The following practice seems to be gaining some momentum by well-intentioned sales leaders and their B.I. partners.
A pro sports sales leader’s activity dashboard showed that that some reps were calling certain prospects 10 or more times. She believed that some prospects were receiving too much attention- and that others must be receiving too little attention.
The team’s BI leader informed the head of sales that 99% of all sales closed with 6 or fewer interactions with the sales prospect.
The sales leader interpreted ‘6’ as a “magic number;” sales reps should strive to have 6 touchpoints (calls or emails). Until a sales opportunity achieves 6 touches, it’s a viable prospect that should be diligently worked. After 6, the chances of success are so limited that they should close it out and focus on bringing new leads into the sales funnel.
Conceptually, approaches like this are designed to make each member of the sales team more productive. The idea – stop wasting time on the wrong prospects – is great. The results of this strategy, however, nearly always disappoint.
The disappointing results can be traced back to basic mistakes that the sales leader chose when defining her activity KPIs. We have written extensively about KPI mistakes that sales leaders and their B.I. counterparts make:
Ignoring Really Important Data
The B.I. leader’s information was factually accurate, but incomplete. Painting a more complete data picture by pulling a few more metrics shouldn’t be too difficult for a competent B.I. leader. Strategies defined my narrowly focused data sets are dangerous, in that they ignore information that might show flaws in the strategy or create a pathway toward better strategies. Every sales leader should feel empowered to ask questions like:
We know information about the wins, but what do we know about our losses?
How do these metrics compare to all of our open opportunities?
What can we learn by adjusting the variable?
In this example case, the B.I. leader should have also noted that:
- The team annually closed 4% of its entire opportunity pipeline
- 95% of all sales close with 3 or fewer interactions
If these were the sales leader’s only data additional points, a quick mathematical calculation would have proven the flawed conclusion:
The sales leader, who was attempting to reduce the number of inefficient activities, was actually encouraging the sales team to do more work than justified on 99.8% of all pipeline activities! (Editor’s note: if you are unsure of this math, but want to geek out with us, we’re happy to talk you through this).
Further, the basic premise that 1% of her pipeline amounted to an inefficient hunt for a needle in a haystack encouraged her to intentionally ignore 1% of deals that she shouldn’t have to abandon.
‘And’ versus ‘Or’
Think about your team. 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 too many sales strategies are derived from single variable data silos like in the example above, without any regard for nuances that might predict deal outcomes and dictate more effective outreach strategies.
Every sales rep has nuanced strengths and weaknesses. When we forcibly jam our salespeople into a 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 when we manage them with any version of a “one-size-fits-all” approach.
- DATA STRATEGY OR DATA HOARDING? - September 28, 2020
- Four Questions that will Kill Sports Comeback Strategies - August 25, 2020
- Larger Prospect Pools = Greater Sales?
Part 5 of the piLYTIX Sports series “Challenging Conventional Wisdom”- September 12, 2019