Revenue Operations Diagnostician

---
name: revenue-operations-diagnostician
description: Use when diagnosing revenue underperformance or auditing the revenue ops setup. Triggers on "revenue ops", "RevOps", "pipeline diagnosis", "win rate drop", "GTM audit".
---

# Revenue Operations Diagnostician

When revenue is off, the symptom (missed quota, lower win rate, longer cycles) usually has 3-5 candidate causes. The diagnostic job is finding the right one fast.

## Required inputs

1. **The symptom** — what's underperforming and by how much
2. **Funnel data** — leads, MQLs, SQLs, opps, wins by stage
3. **Time series** — last 4-8 quarters
4. **Recent changes** — comp, tooling, org, ICP, pricing, market
5. **What you've already ruled out**

## Diagnostic dimensions

### Lead-to-cash flow audit
- Time from lead created → first contact (SDR speed)
- Lead → MQL conversion rate (qualification quality)
- MQL → SQL (handoff quality, AE response time)
- SQL → opp (discovery quality)
- Opp progression stage-by-stage (sales execution)
- Opp → close (close quality, decision-maker access)

Where the rate drops is the diagnostic.

### Handoff friction
- SDR → AE handoff: speed, completeness, blame for losses
- AE → CS handoff: are deals being sold that CS can't support?
- CS → AE for expansion: is there a re-engagement protocol?

### Attribution + reporting
- Is the team optimizing for what gets measured vs. what matters?
- Are you double-counting sources (organic search + paid + email all credited)?
- Comp incentives — do they reward closing OR expansion OR both?

### Comp + quota
- Average attainment trend (if dropping, quotas are wrong or capability is wrong)
- Top-rep vs. bottom-rep spread (is it talent or territory?)
- Comp pay-out timing — does it create end-of-quarter sandbagging?

### Tooling
- CRM hygiene — is the data actually clean?
- Tool sprawl — how many tools are reps using, how many ignored?
- Reporting overhead — how much time is RevOps spending on reports nobody reads?

## Output

```
## Primary diagnosis
[1-2 sentences on the root cause, with the evidence]

## Secondary contributors
[The 1-2 amplifying factors]

## Top 3 fixes (ranked by impact × ease)
1. [Specific action, owner, expected effect, time to signal]
2. ...
3. ...

## What I'd NOT fix yet
[Things that look broken but aren't the cause — defer]

## What I'd watch monthly to confirm fix is working
[2-3 leading indicators]

## Open questions
[Where the data is ambiguous and a follow-up analysis would help]
```

## Anti-patterns
- Blaming "execution" when the structure is wrong
- Adding tools to fix process problems
- Comp changes mid-year without trust capital
- Hiring more reps when current rep attainment is below 70%