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Revenue Operations

RevOps Mastery: Expert Insights on Maximizing Sales Performance, Efficiency and Capacity

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Vernon Bubb, Partner of Stage 2 Capital, and Werner Schmidt, Cofounder and CEO of Lative, stopped by the RevOps Co-Op to drop a ton of knowledge around measuring and predicting sales efficiency and sales capacity. Werner and Vernon have a wealth of experience in Revenue Operations. We appreciated Vernon's additional perspective as a venture capital investor. This was a timely conversation – the market is experiencing a lot of turmoil, causing a significant shift in how investors think about a company's value.

"In the past, there was a correlation between revenue growth and the value of a company. That's no longer the case. There's now a greater correlation between the value of a company and sales efficiency. So it's inevitable to me that in the long term, there will be much more focus on measuring and managing sales efficiency because ultimately that's what drives the value of companies and what we should be aligned to." Vernon Bubb, Partner at Stage 2 Capital.

Is There a Wrong Way to Calculate Sales Productivity?

You may think that sales productivity is simply a calculation of the percentage of your sales team consistently hitting quota – perhaps with some time-to-ramp calculations thrown in for good measure (we did!).

Theres a more accurate way to look at sales productivity.

Vernon and Werner suggested an alternative recommended by top researchers like Forrester. The focus should be on dollars sold per hour a salesperson can be productive. This calculation takes into consideration time off for leave or vacation. It also demands a more precise calculation of exactly how long it takes for the average salesperson to become productive.

The reason why measuring sales representatives against quota is problematic is that quotas change. They may be different because an agreement in a particular region demanded a different compensation model than the other regions, or perhaps goals had to be adjusted mid-year due to overly ambitious goals.

"When we use quota attainment to measure performance, a lot of variables go into setting the quotas. One of the areas I always struggled with when I was back at Citrix – we had a number of salespeople in each of the Geos. We had set the quotas before the start of the year because we needed to get the quotas out on day one. And we would notice that we'd bring out the quotas, and then you'd always get the email that says RevOps needs to adjust quotas in one of the regions. Why? Well, it's just an agreement we made, and we've got to do it for whatever reason. And now, suddenly, you have inconsistencies in how those quotas were set across the regions. Therefore, benchmarking the teams is very difficult," said Vernon. 

"Halfway through the year, you've probably had about 30 changes to quotas for whatever reasons. So, trying to use quota attainment to measure sales performance is, at a high level, fine. It could give you some good indications of where you're heading. But when you start to look at that performance in a more granular view, that gets difficult." 

We mentioned earlier that Vernon and Werner challenged us to rethink using quota attainment as a valid measurement. Here's where the logic flaw really hit home.

"Why is it a mistake? Only 48.5% of salespeople are hitting their quotas. This is scary because it's been dropping. I know the last couple of years have been difficult, but this has been going down over time. It was about 58% about six or seven years ago. So, if we know that, how can we use quotas to measure performance? Quota methodologies, as I've spoken about, are variable from organization to organization. Even within organizations, the methodologies can differ depending on how those businesses are set up. If you've got 30 changes by the middle of the year in your quotas, it's just inconsistent and unstable," said Vernon.

How Should We Calculate Sales Productivity?

We're convinced! Quota attainment no longer makes sense as a benchmark. But we need a viable replacement.

Werner gave us a great alternative. "Using that great research from Forrester or SeriusDecisions, they recommend using how much revenue a salesperson produces per unit of time. This creates a stable foundational metric for us to measure performance against. Now we've got a baseline that we can use." 

"When you look at that across a sales team, then you've got an average productivity generated across that team. When you look at it across a Geo or product line, you now get an average of the productivity per person. There are stable foundational metrics. The more salespeople you have – it's an average – so it gets harder to move," said Werner.

Of course, productivity can change. RevOps teams must watch productivity trends over time. The goal is for productivity to be flat or increase. If it begins dropping, your return on investment calculations will also decrease.

To calculate sales productivity, the formula is as follows:

(Any Revenue in a given period) divided by (the number of salespeople able to sell in that same period)

Simple, right?

To understand how many sales representatives can sell, you'll need to know how many sales representatives out of the total allotted headcount can sell, how much time they can spend selling, and exactly how long it takes for new sales representatives to begin selling. Attrition must also be factored in.

Before you throw in the towel, here are some fantastic reasons this is a metric worth calculating from Werner's slides:

  • It creates a stable, foundational performance baseline from actual operating data
  • Can be applied across teams, territories, product lines, individuals, and other business dimensions
  • Can be trended to determine if operational and enablement programs are working
  • Identifies opportunities and risks in real-time

Are there shortcuts? An easier formula?

Yes. But it will be less reliable.

"You could look at Closed Won business over a quarter – or look at it over half the year or even over the year. And then you're looking at how many salespeople you had during that period. So you're taking your closed-won business divided by how many salespeople you have, and you're getting a sales productivity number," said Werner.

For example, if we sold $850,000 and there were 6 full-time sales representatives in Q2 of 2023, Our productivity per rep per quarter is $141,667.

Let's compare that to a more granular view. Let's say some people were on leave part of the time, and the others took some vacation. That takes us down to 5.2 sales representatives. If we divide the same number of sales by our new number of reps, our productivity per rep number goes up to $163,461. That's a significant difference!

Trending the data over time will show how a new initiative or pricing program impacts productivity. You can also see how new product lines, geographic expansions, or use cases impact the bottom line.

Calculating Sales Efficiency

Sales efficiency is a calculation that helps us understand how much revenue the sales team can generate compared to the amount spent supporting sales. In this context, we're strictly evaluating our investment in the sales team itself. We're not including marketing costs in this calculation (we do that when calculating Customer Acquisition Cost).

The formula for this is:

(Real-time revenue achieved over a period of time) divided by (selling costs over the same period of time)

When investors were comfortable with a "growth at all costs" mentality, sales efficiency wasn't the primary metric. Now, organizations must prioritize efficiency.

"We need to be thinking about doing that efficiently because, ultimately, if you improve operating margin, you start improving company valuation," said Werner.

In prior years, it was acceptable to operate at 2X return. Now we're hearing 3X to 5X is the new goal. Understanding sales efficiency can help leaders understand when to hire more or less – and how much to prioritize enablement activities.

Matt Volm, founder of the RevOps Co-Op summarized the impact of increasing sales efficiency nicely. "If you can improve ramp time for a new salesperson from 90 to 85 days, it doesn't seem like much gain. It's only five days. But let's say you hire just five people over a year. That's a gain of 25 days. That's a whole additional month of selling that you could have accomplished with just the difference between 85 and 90 days. It adds up."

For more real-world examples and details about calculating Sales Efficiency, Productivity, and capacity - check out the full recording above. For more on how to use Lative to automate sales capacity planning, check out their Demo that Doesn't Suck by clicking here.

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