Pipeline Context Notes
Container handle for the side-by-side contextual notes — pairs sales.pipeline_assumptions (left slot) with sales.pipeline_risk_factors (right slot) in the TwoColumnTextarea widget. Visually positions the "what we're assuming" narrative directly next to the "what could break those assumptions" narrative, forcing the team to write them in concert (rather than as two independent surfaces that drift apart over quarters). Common pitfall: writing assumptions without their corresponding risks (or vice versa) means the forecast is incomplete — every assumption should pair to a risk factor that captures the failure mode. — 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_context_notes
Type: Text
Domain: Sales
Definition
Container handle for the side-by-side contextual notes — pairs sales.pipeline_assumptions (left slot) with sales.pipeline_risk_factors (right slot) in the TwoColumnTextarea widget. Visually positions the "what we're assuming" narrative directly next to the "what could break those assumptions" narrative, forcing the team to write them in concert (rather than as two independent surfaces that drift apart over quarters). Common pitfall: writing assumptions without their corresponding risks (or vice versa) means the forecast is incomplete — every assumption should pair to a risk factor that captures the failure mode.
Formula
Container — two-slot composite. Left slot = sales.pipeline_assumptions, right slot = sales.pipeline_risk_factors. No additional content; the value of the container is purely the side-by-side rendering, which structurally encourages assumptions and risks to be written together.Why it matters
Forces a discipline that significantly improves forecast quality — assumption / risk pairs are more useful than either alone because each risk has a sensitivity (how much the forecast moves if the corresponding assumption breaks).
How to interpret
Well-constructed pairs read like "Assume win rate of 28% in Q3 → Risk: Win rate has dropped below 25% in months with competitive entry." A board reading the surface should be able to identify every risk's sensitivity by cross-referencing to the assumption.
Related KPIs
sales.pipeline_assumptionssales.pipeline_risk_factorssales.weighted_forecastsales.quarterly_forecastsales.key_concerns
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_context_notes.json - All Sales KPIs:
/api/ontology/sales.json - Full catalog:
/api/ontology/index.json
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).
Pipeline Deal Count
Total number of active opportunities in the pipeline (open stages only — excludes closed-won and closed-lost). The volume side of pipeline coverage; paired with pipeline_value gives the average deal size and the deal-count vs deal-size ratio that characterizes the motion shape. Common pitfall: counting non-bona-fide opportunities (orphaned trials, demo requests that never converted to a real evaluation) inflates the number — apply a stage-floor cutoff (e.g. SQL or higher) so the count reflects committed evaluation activity. — Sales KPI, I'mBoard-authored (editorial tier).