{
  "kind": "all",
  "value": "all",
  "collectionKey": "slides:all:all:all-document-kinds:all-producers:all-orientations",
  "filters": {
    "documentKinds": [],
    "sourceTypes": [],
    "orientations": []
  },
  "total": 319975,
  "page": 557,
  "pageSize": 18,
  "pageCount": 17777,
  "rows": [
    {
      "docId": "019dd923-5ca1-7489-b637-2c79eb4da4f7",
      "docSlug": "fd1a22c5f6d95a06",
      "documentTitle": "TEI Microsoft Agentic AI",
      "authorId": "Forrester",
      "authorName": "Forrester",
      "documentKindSlug": "consulting-deck",
      "documentKindLabel": "Consulting deck",
      "sourceTypeSlug": "industry_analyst",
      "sourceTypeLabel": "Industry analyst",
      "presentationDate": null,
      "orientation": "portrait",
      "aspectRatio": 0.773,
      "pageNumber": 10,
      "slideType": "financial_analysis",
      "function": "quantify_impact",
      "notes": "This slide is part of a Total Economic Impact (TEI) study by Forrester Consulting.",
      "imagePath": null,
      "matchCount": 1,
      "evidence": null,
      "slideHref": "/slides/019dd923-5ca1-7489-b637-2c79eb4da4f7/10",
      "deckHref": "/decks/019dd923-5ca1-7489-b637-2c79eb4da4f7",
      "deckAnchorHref": "/decks/019dd923-5ca1-7489-b637-2c79eb4da4f7#slide-10",
      "loopMatches": [
        {
          "to": 15,
          "from": 10,
          "name": "Waterfall Value",
          "slug": "31-waterfall-value",
          "bestFor": "Financial analysis, value bridges, variance explanations",
          "matchId": "019de8c9-ff48-750f-8798-525f365fb210",
          "evidence": "Benefits table p10 then p12-15 break GTM into marketing/sales/CS and product/market innovation drivers.",
          "position": 4,
          "objective": "Quantify Go-to-market transformation benefits",
          "structure": "The Total -> Driver 1 Impact -> Driver 2 Impact -> Driver 3 Impact -> The Remainder",
          "confidence": 84,
          "description": "Break down a big number into its component drivers to show where value is created or lost"
        }
      ],
      "arcBeatMatches": [
        {
          "to": 31,
          "from": 10,
          "beatId": "019de8c9-fdf5-7511-a886-09c1ac2e7bff",
          "arcName": "The Consultant's Gambit",
          "arcSlug": "consultants-gambit",
          "beatName": "Evidence & Proof",
          "beatSlug": null,
          "evidence": "Detailed quantified benefits and costs with risk-adjusted tables and quotes.",
          "position": 4,
          "confidence": 88,
          "parentBeatName": null,
          "parentBeatSlug": null
        },
        {
          "to": 31,
          "from": 10,
          "beatId": "019de8c9-fe8a-778d-ae50-87ab43e9ed55",
          "arcName": "The Triple Take",
          "arcSlug": "triple-take",
          "beatName": "The Implications (So What)",
          "beatSlug": null,
          "evidence": "Per-category benefit and cost analyses with risk-adjusted PV.",
          "position": 2,
          "confidence": 60,
          "parentBeatName": null,
          "parentBeatSlug": null
        }
      ],
      "imagePathAlt": null,
      "thumbSrc": null,
      "thumbSrcAlt": null,
      "locked": true
    },
    {
      "docId": "019dd923-5ca1-7489-b637-2c79eb4da4f7",
      "docSlug": "fd1a22c5f6d95a06",
      "documentTitle": "TEI Microsoft Agentic AI",
      "authorId": "Forrester",
      "authorName": "Forrester",
      "documentKindSlug": "consulting-deck",
      "documentKindLabel": "Consulting deck",
      "sourceTypeSlug": "industry_analyst",
      "sourceTypeLabel": "Industry analyst",
      "presentationDate": null,
      "orientation": "portrait",
      "aspectRatio": 0.773,
      "pageNumber": 11,
      "slideType": "case_study",
      "function": "illustrate_case",
      "notes": "The slide includes a table categorizing B2B marketing and sales AI agent use cases.",
      "imagePath": null,
      "matchCount": 1,
      "evidence": null,
      "slideHref": "/slides/019dd923-5ca1-7489-b637-2c79eb4da4f7/11",
