{
  "version": "1.3.0",
  "releasedAt": "2026-05-20",
  "kpi": {
    "rogueId": "sales.pipeline_assumptions",
    "slug": "pipeline_assumptions",
    "domain": "sales",
    "defaultLabel": "Pipeline Assumptions",
    "description": "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).",
    "fieldType": "text",
    "unit": null,
    "maturity": "general",
    "suggestedForStages": [
      "seriesA",
      "seriesB",
      "seriesC",
      "public"
    ],
    "defaultOwningFunctions": [
      "Sales"
    ],
    "stageRelevance": {
      "seriesA": "recommended",
      "seriesB": "recommended",
      "seriesC": "recommended",
      "public": "recommended"
    },
    "definitionSource": {
      "tier": "editorial",
      "sourceName": "imboard Editorial",
      "sourceUrl": null,
      "sectionRef": null,
      "publicationDate": "2026-04-01",
      "attributionNotice": null
    },
    "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\").",
    "whyItMatters": "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.",
    "interpretationGuidance": "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\").",
    "relatedKpiIds": [
      "sales.pipeline_risk_factors",
      "sales.pipeline_context_notes",
      "sales.weighted_forecast",
      "sales.quarterly_forecast",
      "sales.win_rate"
    ]
  }
}