Pipeline Assumptions
Narrative documenting the key assumptions underlying the pipeline forecast — conversion rates by stage, expected sales-cycle length, segment-mix expectations, and any deal-specific dependencies (e.g. "we assume Acme renews their POC by end of month and signs the upgrade in Q3"). Common pitfall: leaving assumptions implicit makes the forecast non-falsifiable — if you don't list the assumptions, you can't identify which one broke when the forecast misses. Renders side-by-side with sales.pipeline_risk_factors in the TwoColumnTextarea widget (sales.pipeline_context_notes container). — Sales KPI, I'mBoard-authored (editorial tier).
I'mBoard-authored (editorial tier)
No public third-party standard anchors this KPI yet, so I'mBoard authors and maintains the definition — transparently labeled as editorial tier. See the ontology methodology for the published vs editorial tier system and the back-attribution workstream.
Rogue ID: sales.pipeline_assumptions
Type: Text
Domain: Sales
Definition
Narrative documenting the key assumptions underlying the pipeline forecast — conversion rates by stage, expected sales-cycle length, segment-mix expectations, and any deal-specific dependencies (e.g. "we assume Acme renews their POC by end of month and signs the upgrade in Q3"). Common pitfall: leaving assumptions implicit makes the forecast non-falsifiable — if you don't list the assumptions, you can't identify which one broke when the forecast misses. Renders side-by-side with sales.pipeline_risk_factors in the TwoColumnTextarea widget (sales.pipeline_context_notes container).
Formula
Free-text narrative — no calculation. Convention: 3–6 bullet assumptions, each one stating the assumed value/rate and the implication if it diverges (e.g. "Assumed Q3 win-rate of 28%; each 5pp miss = $X off forecast").Why it matters
Makes the forecast falsifiable and post-mortem-able — without an assumptions list, missed quarters get attributed to vague "execution" rather than specific assumption failures the next plan should correct.
How to interpret
After-the-fact review: which assumptions held and which broke? An assumption that consistently breaks (e.g. "Q4 always slips") is a planning-process problem, not an execution problem. Strong commentary names 1–2 assumptions explicitly and provides the sensitivity ("if conversion holds at 32%, forecast holds; below 28% we are $X short").
Related KPIs
sales.pipeline_risk_factorssales.pipeline_context_notessales.weighted_forecastsales.quarterly_forecastsales.win_rate
Source
I'mBoard editorial — authored and maintained by I'mBoard, first published 2026-04-01. No third-party standard is cited for this KPI; when one emerges, the definition is back-attributed and promoted to the published tier (a minor version bump). Read the ontology methodology for the published vs editorial tier system, attribution rules, and dispute process.
Stage relevance
| Company stage | Priority |
|---|---|
| Series A | Recommended |
| Series B | Recommended |
| Series C+ | Recommended |
| Public | Recommended |
Suggested for stages: Series A, Series B, Series C+, Public.
Default owning functions
- Sales
Machine-readable
- This KPI as JSON:
/api/ontology/sales/pipeline_assumptions.json - All Sales KPIs:
/api/ontology/sales.json - Full catalog:
/api/ontology/index.json
Opening Pipeline Value
Total pipeline value at the start of the period — the baseline against which the period's pipeline flow (+ new opportunities − won − lost = closing) reconciles. Equal to the prior period's closing pipeline by construction. Surfaces in sales.pipeline_flow as the `start` slot. Common pitfall: restating opening pipeline to retroactively "clean up" stale deals masks the hygiene problem rather than addressing it; cleanup should happen via explicit "old-deal scrub" lines in the flow, not by editing the opening baseline. — Sales KPI, I'mBoard-authored (editorial tier).
Pipeline Composition
Container handle for the manual pipeline-composition summary the bespoke Composition subform edits — four user-entered scalars (total open deals, average deal size, median deal size, largest deal) plus optional `dealsByType` / `dealsByStage` count+value breakdown maps. The median vs. average gap reveals pipeline skew: a median well below the average means a few mega-deals dominate. Common pitfall: carrying the summary forward each quarter instead of re-deriving it from the current open pipeline — roll-forward resets these to zero precisely so a human re-enters the period’s real numbers. — Sales KPI, I'mBoard-authored (editorial tier).