dials = capacity = labor = $$$

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Your top 10% book 41%.

On the inverse: your bottom half books 11%.

We’ve been auditing call logs from potential customers before they’re on TitanX, and the variation in rep performance is vast. The best 10% is 45x more effective than the worst 10%.

But most useful is what this surfaced related to the Pareto principle - the observation that 20% of the effort (or input or cost) within a system produces 80% of the results.

So here’s what we found from a sample of 775 reps, 2.3M dials, 120K connects, and over 10K meetings:

What a meeting actually costs:

Across 20 benchmarked teams, using each team's own real dial and meeting activity, standardized to a $100K blended OTE:

The top 20% of reps generated that 61% of meetings at $963 per meeting.

The bottom 80% cost $5,967 per meeting.

One could argue that this is why variable comp is necessary, but it doesn’t make up for a difference this large. Not even close. That cost doesn’t even include data, tools, enablement/training/coaching, benefits.

Every dollar spent on the bottom 80% buys roughly a quarter of what the same dollar buys on the top 20%. And it doesn't matter how you add it up. Take the typical team, you get 4.4x. If you pool every dollar and every meeting across all 20 teams, you get 6.2x. 

Before you say "not my team" - we checked:

20 teams, zero exceptions.

The tightest gap between the top 20% and bottom 80% in the entire sample is still 2x. The widest runs is more than 10x. There is no team where the top and bottom cost the same to run.

This is a universal gap.

If you take the connects from the bottom 20% of reps, and give them to the top 20% of reps (borrow the best Connect to Meeting Rate) you add 17% more meetings.

That’s based purely on who is doing the calling.

Want to see the numbers for your own team?

Pull your call logs for the last year and ship ‘em over. You can anonymize rep names of course, but it’s not worth not knowing the true cost.

Definitely smarter to analyze the data in depth, at the call log level, before you go firing everyone. 

The call log audit scans 17 different optimization levers and failure modes. For example: is the bottom 20% failing because they’re hamstrung by spam-flagged numbers? For a lot of teams, that was exactly the case:

7 teams had 40%+ dials come from spam-flagged numbers.

Ouch.

We already have the data.

Stick around.

The next few months you’re going to see a lot more where this came from.

Thanks for reading,

Evan Dunn (LinkedIn)

P.S. How’d you feel about Artisan’s billboards? C’mon be honest.