--- name: pipeline-strategy description: "Use when designing or auditing a sales pipeline — stage exit criteria, per-cell conversion, coverage reasoning, leak detection. Triggers on 'tighten our pipeline', 'where is the leak'." status: active tier: senior source: package domain: product context_spine: [product, customer-segment, channel-stage] recommended_for_user_types: [gtm] workspaces: - gtm packs: - gtm-sales lifecycle: active trust: level: professional confidence: high human_review_required: false install: default: true removable: true --- # pipeline-strategy ## When to use - Pipeline stages are named but have no exit criteria — reps move deals on gut and forecasts ride on opinion, not evidence. - Coverage is being computed from a flat multiple (*"3x quota"*) without per-stage conversion rates, so the multiple flatters or punishes the team at random. - A board ask names *"why did pipeline coverage look fine and the quarter still missed?"* — a leak is hiding inside a healthy-looking total. Do NOT use to qualify a single deal (route to `deal-qualification-meddic`), construct the forecast call from a locked pipeline (route to `forecast-accuracy`), or configure CRM stage fields in a specific vendor tool (out of scope — this skill is strategy, not tooling). ## Cognition cluster - **Mental model 6 — Theory of constraints.** A pipeline has one binding stage at any time; rates upstream of the constraint are inventory that never ships, rates downstream cannot exceed the constraint. Find the constraint before changing anything else. See [`docs/contracts/mental-models.md`](../../../docs/contracts/mental-models.md) § 6. - **Mental model 16 — Leading vs. lagging indicators.** Stage-to-stage conversion is leading; closed-won is lagging. A coverage call built on lagging signals can only confirm the miss after it lands. See `mental-models.md` § 16. - **Mental model 3 — Pareto (80/20).** ~20 % of segment × stage cells carry ~80 % of revenue risk. Coverage uniformly applied across cells is theatre; coverage weighted by cell-level conversion is reasoning. See `mental-models.md` § 3. - **Context-spine — product + customer-segment + channel-stage.** Read the **product** slot for what is actually sellable this quarter, the **customer-segment** slot for which segments belong in pipeline (and which are pre-pipeline education), and the **channel-stage** slot for where each segment enters. See [`context-spine`](../../../docs/contracts/context-spine.md). ## Procedure ### Step 0: Inspect — inventory the current pipeline shape Pull stage counts, $ value, age in stage, and stage-to-stage conversion for the trailing two quarters. Inspect whether each stage has a written exit criterion; if not, write one now (one bullet per stage, falsifiable). A pipeline without exit criteria cannot be audited. ### Step 1: Lock stage definitions with exit criteria Each stage gets three lines: 1. **Definition** — what the deal looks like in this stage (one sentence). 2. **Entry trigger** — the buyer event that moves a deal in (not a rep action). 3. **Exit criterion** — the artefact or signal that proves the deal earned the next stage (one bullet, falsifiable; *"meeting booked"* is not falsifiable, *"economic buyer named and confirmed"* is). Reject any stage whose exit criterion is a rep activity ("call made") rather than a buyer signal ("buyer confirmed budget owner"). ### Step 2: Compute per-stage conversion rates with bands For each stage transition, compute the trailing-quarter rate and a 95 % confidence band. Segment by customer-segment (and channel-stage if the channel mix changed). Report the band, not the point — a 30 % rate on 12 deals and a 30 % rate on 300 deals are different signals. ### Step 3: Find the binding constraint The constraint is the stage whose conversion rate is **furthest below its segment-historical median, weighted by $ value flowing through it**. Add deals upstream of any other stage and watch them queue; add deals upstream of the constraint and they queue twice as fast. A pipeline-coverage call that ignores the constraint multiplies inventory the team cannot ship. ### Step 4: Compute coverage cell by cell, not by total Coverage = (pipeline $ at stage *s*) ÷ (target closed-won $ in window) ÷ (cumulative conversion from *s* to closed-won). Compute per segment × stage cell. A 3× total can hide a 0.8× cell — the 0.8× cell is the quarter's risk. ### Step 5: Name three leaks with falsifiable hypotheses For the three lowest coverage cells (or the three steepest conversion-rate drops vs trailing-quarter median), write one sentence per leak: *"\ leaks at \ because \; falsified if \ shows \."