Why does the company number never match the average of the rep numbers?
Because averaging a set of ratios gives every rep the same weight no matter how many deals sit behind their number. This is the single most common defect in sales reporting, and it survives for years because each individual number looks correct.Take a four-person team. Rep A closed 40 opportunities and won 10, a 25% win rate. Reps B, C, and D each closed 4 and won 2, a 50% win rate. The average of the four rep win rates is 43.75%. The actual team win rate is 16 wins out of 52 closed, or 30.8%. The gap is 13 points, and the 43.75% figure is describing a team that does not exist.
The fix takes one rule. Never aggregate a ratio. Aggregate the numerator and the denominator separately, then divide at the level you are reporting on.
What is the correct rollup method for each metric?
Recompute from raw counts for ratios, sum for absolutes, and recalculate medians from the deal list. Different metric shapes aggregate differently, and treating them alike is where reconciliation dies.| Metric | Rollup method | Common mistake |
|---|---|---|
| Win rate | Sum wins, sum closed, then divide | Averaging rep win rates |
| Average deal size | Sum won ACV, divide by win count | Averaging rep averages |
| Sales cycle length | Recompute median from all closed-won deals | Averaging team medians |
| Pipeline coverage | Sum open pipeline, divide by summed quota | Averaging rep coverage ratios |
| Quota attainment | Sum bookings, divide by summed quota | Averaging attainment percentages |
| Stage conversion | Sum entries and exits per stage | Chaining rep-level rates |
| Forecast accuracy | Compare summed forecast to summed actual | Averaging rep accuracy scores |
Should you weight by deal count or by dollars?
Report both, because they answer different questions and their divergence is the finding. Count-weighted metrics describe how often you win. Dollar-weighted metrics describe whether the wins pay the bill.A team can hold a 30% count-based win rate and a 19% dollar-weighted win rate at the same time. That means small deals convert and large deals do not, which points at enterprise motion, pricing, or approval friction rather than at rep skill.
The same split applies to pipeline. A pipeline can carry an average deal size of $80,000 while closed-won deals average $40,000. Count-weighted coverage looks fine in that scenario and dollar-weighted expectations do not. That is one reason the 3x pipeline coverage rule breaks down as a standalone read on the quarter.
How do you handle reps with too few deals to report?
Suppress the ratio, publish the counts, and state the threshold in the report itself. A rep with three closed deals has a win rate of 0%, 33%, 67%, or 100%. No other values are possible. Printing one of those four numbers next to a rep who closed 40 deals invites a comparison the data cannot support.Set a minimum sample per metric, publish it, and hold to it. The floor matters less than the fact that it is written down and applied consistently. Below the floor, show wins and closed count as raw numbers. Managers can read "2 of 5" without any help, and it carries the uncertainty in a way that "40%" does not.
The suppression rule also protects the team number. When a rep-level ratio is unstable, any rollup that averages it inherits that instability and passes it to the board deck.
Why do rollups rewrite history after a reorg?
Because most CRM reports attribute closed deals to the rep's current team rather than the team that owned the deal when it closed. Move one rep between segments and last year's team numbers change overnight.Snapshot the attribution at close. Write owner, team, segment, and territory onto the opportunity record when it reaches closed-won or closed-lost, and report against those stored fields rather than the live hierarchy. Without the snapshot, no historical comparison is stable, and every territory change quietly invalidates the trend lines the forecast is built on.
The same rule applies to quota. Store the quota that was in force during the period, not the rep's current quota. Ramping reps make this obvious, since attainment computed against a full-year quota during a ramp period is wrong by definition.
How do you make the levels reconcile every week?
Build one deal-level table and derive every level of the report from it. Rollups break when each level has its own source. The team dashboard pulls from one report, the executive summary pulls from another, and the two disagree by a few points that nobody can explain.One table, one row per opportunity, with the fields the rollup needs frozen at close. Every level of reporting is then a group-by over the same rows, which means the numbers reconcile by construction rather than by reconciliation meetings.
Then run one check before publishing. Sum the lowest level and compare it to the top-level figure. If they differ, the report has an averaging bug or an attribution gap, and both are fixable in minutes when you catch them at that moment. Anchoring definitions the same way across the org is the other half of this problem, and sales velocity is a useful test case because it multiplies four metrics that each aggregate differently.
Frequently Asked Questions
Why does team win rate differ from the average of rep win rates?
Because averaging rep win rates gives every rep equal weight regardless of how many deals they closed. A rep with 3 closed deals counts as much as a rep with 40. Recompute from raw counts at each level instead of averaging the level below.
Should sales metrics be weighted by deal count or by dollars?
Both, reported side by side. Count-weighted metrics tell you how often the team wins. Dollar-weighted metrics tell you whether the wins are the ones that fund the number. They diverge when large deals convert differently from small ones.
What is the right way to roll up sales cycle length?
Use the median at every level and recompute it from the underlying deal list. Medians do not aggregate, so a company median cannot be derived from team medians. Store the deal-level durations and recalculate up the hierarchy.
How do you handle reps with too few deals to report on?
Suppress the ratio and show the raw counts instead. Set a minimum sample per metric, publish that rule, and display counts below the threshold rather than a percentage that one deal can rewrite.
Why do rollups break when a rep changes teams?
Because most CRM reports attribute deals to the rep's current team rather than the team they belonged to when the deal closed. Snapshot team assignment at close and report against the snapshot, or historical team numbers rewrite themselves every reorg.
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