Let’s say you have 100 people on a sales team. Can they all be great? Most sales leaders say no. Conventional wisdom will say something like ten of them can be exceptional. Ten of them will be dogs. And the other eighty will fall somewhere between “solid performers” and “good enough to not be fired.”

I hate conventional wisdom. Especially when it’s as destructive as this. And make no mistake, this is destructive logic with little more than a baseless rule of thumb at its core. Nonetheless, most sales leaders pretty much accept the 10-80-10 performance standard as an incontestable law of nature. In so doing, we are inherently setting an artificially low bar with which to measure our success. Provided you have a great offering and a large enough target market, the goal of a sales leader should be to ensure that every salesperson on the team performs spectacularly.

Ironically, the KPIs – key performance indicators – that many sales leaders rely on to measure, predict and ensure sales rep success often actually perpetuate tiered success levels in which too many salespeople fail to meet their potential.

The problems with KPIs stem from sales leaders’ perceptions of KPIs and the opportunity cost of not taking a more scientific approach to understanding a company’s actual predictors of sales success:

Unreasonable Expectations & Emphasis

Think about your own sales KPIs. Do you have salespeople who hit all the KPIs, but still land on the lower half of the leaderboard? Do you have people at the top of the leaderboard who haven’t hit all their KPIs? Of course you do! In itself, that’s not a problem, but simply illustrative that most KPIs aren’t the locked and loaded predictors that sales leaders might wish they were.

KPIs are usually created with the right intentions. In some cases, they are meant to get out ahead of problems before they become systemic. In other cases they might be intended to set minimally acceptable levels of effort or output required by every member of the sales team. In these senses, KPIs can be directionally helpful predictors of success and failure.

However, KPIs are usually created from team averages without a detailed understanding of individual rep strengths or nuanced attributes of individual deals. Too many sales leaders overlook these differences and instead see the KPIs as black and white predictors of success. This becomes management by numbers and these leaders have teed themselves up for disappointing surprises.

Wrong Incentives

When generic KPIs are overemphasized, they incentivize the worst possible behaviors at all levels of the sales organization. Sandbagging, or hiding deals, is heightened in organizations that overemphasize sales cycles or uniform stage velocities – even though everyone will acknowledge that there may be legitimate and compelling reasons for certain deals to progress more slowly than others. When organizations overemphasize metrics for forecast calls, reps often feel compelled to “commit” deals that they know are a little more than a shot in the dark. Organizations that lean too heavily on activity metrics often find reps logging questionable calls or sending superfluous emails that don’t bring a buyer any closer to a decision. Companies that inflexibly demand a 3-to-1 or 4-to-1 pipeline ratio often see leads prematurely being categorized as opportunities, and sacrifice quality for quantity.

The result is a morass of bad sales data that only pushes the target of understanding the true drivers of success and failure farther away.

Ignoring Half the Story

When defining new KPIs, sales leaders often look at attributes of the deals that won or the sales people consistently at the top of the leaderboard and attempt to draw conclusions. That seems like a reasonable starting point, right?

As a starting point, dissecting attributes of the best salespeople or winning deals is fine. But if the process ends here, sales leaders are positioning themselves for disappointing surprises because they haven’t considered the traits of underperforming reps and deals that lose. Too often, we find that companies’ chosen KPIs would have varied only negligibly had they been based on attributes of losing deals or reps outside of the top 10%.

Static indicators

What worked in sales yesterday, doesn’t always work today nor is it guaranteed to work tomorrow. Yet too many sales organizations are built around KPIs that haven’t been re-evaluated in years or don’t more heavily weight recent events.

And versus Or

Think about your company. What is fundamentally different about the deals that your organization wins from the deals that you lose? Is it certain buyer attributes? Is it certain seller attributes? Price? Product? Activity levels? Does sales cycle or stage velocity mean anything? Competition?

Most sales leaders intuitively recognize that all of these variables (and more) simultaneously impact every deal in the sales pipeline. Success and failure are not decided by one variable or another. They are the product of lots of different elements all moving simultaneously. Yet most KPIs are derived from single variable data silos, without any regard for nuances that might predict individual deal outcomes and rep success levels.

Your Salespeople

Great salespeople are dreamers. They naturally “think big” and have an “eat what you kill” mentality. They are smart, creative and competitive. Being less than spectacular is unfathomable. They have an ego, but they’re not arrogant. They will learn from the best, but they need to be better.

This is the DNA that we all hire for and it’s the DNA that positions us all for success.

When we forcibly jam these forces of nature into a sales mold based on perceived success drivers for a collection of other reps, we are discounting each individual salesperson’s individual strengths, weaknesses and abilities to succeed outside of that precise mold. Instead of capitalizing on the attributes that position each salesperson and each opportunity in the pipeline for success, we are creating cadence-driven robots instead of thoughtful business leaders.

Jim Dries is the CEO of piLYTIX, a data science as a service company serving heads of sales and their teams.