      "deckHref": "/decks/019dd923-5ca1-7489-b637-2c79eb4da4f7",
      "deckAnchorHref": "/decks/019dd923-5ca1-7489-b637-2c79eb4da4f7#slide-11",
      "loopMatches": [
        {
          "to": 15,
          "from": 10,
          "name": "Waterfall Value",
          "slug": "31-waterfall-value",
          "bestFor": "Financial analysis, value bridges, variance explanations",
          "matchId": "019de8c9-ff48-750f-8798-525f365fb210",
          "evidence": "Benefits table p10 then p12-15 break GTM into marketing/sales/CS and product/market innovation drivers.",
          "position": 4,
          "objective": "Quantify Go-to-market transformation benefits",
          "structure": "The Total -> Driver 1 Impact -> Driver 2 Impact -> Driver 3 Impact -> The Remainder",
          "confidence": 84,
          "description": "Break down a big number into its component drivers to show where value is created or lost"
        }
      ],
      "arcBeatMatches": [
        {
          "to": 31,
          "from": 10,
          "beatId": "019de8c9-fdf5-7511-a886-09c1ac2e7bff",
          "arcName": "The Consultant's Gambit",
          "arcSlug": "consultants-gambit",
          "beatName": "Evidence & Proof",
          "beatSlug": null,
          "evidence": "Detailed quantified benefits and costs with risk-adjusted tables and quotes.",
          "position": 4,
          "confidence": 88,
          "parentBeatName": null,
          "parentBeatSlug": null
        },
        {
          "to": 31,
          "from": 10,
          "beatId": "019de8c9-fe8a-778d-ae50-87ab43e9ed55",
          "arcName": "The Triple Take",
          "arcSlug": "triple-take",
          "beatName": "The Implications (So What)",
          "beatSlug": null,
          "evidence": "Per-category benefit and cost analyses with risk-adjusted PV.",
          "position": 2,
          "confidence": 60,
          "parentBeatName": null,
          "parentBeatSlug": null
        }
      ],
      "imagePathAlt": null,
      "thumbSrc": null,
      "thumbSrcAlt": null,
      "locked": true
    },
    {
      "docId": "019dd923-5ca1-7489-b637-2c79eb4da4f7",
      "docSlug": "fd1a22c5f6d95a06",
      "documentTitle": "TEI Microsoft Agentic AI",
      "authorId": "Forrester",
      "authorName": "Forrester",
      "documentKindSlug": "consulting-deck",
      "documentKindLabel": "Consulting deck",
      "sourceTypeSlug": "industry_analyst",
      "sourceTypeLabel": "Industry analyst",
      "presentationDate": null,
      "orientation": "portrait",
      "aspectRatio": 0.773,
      "pageNumber": 12,
      "slideType": "appendix_data",
      "function": "quantify_impact",
      "notes": "The slide provides the logic for a financial model, including baseline revenue, net margin, and risk-adjusted PV.",
      "imagePath": null,
      "matchCount": 1,
      "evidence": null,
      "slideHref": "/slides/019dd923-5ca1-7489-b637-2c79eb4da4f7/12",
      "deckHref": "/decks/019dd923-5ca1-7489-b637-2c79eb4da4f7",
      "deckAnchorHref": "/decks/019dd923-5ca1-7489-b637-2c79eb4da4f7#slide-12",
      "loopMatches": [
        {
          "to": 15,
          "from": 10,
          "name": "Waterfall Value",
          "slug": "31-waterfall-value",
          "bestFor": "Financial analysis, value bridges, variance explanations",
          "matchId": "019de8c9-ff48-750f-8798-525f365fb210",
          "evidence": "Benefits table p10 then p12-15 break GTM into marketing/sales/CS and product/market innovation drivers.",
          "position": 4,
          "objective": "Quantify Go-to-market transformation benefits",
          "structure": "The Total -> Driver 1 Impact -> Driver 2 Impact -> Driver 3 Impact -> The Remainder",
          "confidence": 84,
          "description": "Break down a big number into its component drivers to show where value is created or lost"
        }
      ],
      "arcBeatMatches": [
        {
          "to": 31,
          "from": 10,
          "beatId": "019de8c9-fdf5-7511-a886-09c1ac2e7bff",
