Nimble business leaders who are moving away from outdated measurement practices and relying on data science are better positioned to predict and ensure success of their sales and fundraising teams
Let’s say you have 100 people on a sports sales or university fundraising team. Can they all be great? Most revenue generation 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 and fundraising 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 revenue-generating leadership should be to ensure that every individual on the team performs spectacularly.
Ironically, the KPIs – key performance indicators – that many sales and fundraising leaders rely on to measure, predict, and ensure success often actually perpetuates tiered success levels in which too many salespeople or fundraisers fail to meet their potential.
The problems with KPIs stem from revenue generating leaders’ perceptions of KPIs and the opportunity cost of not taking a more scientific approach to understanding a company’s actual predictors of success.
Unreasonable Expectations & Emphasis
Think about your own sales KPIs. Do you have people 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, this scenario is not a problem, but it illustrates that most KPIs aren’t the locked and loaded predictors that sales and fundraising 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 revenue generating teams. In these situations, KPIs can be directionally helpful predictors of success and failure.
However, KPIs are usually created from team averages without a detailed understanding of the individual team member strengths, or of nuanced attributes of individual deals. Too many 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.
When generic KPIs are overemphasized, they incentivize the worst possible behaviors at all levels of revenue generating units. Sandbagging, or hiding deals, is heightened in organizations that overemphasize sales and fundraising 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 calls or contacts, revenue generating team members 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 teams logging questionable calls or sending superfluous emails that don’t bring a prospect any closer to a decision. Companies that inflexibly demand every 3 or 4 leads convert to one opportunity often see leads prematurely being categorized as opportunities, and sacrifice quality for quantity.
The result is a morass of bad data that only pushes the target of understanding the true drivers of success and failure farther away.
Ignoring Half of the Story
When defining new KPIs, revenue team leaders often look at attributes of the deals that won or the 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 revenue generators or winning deals is fine. However, we find that companies’ chosen KPIs would have varied only negligibly had they been based on attributes of winning deals or reps inside of the top 10%. If the process ends here, leaders are positioning themselves for disappointing surprises because they haven’t considered the traits of underperforming individuals and deals that lose.
Revenue generating tactics that worked yesterday won’t always work today, nor are they guaranteed to work tomorrow. Yet too many revenue generating entities are built around KPIs that haven’t been re-evaluated in years or don’t more heavily weight recent events.
And vs Or
Think about your company. What is fundamentally different about the deals that you win from the deals that you lose? Is it certain buyer attributes? Is it certain seller attributes? Price? Product? Activity levels? Does sales or fundraising cycle or stage velocity mean anything? Competition?
Most revenue generation 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 individual success levels.
Really good sales reps and fundraising professionals are dreamers. They naturally “think big” – and 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 mold based on perceived drivers of success, we are discounting each individual’s strengths, weaknesses, and abilities to succeed outside of that precise mold. Instead of capitalizing on the attributes that position each salesperson or fundraiser and each opportunity in the pipeline for success, we are creating cadence-driven robots instead of thoughtful business leaders.