How to analyze employee performance - Sales Analytics

Introduction

We have heard a lot about Pareto's 80/20 rule states that 80% of the outcome is attributed to 20% of a specific element in business. As an example, in sales, they say 80% of sales come from 20% of customers. Here is a different yet equally powerful rule that may interest you. It's the 20/60/20 rule of leadership. This rule splits the population into 3 groups with varied behavior. If aligned with employees' performance, this is how it would look like.

Top 20%

Strong performers in your organization. You can depend on them, they are like a smooth functioning unit that understands their goals, work hard, and have the required skills to deliver the top results. You need to leave them alone as they already know what needs to be delivered. Tinkering with them through over-communication or needless coaching might actually create an imbalance.

Middle 60%

Average performers who need some level of hand-holding. Be clear that their average performance may not necessarily be attributed to a lack of potential or competencies. There can be other elements that we need to uncover and work upon. These are your dark horses who can actually turn the tide around for you with the right coaching and guidance.

Bottom 20%

Underperformers who are your weakest links. Their reason to being in this group can be attributed to multiple factors, lack of potential, skill sets, or improper role fitment. I believe these are pretty much like the top 20%. I would not spend too much time on them unless there's a clear understanding of the areas to focus upon. Any energy spent without this clarity would end up in frustration.

20/60/20 Analysis

To understand the health of a sales organization, we analyzed three core metrics through the 20/60/20 lens: Attrition, Performance Variation, and Earnings Contribution. Let’s start with attrition across the hierarchy for the year.

Among Sales Directors:
-25% of top performers exited the organization
-21% of mid-tier performers left
-38% of bottom performers churned

At first glance, losing bottom performers may seem like a natural reset. Fresh hiring. New energy. Better alignment. But pause. A 25% exit rate among top performers is not a routine fluctuation, it’s a signal. Top performers are typically the most rewarded, most recognized, and most productive. If one in four is leaving, the question isn’t about individual dissatisfaction. It’s structural.

-Is the incentive design failing to retain excellence?
-Is there misalignment between effort and earnings?
-Are leadership, product-market fit, or territory design causing burnout?

What does this mean for next year’s revenue predictability?

When both the top and bottom layers show significant churn, the issue may not be people-specific. It may indicate something deeper, which is compensation architecture, role clarity, enablement, or systemic friction in the sales process. Before coaching individuals, the organization may need to conduct an internal review.

Performance Mobility: Who’s Moving, and Why?

Now, let’s examine performance movement across two time periods.

A) Bottom Performers

Out of 48 underperforming reps:

-4 moved into the top category
-28 showed measurable improvement
-16 remained stagnant

This tells an important story. First, improvement is possible and visible. Something worked. Whether it was incentive restructuring, coaching, territory adjustments, or process simplification, there was positive momentum. That initiative deserves deeper analysis and potential scaling.

But 16 remaining in the same category raises a harder question:
Is this a capability issue, a hiring mismatch, or a systemic barrier that no incentive tweak can fix?
Data doesn’t just validate optimism, it forces tough calls.

B) Top Performers

Out of 48 top reps:
-6 slipped to the bottom tier
-29 showed varying degrees of deterioration

This is more concerning than stagnation at the bottom tier.

When high performers decline at scale, it suggests one of three dynamics:
-Incentive changes may have unintentionally diluted motivation at the top.
-Emerging talent from the lower tier is outperforming incumbents.
-Market, territory, or product shifts have altered competitive advantage.

The critical question becomes: Did organizational interventions disproportionately lift the bottom at the expense of the top? Or is this healthy competitive reshuffling? Performance distribution is not static. It is fluid and often incentive-sensitive.

The Bigger Insight

The 20/60/20 model is not about labeling people.

a) It is about diagnosing system behavior.
b) Attrition patterns reveal structural stress.
c) Mobility patterns reveal incentive effectiveness.
d) Stagnation reveals talent risk.
e) Downward drift reveals motivational gaps.

When analyzed together, they tell you whether your sales engine is self-correcting…or slowly destabilizing.
And that insight matters far more than any graph ever could.

What the Sales Data Reveals About Attainment and Volume

To understand what’s really happening, we examined two core indicators over time: % attainment and sales volume, segmented across the entire salesforce. Across performance categories, attainment levels remained broadly stable with minor fluctuations. On the surface, that suggests consistency. No dramatic swings. No visible performance shock.

But when we shift focus to total sales volume, a different picture emerges.
Overall revenue has increased quarter after quarter.
At first glance, that sounds like success. The latest IC plan seems to be pushing the organization forward. Activity is up. Output is growing. The system appears to be working.

But growth alone doesn’t tell the full story.

When we break the numbers down by performance tiers, a pattern becomes clear:
Reps are moving between buckets by replacing each other in the top, middle, and bottom segments, and yet the contribution from top and mid-tier performers has not meaningfully expanded. Meanwhile, bottom-tier contribution has remained relatively constant.

In other words, performance reshuffling is happening, but performance expansion is not. That distinction matters.

If the top 20% are not increasing their revenue share, and mid-tier performers are not scaling meaningfully, then incremental growth may be driven more by structural factors (market expansion, pricing shifts, broader demand) than by true incentive-led performance acceleration.

This raises an important question:

Is the current IC plan lifting the floor but not raising the ceiling?
If bottom performers are stabilizing or improving slightly while top performers are not being pushed to stretch further, the plan may be optimized for containment rather than excellence.

And that has consequences.

A compensation structure overly aligned toward protecting the lower tier can unintentionally dilute motivation at the top. High performers thrive on differentiated upside. If that upside flattens, so does discretionary effort.

The result?

1) Stable attainment
2) Moderate overall growth.
3) No breakout performance from the top tier

Which suggests that the most recent IC plan may be improving baseline performance, but not maximizing peak performance. In competitive markets, expanding peak performance matters more than stabilizing the baseline.

Key Takeaways

• There is attrition across performance buckets within a role group; Directors and Sales Executive groups are a couple of examples. There is a need to address issues with people, products, or processes before focusing on individuals in this role.
• Area Sales Managers & Regional Sales Managers show a different picture, though. Maximum attrition in these groups is at the bottom. There is a need to analyze this attrition trend vis-a-vis other groups and understand what's keeping the top performers engaged while other role groups are struggling to do so.
• Across the board, top-performing and bottom-performing reps have swapped roles, resulting in marginal sales growth. There is a need to study the recent IC plan and identify if payout curves need to be redone to give an equal opportunity across the board.

Sales analytics is an emerging field that can help you make data-driven decisions and significantly improve overall efficiency.