{
  "docId": "019dd923-5ca1-7489-b639-4dda27d9d887",
  "docSlug": "67e4131ec199fc70",
  "documentTitle": "Technology Trends Outlook 2022",
  "authorId": "McKinsey",
  "authorName": "McKinsey",
  "documentKindSlug": "consulting-deck",
  "documentKindLabel": "Consulting deck",
  "sourceTypeSlug": "strategy_consulting",
  "sourceTypeLabel": "Strategy consulting",
  "presentationDate": null,
  "orientation": "landscape",
  "aspectRatio": 1.778,
  "pageNumber": 60,
  "pageCount": 184,
  "prevPage": 59,
  "nextPage": 61,
  "slideType": "industry_trends",
  "function": "present_framework",
  "density": "dense",
  "nDataPoints": 0,
  "notes": "The slide uses a process flow diagram to illustrate the ML lifecycle from data management to live-model operations.",
  "elementsJson": [
    "headline_text",
    "paragraph",
    "process_diagram",
    "callout_box"
  ],
  "metadataConfidence": 1,
  "imagePath": null,
  "slideHref": "/slides/019dd923-5ca1-7489-b639-4dda27d9d887/60",
  "deckHref": "/decks/019dd923-5ca1-7489-b639-4dda27d9d887",
  "deckJsonHref": "/decks/019dd923-5ca1-7489-b639-4dda27d9d887.json",
  "deckAnchorHref": "/decks/019dd923-5ca1-7489-b639-4dda27d9d887#slide-60",
  "components": [
    {
      "bbox": {
        "h": 0.5,
        "w": 0.25,
        "x": 0.73,
        "y": 0.35
      },
      "kind": "callout",
      "text": "Future progression: ML production for organizations is delivered reliably and at scale, featuring: deployment scaled across networks, modular structure with high reuse, robust monitoring and testing, automation of common processes, low maintenance cost, lower risk, higher ROI",
      "attrs": null,
      "subkind": "primary",
      "toolName": null,
      "toolSlug": null,
      "confidence": null,
      "componentId": "86837d65-02ac-4c28-9ad2-f99cb9baeacd",
      "frameworkName": null,
      "frameworkSlug": null
    },
    {
      "bbox": null,
      "kind": "callout",
      "text": "ML production for organizations is delivered reliably and at scale, featuring: deployment scaled across networks, modular structure with high reuse, robust monitoring and testing, automation of common processes, low maintenance cost, lower risk, higher ROI.",
      "attrs": null,
      "subkind": null,
      "toolName": "Visual emphasis",
      "toolSlug": "visual-emphasis",
      "confidence": null,
      "componentId": "019dd951-d3ba-7150-b031-216ca884a392",
      "frameworkName": null,
      "frameworkSlug": null
    },
    {
      "bbox": {
        "h": 0.2,
        "w": 0.65,
        "x": 0.04,
        "y": 0.65
      },
      "kind": "diagram",
      "text": "Flow from Live data to Model sustained over time through various stages",
      "attrs": null,
      "subkind": "process",
      "toolName": null,
      "toolSlug": null,
      "confidence": null,
      "componentId": "803240b2-01f7-4099-b977-18141c8cb7dd",
      "frameworkName": null,
      "frameworkSlug": null
    },
    {
      "bbox": {
        "h": 0.15,
        "w": 0.65,
        "x": 0.04,
        "y": 0.44
      },
      "kind": "diagram",
      "text": "ML workflow: 1. Data management, 2. Model development, 3. Model deployment, 4. Live-model operations",
      "attrs": null,
      "subkind": "process",
      "toolName": null,
      "toolSlug": null,
      "confidence": null,
      "componentId": "c2712ae0-162d-422d-9406-6ec86aa63366",
      "frameworkName": null,
      "frameworkSlug": null
    },
    {
      "bbox": {
        "h": 0.1,
        "w": 0.65,
        "x": 0.04,
        "y": 0.25
      },
      "kind": "paragraph",
      "text": "Machine learning (ML) workflows are the processes that bring AI and ML into production for real-world business use. Solutions industrializing ML provide the software and hardware technologies to scale ML workflows and ease the development and deployment of ML for organizations.",
      "attrs": null,
      "subkind": "paragraph",
      "toolName": null,
      "toolSlug": null,
      "confidence": null,
      "componentId": "3b05b06b-e271-450e-9861-1ba81083f868",
      "frameworkName": null,
      "frameworkSlug": null
    },
    {
      "bbox": {
        "h": 0.02,
        "w": 0.15,
        "x": 0.04,
        "y": 0.95
      },
      "kind": "source-note",
      "text": "Source: McKinsey analysis",
      "attrs": null,
      "subkind": null,
      "toolName": null,
      "toolSlug": null,
      "confidence": null,
      "componentId": "e49a5072-3e45-4c2d-8705-75c986914d67",
      "frameworkName": null,
      "frameworkSlug": null
    },
    {
      "bbox": {
        "h": 0.04,
        "w": 0.3,
        "x": 0.04,
        "y": 0.08
      },
      "kind": "title",
      "text": "What is the trend about?",
      "attrs": null,
      "subkind": "headline",
      "toolName": null,
      "toolSlug": null,
      "confidence": null,
      "componentId": "f7239345-3327-4722-8806-01360b2861eb",
      "frameworkName": null,
      "frameworkSlug": null
    }
  ],
  "metrics": [],
  "tools": [
    {
      "name": "Process flow",
      "slug": "process-flow",
      "agent": null,
      "layer": "slide",
      "matchId": "454dc21a-4706-4f2f-a4a5-ce3fc3439495",
      "evidence": "diagram/process: ML workflow: 1. Data management, 2. Model development, 3. Model deployment, 4. Live-model operations",
      "confidence": 0.7
    }
  ],
  "frameworks": [
    {
      "name": "process",
      "slug": null,
      "matchId": "1bc8df55-3ee9-44c4-a21c-078779424188",
      "evidence": "The slide depicts the ML lifecycle as a sequential process flow.",
      "confidence": 0.9
    }
  ],
  "arcBeats": [],
  "loops": [],
  "imagePathAlt": null,
  "thumbSrc": null,
  "thumbSrcAlt": null,
  "locked": true
}