* If a cause is not testable in under two weeks, the hypothesis is not yet sharp enough — sharpen before recommending a fix. ### Step 6: Hand back Hand the locked stages, the per-cell coverage table, and the three leak hypotheses to [`forecast-accuracy`](../forecast-accuracy/SKILL.md) for commit / best-case categorisation, and to [`deal-qualification-meddic`](../deal-qualification-meddic/SKILL.md) when the leak is upstream qualification, not late-stage execution. ## Related Skills **WHEN to use this** - Designing or auditing pipeline stages and per-stage rates. - Computing coverage by segment × stage instead of by total. **WHEN NOT to use this** - Single-deal qualification — route to [`deal-qualification-meddic`](../deal-qualification-meddic/SKILL.md). - Forecast call construction from a locked pipeline — route to [`forecast-accuracy`](../forecast-accuracy/SKILL.md). - Product-led conversion-funnel diagnosis (signup → activation → paid) — route to [`funnel-analysis`](../funnel-analysis/SKILL.md). ## When the agent should load this - "Tighten our pipeline stages — exit criteria are vibes." - "Coverage looks 3× and we still missed. Where is the leak?" - "Audit per-stage conversion by segment." - "Welche Stage ist das Bottleneck im Quartal?" ## Output 1. **`stage-definitions.md`** — one block per stage: definition · entry trigger · exit criterion (buyer signal, falsifiable). 2. **`coverage-by-cell.md`** — table of segment × stage cells with $ pipeline, cumulative conversion, and computed coverage. Cells under 1× flagged. 3. **`leak-hypotheses.md`** — three leaks with falsifiable test + expected signal + 2-week deadline. ## Gotcha - A pipeline with exit criteria written as rep activities (*"call made"*) is unauditable — reps move deals on activity, not on buyer signal, and forecasts inherit the noise. - Total-pipeline coverage is the wrong unit. A 3× total made of 5× early-stage and 0.5× late-stage will miss the quarter even though the dashboard looks healthy. - Per-stage conversion rates without confidence bands are gossip dressed as evidence. Twelve deals give you a band so wide the rate is uninformative. ## Do NOT - Do NOT invent stages to flatter the dashboard. Each stage must have a buyer signal earning the transition. - Do NOT compare the quarter's coverage to a fixed historical multiple if segment mix changed — recompute per cell. - Do NOT recommend a fix to a leak before naming the falsifiable test that proves the cause. ## Runnable example Mid-market SaaS, total coverage 3.1×, quarter missed by 18 %. - Stages with exit criteria — *Discovery → Qualified (economic buyer named) → Proposal (pricing in writing) → Negotiation (terms in redline) → Won.* - Per-cell coverage — Mid-Market × Proposal: **0.7×**. Mid-Market × Discovery: **6.4×**. Enterprise × Negotiation: **2.1×**. - Constraint — Proposal → Negotiation conversion 22 % vs 41 % trailing-quarter median (band 14–31 %). Constraint is **Proposal exit**, not pipeline volume. - Leaks — *(1)* Mid-Market proposals stall at pricing-page review; falsified if a pre-proposal pricing-walkthrough call lifts Proposal → Negotiation to 35 %+ within four weeks. *(2)* Enterprise Negotiation drags > 60 days; falsified if procurement-checklist shipped at Proposal stage cuts median age by 20 days. *(3)* Discovery overflow is unqualified — route to `deal-qualification-meddic`. - Hand-off — coverage table + leaks → `forecast-accuracy` for commit / best-case rebuild on the corrected denominator.