{
  "schema": "vedokrok.public-item.v1",
  "release_id": "MHC-RPUB-20260920-75ad787a",
  "url": "/knowledge/explain-forecast-error-by-component",
  "id": "MHC-D-RESEARCH-0635",
  "version": "0.1.0",
  "title": "Explain forecast error by component",
  "summary": "One error number can hide five different systems.",
  "kind": "protocol",
  "body": "After delivery, compare forecast with actual by components such as active work, wait/dependency time, rework, scope change and realized risks. Keep categories stable enough to compare across projects. Fix the component that repeatedly dominates instead of applying one global pad.",
  "limits": [
    "Categories are models; keep them simple enough to use and refine them only when they change decisions."
  ],
  "topics": [
    "union-project-estimation-and-delivery-realism"
  ],
  "intents": [],
  "source_ids": [
    "RS-F874002E4A58CC3B",
    "RS-3AABED087865223D"
  ],
  "evidence": [
    {
      "claim": "The 2026 Green Book recommends explicitly accounting for optimism bias in cost, benefit and duration estimates and using historical forecast errors from similar proposals where available.",
      "source_id": "RS-F874002E4A58CC3B",
      "role": "supports",
      "note": "The guidance is for UK public appraisal; the transferable principle is empirical correction, not a universal percentage uplift.",
      "locator": "Optimism bias"
    },
    {
      "claim": "Supplementary Green Book optimism-bias guidance recommends basing adjustments on data from past or similar projects and collecting local data to improve future estimates.",
      "source_id": "RS-3AABED087865223D",
      "role": "supports",
      "note": "Reference classes must be genuinely comparable; irrelevant historical projects can make an estimate worse.",
      "locator": "Introduction and making adjustments"
    }
  ],
  "use_when": [
    "A project was late and the only lesson is 'we underestimated.'"
  ],
  "avoid_when": [
    "Categories are models; keep them simple enough to use and refine them only when they change decisions."
  ],
  "example": "A two-day slip turns out to be almost entirely approval latency, so the next improvement targets the review queue rather than adding 20% to development effort.",
  "check": "The post-estimate review identifies the dominant source of forecast error.",
  "steps": [
    "The post-estimate review identifies the dominant source of forecast error."
  ],
  "sources": [
    {
      "id": "RS-F874002E4A58CC3B",
      "title": "The Green Book (2026)",
      "url": "https://www.gov.uk/government/publications/the-green-book-appraisal-and-evaluation-in-central-government/the-green-book-2026"
    },
    {
      "id": "RS-3AABED087865223D",
      "title": "Supplementary Green Book Guidance: Optimism Bias",
      "url": "https://assets.publishing.service.gov.uk/media/5a74dae740f0b65f61322c72/Optimism_bias.pdf"
    }
  ],
  "relations": [
    {
      "from": "MHC-D-RESEARCH-0635",
      "to": "MHC-D-RESEARCH-0636",
      "type": "use_before",
      "url": "/knowledge/maintain-a-local-forecast-error-baseline"
    }
  ],
  "collections": [
    {
      "id": "RC-3C67E080415E2677",
      "title": "Estimate the delivery system, not only the hands-on work",
      "url": "/collections/estimate-the-delivery-system-not-only-the-hands-on-work"
    }
  ]
}