Every SalesOps team knows the average attainment number. Almost none know the shape. A team averaging 98% attainment can be healthy (bell curve clustered around 100%), or it can be a disaster (half the team at 50%, half at 150%, averaging out to look fine). The shape tells you whether your plan is working; the average tells you nothing.
This tool takes a list of attainment percentages, builds the histogram, calculates the statistical shape (skewness, spread, clustering), and diagnoses it against four common patterns: healthy bell curve, flat/undifferentiated, bimodal (two-class), or skewed (quotas too high or too low). Each diagnosis comes with specific plan-design recommendations.
The healthy distribution — and why
Benchmark: the 60/15/25 shape
In a well-designed plan with correctly-set quotas, you should see roughly: 60–70% of reps between 80–120% attainment (the bell's sweet spot), 10–15% above 120% (top performers earning accelerators), and 15–25% below 80% (underperformers who need coaching or off-ramping). The median should land near 100%.
Why this shape and not another
A plan that rewards effort + skill should produce a distribution that differentiates reps — some exceed, most hit, a minority miss. Too narrow a distribution (everyone at 95-105%) suggests quotas are too soft and the plan doesn't create stretch. Too wide (reps ranging 30-200%) suggests either wildly unbalanced territories or a plan where luck dominates skill.
The four anti-patterns
Flat: attainment spread evenly across the range. Plan doesn't differentiate. Bimodal: two clusters (e.g., one around 60%, one around 130%). Two-class system — your top quartile is on a different job than your bottom. Skewed low: most reps below 80%. Quotas too aggressive. Skewed high: most reps above 110%. Quotas too soft — you're paying accelerators on everything.
A team averaging 100% attainment with a healthy bell curve is a high-trust, high-performance engine. A team averaging 100% with bimodal distribution is a flight risk — your top performers are bored (flat ceiling), your bottom performers are demoralized (no path up), and you'll lose the middle tier to competitors with flatter teams. Same average. Opposite futures. The shape is the signal.
Attainment Distribution Analyzer
Paste one attainment % per line or comma-separated. We do the rest.
ℹ️ How this tool works +
The question it answers: What does my team's attainment distribution actually look like, how does it compare to the healthy benchmark, and what's the plan-design implication?
What to enter:
- Attainment percentages for each rep — one number per line or comma-separated. No need for the rep's name. Enter as percentages (e.g.,
95for 95% attainment). - Minimum 5 reps for statistically meaningful output. More than 8 is ideal.
What the tool computes:
- Histogram across 7 buckets: <60%, 60-79%, 80-99%, 100-119%, 120-139%, 140-159%, ≥160%.
- Key stats: mean, median, spread (stdev), % at or above 100%, % in 80-120% sweet spot.
- Shape diagnosis: Healthy / Flat / Bimodal / Skewed Low / Skewed High.
What you'll get back:
- The diagnosed shape with an explanation of what it indicates about your plan.
- A visual histogram with the sweet-spot band highlighted green.
- Shape-specific recommendations — what to adjust in quota-setting, plan structure, or territory design.
Sample data pre-loaded (8 reps, realistic healthy-bell distribution). Replace with your team's numbers and re-analyze.
Benchmarks, ranges, and default values in this tool reflect Falcon's practitioner experience across consulting engagements. They are directional starting points, not substitutes for market survey data. For binding compensation decisions, validate key figures against Radford, Mercer, Carta, or WorldatWork survey data for your specific geography, industry, and company stage.
How to act on each diagnosis
Healthy bell curve
Your plan is working. Protect it — don't tinker with quotas or rates without cause. Focus management attention on the 15-25% below 80% (coaching or off-ramping) and the 10-15% above 120% (retention and stretch goals).
Flat / undifferentiated
Your plan isn't creating performance differentiation. Either quotas are set based on equal potential that doesn't exist, or the plan doesn't reward over-attainment enough for top performers to stretch. Audit accelerator depth (the ratio of above-quota commission to at-quota commission) — flat distribution usually traces to weak accelerators.
Bimodal (two-class team)
The most dangerous shape. You have a top cluster and a bottom cluster with little in the middle. This indicates either radically uneven territories (top cluster is on the easy ones) or a learning-curve gap (tenured reps vs new hires with no middle ramp). Use the Territory Balance Checker to rule out imbalance first.
Skewed low (quotas too high)
Most reps below 80% attainment. Either quotas were set too aggressively or the market conditions the plan was built for changed. Action: mid-year quota adjustment (use the Quota Change Impact Modeler) or revised plan design for next year. If you don't adjust, expect attrition.
Skewed high (quotas too low)
Most reps above 110%, median near 120%. Quotas were set too soft — you're paying accelerators on routine performance. The comp cost is higher than necessary and the plan has no real stretch. Raise quotas for next year; communicate clearly that this is a recalibration, not a punishment.
A narrow distribution clustered tightly around 100% looks healthy on a summary slide but is actually a flat distribution in disguise. It indicates reps calibrating to hit exactly their number and stopping — the plan isn't creating genuine stretch. If your distribution is too tight, widen the accelerator range or add strategic-deal SPIFFs that reward over-attainment.
Not sure what your shape means?
We help SalesOps teams diagnose distribution shape and identify the one plan-design change that moves the team toward healthy. Book a 20-minute review.
Book a 20-minute consultation →FAQ
Minimum 5, ideally 8+. Below 5, a single outlier distorts the shape. For teams under 10, interpret the shape directionally; wait until you have at least 2 quarters of data for confident conclusions.
Exclude reps in their ramp period (typically <6 months in role). Including them creates an artificial low-tail that's a ramp artifact, not a plan signal. If you want to see ramp dynamics, run separately.
Best applied to one role type at a time (e.g., just Mid-Market AEs, not AEs + SEs mixed). Mixed role analysis hides the fact that overlay roles typically have tighter distributions than primary quota carriers.
Quarterly volatility is normal — look at year-end distribution for the plan-design signal. Within-year, compare this quarter's shape to last year's same quarter to control for seasonality. Shape drift across years is the real signal.