forecast-accuracy

When to use

• The quarterly forecast call is being constructed and the team needs a categorisation rule that survives retro — not a feel-good number that flatters this week.
• Commit has missed two or more quarters and nobody can name which signals broke — the retro-loop is missing or the categorisation rule is unwritten.
• A new RevOps lead inherits a pipeline and needs to rebuild the forecast call without inheriting last regime's optimism bias.

Do NOT use to design pipeline stages (route to pipeline-strategy), qualify a single deal (route to deal-qualification-meddic), or build the finance-side top-down / bottom-up model (composes against — but does not duplicate — the finance-partner forecasting capability, via the forecast-construction-shape interface).

Cognition cluster

• Mental model 16 — Leading vs. lagging indicators. Closed-won is lagging; per-stage conversion and MEDDIC-slot completeness are leading. A forecast built on lagging signals can only confirm the result after it lands. See docs/contracts/mental-models.md § 16.
• Mental model 29 — Premortem. Before locking the call, write the post-quarter retro as if commit missed by 20 %. The premortem surfaces which categorisations are riding on weak evidence; demote those before the call locks. See mental-models.md § 29.
• Mental model 9 — Hypothesis-driven thinking. Each commit deal carries a falsifiable claim: "this closes by <date> because <evidence>." If the claim cannot be falsified inside the quarter, the deal is best-case, not commit. See mental-models.md § 9.
• Context-spine — product + customer-segment. Read the product slot for what is actually GA-shippable this quarter (deals depending on non-shipped scope are not commit), and the customer-segment slot for segment-historical close rates — pricing-power and cycle-length differ by segment and the forecast must too. See context-spine.

Procedure

Step 0: Inspect — inherit pipeline + qualification artefacts

Pull stage-definitions.md, coverage-by-cell.md from pipeline-strategy, and the latest meddic-card.md per deal from deal-qualification-meddic. Inspect whether each commit-candidate deal carries falsifiable evidence per MEDDIC slot — a forecast built without that inspection is rep opinion, not categorisation.

Step 1: Lock the three categories with falsifiable rules

1. Commit — deal closes in-window with ≥ 90 % subjective probability and MEDDIC slots all filled with evidence and decision-process has buyer-written dates inside the window.
2. Best-case — deal could close in-window with ≥ 50 % probability and ≤ 2 MEDDIC slots unfilled and at least one decision-process date inside the window.
3. Pipeline — everything else. Pipeline is not a forecast category; it is the population from which commit and best-case are drawn.

Reject "commit" placements that do not meet all three commit criteria, regardless of $ value or rep confidence.

Step 2: Apply the segment-historical close rate

For each deal, compute expected $ = $ × segment-historical in-window close-rate (trailing four quarters). Aggregate by category. If commit-$ exceeds (segment historical commit close-rate × pipeline-$ in commit), the call is structurally optimistic — find the optimism source before defending the number.

Step 3: Premortem the commit list

Write "if commit misses by 20 %, the reason is ___." The most common patterns: (a) one anchor deal slipped, (b) segment cycle lengthened, (c) procurement/legal queues bunched at quarter-end. Tag each commit deal with which of these would kill it; deals tagged with two or more move to best-case.

Step 4: Construct the call with confidence bands

Report commit $ = sum of commit-tagged after Step 3 demotions. Best-case $ = commit + best-case-tagged. Attach the band: "commit ± <historical-deviation>; best-case ± <historical upside>". A call without a band has no honesty about its prior miss-rate.

Step 5: Run the accuracy retro-loop at quarter-end

Compare predicted commit / best-case / pipeline to actual closed-won by category. Compute per-rep, per-segment, and per-stage miss-rate. Patterns that repeat for two quarters become categorisation rule changes in Step 1; one-off misses become deal-level evidence upgrades in Step 0.

Related Skills

WHEN to use this

• Constructing the quarterly forecast call from a qualified pipeline.
• Running the accuracy retro-loop and feeding it back into Step 1.

WHEN NOT to use this

• Designing pipeline stages or per-stage conversion targets — route to pipeline-strategy.
• Single-deal qualification or disqualification — route to deal-qualification-meddic.
• Finance-side top-down model or board-deck forecast — composes against (does not replace) the finance-partner forecasting capability via the forecast-construction-shape interface.

When the agent should load this

• "Build the Q3 forecast call."
• "Why does our commit keep missing?"
• "Run the forecast retro for last quarter."
• "Welche Deals gehören wirklich in Commit?"

Output

1. forecast-call.md — commit $ and best-case $ with confidence bands; per-segment breakdown.
2. commit-list.md — one row per commit deal: $, segment, MEDDIC-completeness, decision-process date, premortem tag (none / single-risk / two-risk demoted).
3. retro-deltas.md (at quarter-end) — predicted vs actual per category, per-segment, per-rep miss-rate, and the categorisation-rule change (if any) for next quarter.

Gotcha

• "Strong commit" without buyer-written dates inside the window is a wish, not a forecast. Subjective probability without artefact evidence is what the retro will punish.
• Segment-historical close rates change after a pricing change, a packaging change, or a competitive shift. Recompute the rates when the segment shape changes, otherwise the call inherits the old regime's optimism.
• Reporting commit as a point estimate without the band hides the prior miss-rate. A team that has missed by 18 % twice and reports commit ± 0 % is performing forecasting, not doing it.

Do NOT

• Do NOT place a deal in commit because the size is large; size is independent of evidence.
• Do NOT skip the premortem on commit deals — most misses come from a small number of anchor deals slipping, and the premortem is where you catch them.
• Do NOT change categorisation rules on a single-quarter miss; rules change on a two-quarter pattern.

Runnable example

End of Q2, last two commits missed by 14 % and 21 %.

• Step 1 enforcement — three deals placed in commit had ≥ 2 MEDDIC slots open; demoted to best-case (–$ 540 k commit, +$ 540 k best-case).
• Segment close-rate — Mid-Market historical commit close-rate is 78 %; commit-$ implies 91 % aggregate close-rate; structural optimism of ~$ 320 k.
• Premortem — two anchor deals (each > 10 % of commit) tagged single-risk (procurement queue); one tagged two-risk (no buyer-written date) → demoted.
• Final call — "commit $ 4.1 m ± 12 % (historical deviation); best-case $ 6.7 m + 8 % / – 14 %." Commit-list flags the two procurement-risk anchors for VP-level intervention.
• Retro at quarter-end — predicted commit $ 4.1 m, actual $ 4.0 m; rule unchanged; one rep over-commits two quarters running → categorisation-coaching action.