Robert Wahbe is the co-founder and CEO of High point, sales enablement platform. More posts from this contributor Reimagine inside selling to increase B2B customer acquisition
In today’s data-abundant era, leaders have many metrics to choose from to measure progress against their strategic initiatives. However, even with all this data, too many leaders are focusing on aggregate data, ignoring the most important metrics.
When you synthesize data at a high level, you run the risk of creating a metric I call “watermelon:” numbers that are green at first glance, but red beneath the surface. Watermelon hides an underlying execution problem that runs throughout your sales team – and if left unchecked for too long, can damage your business from the inside out.
Watermelon hides underlying execution problems – and if left too long, they can damage your business from the inside out.
Leaders who rely on averages and aggregates are doing their business a disservice by failing to dig deep enough to understand the status of their business goals and areas for improvement.
For example, in a recent earnings call, Cloudflare revealed that they had “identified over 100 people in our sales team who consistently fell short of expectations. Simply put, a significant percentage of our sales force repeatedly underperforms against measurable performance targets and critical KPIs.”
How did 100 people miss so long? Leaders don’t dig deep enough into the data. It’s important to identify the root cause of these seller mistakes and fix them from the ground up.
This is what it means to find a watermelon, how to identify it, and a framework that provides better insights and actions to increase your bottom line.
Finding watermelons using person-centered analysis
When looking at important performance metrics, many leaders take an overly limited view of their data. Activity and yield metrics are typically sliced and diced by dimensions such as industry, segment, geography, product line, customer group, and buying persona, so leaders can answer questions like, “What is the win rate for mid-market manufactures in Europe?” This is fine, but nearly every company is missing one of its most important dimensions: people.
Failing to see your metrics by people clouds inconsistent performance across teams, which kills overall productivity. Let’s say your average win rate is 34% – what seems like a very healthy metric could be a whole watermelon. Frankly, for most companies what is likely to happen is the win rate of the top performing quartile is high while most of your team’s win rate is low.
You won’t discover this reality unless you look at the people dimension, examining the distribution of everyone’s performance against that metric. It might look something like:
Looking at distributions can be a little tricky, so here’s a way to simplify the analysis. You use participation rates as a proxy for distribution, for each cohort you want.
Based on the previous example, you could look at your win rate for a mid-market manufacturer in Europe and then analyze your rep’s performance on that transaction to determine the Participation Rate against the win rate metric.