Experts and probabilities in sales. Why sales leaders should care.
Look no further than the NBA Playoffs to provide a platform for examining experts and probabilities in sales.
During a famous NBA Playoff series, the Oklahoma City Thunder roared to a shocking 3-1 lead in their best-of-seven games against the Golden State Warriors. A few loyalists held out hope that their team could come back and sweep the final three games. The rest of the sports world wrote the Warriors off. Media pundits cited the highly unlikely statistical probability that the Warriors would be able to come back. A few of the more aggressive sports analysts even got specific. “About 4%” was the likelihood that was repeated convincingly by many sources. They referenced actual data – and seemingly lots of it.
However, even non-mathematically inclined people can think back to junior high school math. For example, recall the probability of flipping a coin three times for three consecutive heads (or tails). That is one in eight – or 12.5%. Going back the series, assume the teams are roughly an even match. In this case, likelihood of the team down 3-1 resulting in a victory is closer to 12.5%. To the casual observer, this success projection that doesn’t align with our own snap judgment. Therefore, it might imply that there’s a deep mathematical analysis.
Experts, probabilities, and sales – the problem with attaching to one statistic
But, cut through all the noise surrounding these pundits’ arguments in favor of Golden State’s pending demise. In doing so, we quickly see they are attaching to one only statistic. That is, in the last 232 NBA playoff series that started 3 – 1, only 9 teams who were down came back to take the series. The 4% is simply the quotient of winners (9) divided by all previous 3 – 1 series (232).
So what is so wrong about this approach? After all, none of these pundits said that a Golden State comeback was an impossibility. Golden State was clearly in a suboptimal situation. But was it really as dire as the prognosticators suggested? Probably not.
The approach taken by these armchair data analysts highlights the problem with experts and probabilities. Media analysts tend to rely exclusively on one statistic in a vacuum. A more complete approach would have included a detailed analysis of the history of those earlier 232 series. Were there identifiable characteristics of those nine winning teams that mirrored Golden State? Even if we assume that the 9-of-232 statistic was an important factor, was there anything about Golden State’s team or each of the next three games that would make it a potential outlier? Was there some anomalous circumstance that guided Golden State to a 3 – 1 deficit, but might not be present in the next three games?
Sales, and every industry, has experts and probabilities and is subject to judging based on isolated variables
Professional sports media is not the only industry subject to flaws in their approach to data. As companies are retooling to become more data driven, we see these same mistakes play out every day in sales organizations around the world. Sales reps and their managers attach to one clearly understood metric or another and ignore all other data points that could suggest a very different outcome. They then make seemingly reasonable conclusions on all manner of sales challenges based on those singular data points:
Purchase History: “This prospect purchased at his previous company and loves us! This deal will definitely close!”
Forecast category: “My team always closes exactly 90% of our commit forecast.”
Perceived rep tendencies: “Diane is a sandbagger, but she always comes through in the end, so I will just put her at quota.”
Lead Score or Opportunity Source: “We have one week left in the quarter. Please stop wasting your time on opportunities with a low lead score.”
Deal Age: “Karen is typically spot-on with her forecast, but this deal has been in the pipeline for too long, so I don’t believe it.”
It is understandable why sales leaders are left to judgment calls based on these isolated variables. Every organization has to contend with finite sales resources and a constantly ticking clock. Sales managers need to focus their reps on deals that appear likely to win. Likewise, they have to submit forecasts that at least acknowledge observed patterns of rep behaviors.
The power of analyzing all impactful variables
However, when analyzing winning and losing deals, all impactful signals and the interconnected nature of those signals contribute to a meaningful examination.
In the short term, we have to assume that certain deals that should win will get less attention than they merit. Other deals that statistically face the longest of odds will be subject to overinvestment of time. Over the longer term, a lack of awareness of the true drivers of wins and losses will make us less equipped to architect our sales organizations for success.
Whether we are discussing a sales rep who has a well-established pattern of overpromising, or a basketball series that has well-established patterns of winning and losing, there are almost always other data points that will influence the true probability. Understanding that data will minimize the surprises that leadership teams (and Thunder fans) hate.
