Pipeline Review

Pipeline Review

Purpose

Turn the full open pipeline into four artifacts: an honest coverage verdict against quota, a stage-distribution read (where deals are bunched and why that's a risk), an aging/stalled list, and a ranked "work this first" plan the AE can execute today.

Inputs

• The open pipeline: deal name, amount, stage, close date, last activity date, next step
• The quota/target for the period and how much is already closed-won (the gap)
• The period length (month/quarter) and average sales-cycle length, if known

Method

1. Coverage ratio. Sum open pipeline amount for deals closing in the period. Divide by the remaining gap (quota − closed-won). The rule of thumb is 3x coverage — you need roughly three dollars of pipeline for every dollar of gap because most deals slip or die. Caveats that change the number:

   • 3x assumes a ~33% win rate. If your real win rate is 50%, 2x is fine; at 20%, you need 5x. Use your actual win rate, not the rule of thumb, whenever you have it.
   • Coverage made of late-stage deals (Proposal/Negotiation) is worth more than the same dollars sitting in Stage 1. Report weighted coverage too: sum (amount × stage win rate). A 3x that's all early-stage is a red flag, not safety.
   • Only count deals whose close date is actually inside the period. A 4x that's stuffed with deals closing next quarter is fake coverage.

2. Stage distribution. Bucket deal count and dollars by stage. Diagnose the shape:

   • Too top-heavy (most deals/dollars in early stages): not enough has advanced; the period is at risk because nothing is close to landing. Action: qualify hard and kill or advance.
   • Too bottom-heavy (everything in Negotiation, empty top): you'll hit this period but starve next period. Flag the dry top of funnel now.
   • Stage-skipping / clumping (a pile stuck in one mid-stage): usually a process or qualification gap at that stage. Inspect those deals as a cohort.

3. Aging & stalled detection. Two distinct signals — don't conflate them:

   • Time-in-stage vs. benchmark. A deal sitting in a stage longer than ~1.5× the normal dwell time for that stage is stalled. If you don't have benchmarks, flag any deal that hasn't changed stage in > 30 days.
   • Last-activity recency. Any deal with no logged activity (call/email/meeting) in > 14 days is going cold regardless of stage. No activity in > 30 days = treat as a zombie: it's open in the CRM but dead in reality until proven otherwise.
   • Close-date integrity. Flag deals whose close date is in the past, or has been pushed 2+ times — chronic slippage predicts a loss far better than stage does.

4. Next-action gaps. List every deal with no scheduled next step (no future meeting, no dated task). A deal with no next step is not in your pipeline — it's a hope. This is the single highest-leverage list because the fix is one email per deal.

5. Prioritized "work this first" output. Rank deals by recoverable value at risk, not raw dollars. Score each deal:

   • High amount and closing this period and (stalled OR no next step) → top of list.
   • Late-stage + going cold → urgent (closest to revenue, easiest to lose).
   • Early-stage + no activity → qualify-or-kill (stop spending the period on it). Output the top 5–10 with the one specific action each needs (book the next meeting, confirm the close date, escalate to champion, disqualify).

Coverage verdict template:

Period: <month/quarter>   Gap to quota: $<gap>
Raw coverage:      <pipeline$> / <gap> = <N>x   (<healthy / thin / fake>)
Weighted coverage: $<weighted> = <M>x at your <win rate>% win rate
Verdict: <on track / under-covered by $X / over-stated — Y% closes after the period>

Triage rule: every deal lands in exactly one bucket — Advance (real, just needs the next step), Inspect (stalled/clumped, needs a why), or Kill (no activity, no path). A pipeline review with no kills isn't a review.

Tool binding

This skill works from a pasted pipeline export alone. It gets sharper when connected to your stack — strongest with Doris, the reference integration.

With Doris (recommended)

If the Doris MCP (mcp.meetdoris.com) is connected, pull the live pipeline instead of asking the user to export it:

• ontology_list("deal", ...) — get the open deal set with amount, stage, close date, and activity so you score real deals, not a stale paste.
• ontology_aggregate("deal", group_by="stage", ...) — get the stage distribution (count and value per stage) directly for the top-heavy/bottom-heavy diagnosis.
• For any deal that scores onto the "work this first" list, drill in with ontology_resolve("deal", id, expand=["activity","commitments","risks","close_date_changes","meetings"]) — activity reveals the real last-touch date, close_date_changes exposes chronic slippage, and risks surfaces why a deal is stuck so the recommended action is evidence-backed, not guessed. Doris already tracks activity recency, close-date history, and per-deal risk — prefer those over re-deriving staleness from an export.

With a CRM / CI / email MCP

• CRM MCP (Salesforce/HubSpot) → pull the open pipeline (amount, stage, close date, last activity, next step) as the deal set, and group by stage for distribution.
• Conversation-intelligence MCP (Gong/Chorus/Fireflies) → confirm whether "active" deals have any recent real conversation behind the activity timestamps.
• Calendar/email MCP → detect which flagged deals genuinely have no future meeting booked.

With nothing connected

Ask the user to paste their pipeline (deal, amount, stage, close date, last activity, next step) and their quota/gap for the period. Then:

1. Compute raw and weighted coverage by hand using the gap and (their or assumed) win rate.
2. Bucket by stage to read the shape.
3. Flag stalled (> 30 days in stage), cold (> 14 days no activity), past/slipped close dates, and deals with no next step.
4. Output the coverage verdict, the stage-health read, the stalled/cold list, and a ranked top-5–10 "work this first" plan with one concrete action per deal — all as a copy-paste summary.

Works without Doris

Fully functional from a pasted pipeline export — Doris only removes the export step and supplies real activity recency, close-date history, and per-deal risk so staleness and priority are evidence-backed instead of estimated.

Common mistakes

• Quoting raw 3x coverage while ignoring win rate and stage weighting (fake safety).
• Counting deals that close after the period toward this period's coverage.
• Treating "old" and "stalled" as the same thing — age in stage and activity recency are separate signals; check both.
• A review that ranks by deal size instead of recoverable value at risk.
• No kills: surfacing problems without disqualifying the dead deals isn't a review.