On Measuring Sales Performance

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It’s becoming increasingly complicated to measure sales performance–particularly in complex B2B sales. We are used to setting quotas and measuring our progress against those quotas.

But our measurement systems are getting increasingly complex.

First, as we look at leveraging teams to sell complex deals, I hear increasing concerns with, “Who do we credit?” Particularly, when many people contribute and we need to credit different people.

Second, are we measuring the right things? Is revenue/orders the only thing we should be measuring? Are there other goals, equally important to achieving our overall organizational goals, that we should be measuring?

I think we make the issue of measuring sales performance more complicated than it need be, because we confuse it with “compensating sales performance.” These are interrelated, but separate issues, and we have to look at them independently.

When we separate measuring sales performance from compensating sales performance, we are able to start clarifying things. We can start to develop more meaningful metrics.

Who gets credit? We don’t have problems with giving team or duplicate credit for results. If multiple people contribute to a sales effort, we can give credit to the whole team. We don’t have to think about how much credit to apportion to each person, particularly when we know that to achieve the goal, we need the participation of each person.

When we eliminate the issue of who gets credit, we eliminate all the time wasted in negotiating this, apportioning credits, or “protecting our turf,” focusing instead on doing the work.

What do we measure? Too often, we focus only on orders and revenue. Those are important, after all orders and revenue are what keep our companies in business. But is that all we should be measuring? And they are trailing metrics, so does measuring orders and revenue really help us in managing the business and achieving our goals?

Output measures: There are a number of output measures that may be important to achieving our corporate goals. Revenue, orders are well known. Mix, both product/service and market may be important in assuring balanced performance in executing the company strategy. Retention, customer satisfaction, customer/account growth may also be important measures. New customer acquisition, new market penetration can be important measure, if they are important to our company strategies. Growth, margin, average discount are other interesting output measures. Win/loss rates are interesting output measures.

Process measures: We spend too little time thinking of the appropriate process measures. These are important because they help us understand whether we are likely to achieve our output goals. They help us understand if we are doing the right things with the right people at the right time and in the right way. Pipeline metrics are great examples of process measures. If we have healthy pipelines, we can expect that we will be highly likely to achieve our output goals.

One of the important things we miss about process measures is we must continually look at refining and improving our processes, as a result, our process measures will constantly be changing as we improve our processes. For example, if we look at to improve our performance in executing deals, our pipeline dynamics will change and our pipeline metrics will change. Likewise, improving our win rates (a process metric) will change the dynamics of our pipelines.

Activity measures: It’s become very fashionable to measure activity–partly because it’s so easy to do. We are inundated with activity measures—dials, emails, text messages, number of customer meetings a week, number of proposals a month, and so forth. Volume of leads, MQLs, SQLs, SALs, and so forth are other activity measures.

There are problems with many of our activity measures. First, most are easily gamed. For example, there is no reason that a sales person shouldn’t be able to achieve any goal on number of dials/calls—making this goal doesn’t mean we have had impactful conversations with customers/prospects.

We get activity metrics wrong in several senses. First they become ends in themselves. We lose track of why we have the activity metrics, instead focusing on those metrics.

Second we try to tie the activity metrics to the output metrics, when they are more closely related to the process metrics. Stated differently, we ought to be able to understand the cause/effect relationships in our activity metrics, the only way to do this is to tie them to process metrics.

Third (related to the prior to points), since activity metrics become ends in themselves, we never consider, “How do we get better, how do we improve?” As a result, when we change our output goals, we tend just to do the math, not understand the most effective and efficient processes to achieve the output goals.

Sales performance, effectiveness, efficiency is not an unchanging math equation. The data, should cause us to look at our underlying processes, constantly challenging ourselves with the questions, “How do we get better? How do we maximize our impact in everything we do?”

Goals vs. Metrics. We confuse goals and metrics. They are related, but aren’t quite interchangeable. Metrics are the things we measure—duggh. Whether it’s revenue, pipeline health, prospecting meetings. The goals are the targets we set for key metrics. For example, “how much revenue, volume/velocity goals for pipelines, number of prospecting meetings.

How many metrics? As with activity metrics, too often we measure too many things, as a result they become meaningless and confusing to the people on whom we inflict these metrics. Measuring only output metrics, clearly doesn’t enable us to keep “on target.” So we have to measure more. A few process metrics, are really helpful leading indicators.

When we have process understanding, we realize the interrelationship between the activity metrics and the processes. As a result, we have to measure less. We can focus on a few key process or related activity metrics, not the endless list of activity metrics.

So what’s the right number? It depends, but it should only be a handful. With the right metrics, we have a starting point to understanding performance and drilling down into what’s happening and why.

On Compensation: We base compensation on a number of issues. Attainment of certain goals (performance and others) is one element of compensation. Another element of compensation is the value of a role to the organization. Another element is affordability. As we start separating what we measure and how we measure for each role in the organization, it becomes much easier to develop fair compensation plans for each role. We overcomplicate the process by mixing both, simultaneously.

On Performance and Compensation: We mistakenly tie our ability to drive performance solely to compensation. We somehow think, “sales people are coin operated,” basing everything we do to achieve our goals on the compensation plan.

In doing this, we miss the opportunity to leverage all the levers that drive performance in an organization. People are driven to accomplish things and achieve for a whole number of reasons, not just based on compensation.

We have to understand each of those performance levers, we need to understand what drives human behaviors and what behaviors we expect of high performers in our organization.

Money is important to everyone in the organization, not just sales. Everyone wants fair compensation for what they do, but that isn’t the only thing that drives their performance.

And metrics are how we assess performance.

We make it more complicated and confusing than it need be–as a result, we seldom optimize performance.

Republished with author's permission from original post.

Dave Brock
Dave has spent his career developing high performance organizations. He worked in sales, marketing, and executive management capacities with IBM, Tektronix and Keithley Instruments. His consulting clients include companies in the semiconductor, aerospace, electronics, consumer products, computer, telecommunications, retailing, internet, software, professional and financial services industries.

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