Feedback

{
  "id": "TRIZ-23",
  "title": "Feedback",
  "intent": "Improve control and outcomes by continuously feeding results back into the system to adjust behavior.",
  "triz_principle": {
    "number": 23,
    "name": "Feedback",
    "definition": "Introduce feedback to improve or regulate a process or system."
  },
  "problem_understanding": {
    "core_contradiction": "We want stable, predictable results, but actions are taken with incomplete or delayed information.",
    "why_this_hurts": "Without feedback, systems drift, mistakes repeat, and optimization relies on assumptions instead of evidence.",
    "typical_signals": [
      "decisions made without measurable outcomes",
      "problems discovered too late",
      "same mistakes recurring across cycles",
      "manual reviews disconnected from real usage"
    ]
  },
  "solution_logic": {
    "core_idea": "Close the loop between action and outcome.",
    "key_rule": "Feedback must be fast, relevant, and actionable.",
    "how_it_resolves_the_contradiction": "The system self-corrects based on real results instead of static rules or assumptions."
  },
  "application_patterns": {
    "consulting": [
      "post-decision reviews with measurable KPIs",
      "short feedback loops with stakeholders",
      "evidence-based refinement of recommendations"
    ],
    "software_engineering": [
      "runtime metrics and tracing",
      "user behavior analytics",
      "automated alerts tied to business impact"
    ],
    "architecture": [
      "observability as a first-class concern",
      "closed-loop control systems",
      "adaptive throttling based on live metrics"
    ],
    "enterprise_sap": [
      "monitor MDG rejection reasons and cycle times",
      "feedback-driven tuning of validation rules",
      "replication monitoring feeding back into governance decisions"
    ]
  },
  "anti_patterns": [
    "collecting metrics without acting on them",
    "feedback that arrives too late to matter",
    "too many signals with no prioritization"
  ],
  "usage_guidance": {
    "use_when": [
      "outcomes are uncertain or variable",
      "decisions have delayed or indirect effects",
      "learning and adaptation are required"
    ],
    "do_not_use_when": [
      "feedback cost exceeds value",
      "system behavior must remain fixed"
    ]
  },
  "diagnostic_questions": [
    "What result do we actually observe after action?",
    "How fast does this information return?",
    "Which signal would allow earlier correction?"
  ],
  "example": {
    "before": "Validation rules are defined once and rarely reviewed.",
    "after": "Rules are continuously adjusted based on real rejection and correction data."
  },
  "meta": {
    "schema": "dkharlanau.dataset.byte",
    "schema_version": "1.1",
    "dataset": "TRIZ-bytes",
    "source_project": "cv-ai",
    "source_path": "TRIZ-bytes/TRIZ-23.json",
    "generated_at_utc": "2026-02-03T14:33:32+00:00",
    "creator": {
      "name": "Dzmitryi Kharlanau",
      "role": "SAP Lead",
      "website": "https://dkharlanau.github.io",
      "linkedin": "https://www.linkedin.com/in/dkharlanau"
    },
    "attribution": {
      "attribution_required": true,
      "preferred_citation": "Dzmitryi Kharlanau (SAP Lead). Dataset bytes: https://dkharlanau.github.io"
    },
    "license": {
      "name": "",
      "spdx": "",
      "url": ""
    },
    "links": {
      "website": "https://dkharlanau.github.io",
      "linkedin": "https://www.linkedin.com/in/dkharlanau"
    },
    "contact": {
      "preferred": "linkedin",
      "linkedin": "https://www.linkedin.com/in/dkharlanau"
    },
    "canonical_url": "https://dkharlanau.github.io/datasets/TRIZ-bytes/TRIZ-23.json",
    "created_at_utc": "2026-02-03T14:33:32+00:00",
    "updated_at_utc": "2026-02-03T15:29:02+00:00",
    "provenance": {
      "source_type": "chat_export_extraction",
      "note": "Extracted and curated by Dzmitryi Kharlanau; enriched for attribution and crawler indexing."
    },
    "entity_type": "triz_byte",
    "entity_subtype": "",
    "summary": "Improve control and outcomes by continuously feeding results back into the system to adjust behavior."
  }
}