is entirely due to talent and how he or she applies it.1

Outbound sales results are more luck-driven. A certain logic suggests that outbound sales—or pure prospecting—is the more skill-dependent job: In outbound sales, the salesperson must navigate all aspects of the selling process, and often must convince an unready buyer to purchase. The outbound selling role is certainly the harder of the two jobs—measured by salesperson turnover or job satisfaction—but that does not mean it is the more skill-dependent.

You’ve heard that much of the buying process is complete before a prospect contacts a salesperson, and that is certainly true of the inbound team, which benefits from the company’s strong brand awareness and positive positioning. The above chart shows that even the least successful inbound salesperson wins about 40% of the time—sales attributed to the company’s marketing department and brand equity.

That still leaves many performance outcomes up for grabs, in the 40% to 55% conversion range. Think of those additional 15% of calls as “marginal” opportunities—customers who might buy, depending on the conversation. Outcomes of marginal calls can sometimes be attributed to luck, good and bad. But roughly 85% is explained by something other than luck.

Contrast that with the outbound salesperson. Again, one might conclude that the least effective outbound salespeople produce zero sales, or close to it. Thus fueling the belief that outbound sales are 100% salesperson attributable—no calls, no sales. Simplistically true, that perspective ignores that outbound salespeople can be lucky (or unlucky) on any call. Even if calling accounts for 100% of sales, it’s not fair to say that talent, skill and effort account for 100% of results.

Executives often miss this point. Looking these data, it’s easy to fixate on the top producing outbound salespeople generating 10 times more wins than the bottom producers, and to peg them as needing more improvement. While the spread is narrower in inbound (top performers generate only 37% more than bottom performers), the potential impact of performance improvement is actually greater. For inbound, it’s a difference of more than 100 wins over 1,000 calls fielded; in outbound, it’s only a few dozen wins over the same call volume.

Now that I’ve illustrated an approach to quantifying luck in sales processes, let’s return to the application of that newfound knowledge … in my next blog post.

[1] Remember that this observation applies for a specific measurement period—in this case, a calendar quarter. The outcome of any single sales call could be attributed wholly to skill or luck, or any combination therein. We’re looking across many sales calls to make this assessment.

Topics: Jason Brown, sales process design, role of luck in sales, sales performance