          "arcName": "The Consultant's Gambit",
          "arcSlug": "consultants-gambit",
          "beatName": "Evidence & Proof",
          "beatSlug": null,
          "evidence": "Detailed quantified benefits and costs with risk-adjusted tables and quotes.",
          "position": 4,
          "confidence": 88,
          "parentBeatName": null,
          "parentBeatSlug": null
        },
        {
          "to": 31,
          "from": 10,
          "beatId": "019de8c9-fe8a-778d-ae50-87ab43e9ed55",
          "arcName": "The Triple Take",
          "arcSlug": "triple-take",
          "beatName": "The Implications (So What)",
          "beatSlug": null,
          "evidence": "Per-category benefit and cost analyses with risk-adjusted PV.",
          "position": 2,
          "confidence": 60,
          "parentBeatName": null,
          "parentBeatSlug": null
        }
      ],
      "imagePathAlt": null,
      "thumbSrc": null,
      "thumbSrcAlt": null,
      "locked": true
    },
    {
      "docId": "019dd923-5ca1-7489-b637-2c79eb4da4f7",
      "docSlug": "fd1a22c5f6d95a06",
      "documentTitle": "TEI Microsoft Agentic AI",
      "authorId": "Forrester",
      "authorName": "Forrester",
      "documentKindSlug": "consulting-deck",
      "documentKindLabel": "Consulting deck",
      "sourceTypeSlug": "industry_analyst",
      "sourceTypeLabel": "Industry analyst",
      "presentationDate": null,
      "orientation": "portrait",
      "aspectRatio": 0.773,
      "pageNumber": 13,
      "slideType": "appendix_data",
      "function": "quantify_impact",
      "notes": "The slide contains a detailed financial model (TEI) and qualitative testimonials from interviewees.",
      "imagePath": null,
      "matchCount": 1,
      "evidence": null,
      "slideHref": "/slides/019dd923-5ca1-7489-b637-2c79eb4da4f7/13",
      "deckHref": "/decks/019dd923-5ca1-7489-b637-2c79eb4da4f7",
      "deckAnchorHref": "/decks/019dd923-5ca1-7489-b637-2c79eb4da4f7#slide-13",
      "loopMatches": [
        {
          "to": 15,
          "from": 10,
          "name": "Waterfall Value",
          "slug": "31-waterfall-value",
          "bestFor": "Financial analysis, value bridges, variance explanations",
          "matchId": "019de8c9-ff48-750f-8798-525f365fb210",
          "evidence": "Benefits table p10 then p12-15 break GTM into marketing/sales/CS and product/market innovation drivers.",
          "position": 4,
          "objective": "Quantify Go-to-market transformation benefits",
          "structure": "The Total -> Driver 1 Impact -> Driver 2 Impact -> Driver 3 Impact -> The Remainder",
          "confidence": 84,
          "description": "Break down a big number into its component drivers to show where value is created or lost"
        }
      ],
      "arcBeatMatches": [
        {
          "to": 31,
          "from": 10,
          "beatId": "019de8c9-fdf5-7511-a886-09c1ac2e7bff",
          "arcName": "The Consultant's Gambit",
          "arcSlug": "consultants-gambit",
          "beatName": "Evidence & Proof",
          "beatSlug": null,
          "evidence": "Detailed quantified benefits and costs with risk-adjusted tables and quotes.",
          "position": 4,
          "confidence": 88,
          "parentBeatName": null,
          "parentBeatSlug": null
        },
        {
          "to": 31,
          "from": 10,
          "beatId": "019de8c9-fe8a-778d-ae50-87ab43e9ed55",
          "arcName": "The Triple Take",
          "arcSlug": "triple-take",
          "beatName": "The Implications (So What)",
          "beatSlug": null,
          "evidence": "Per-category benefit and cost analyses with risk-adjusted PV.",
          "position": 2,
          "confidence": 60,
          "parentBeatName": null,
          "parentBeatSlug": null
        }
      ],
      "imagePathAlt": null,
      "thumbSrc": null,
      "thumbSrcAlt": null,
      "locked": true
    },
    {
      "docId": "019dd923-5ca1-7489-b637-2c79eb4da4f7",
      "docSlug": "fd1a22c5f6d95a06",
      "documentTitle": "TEI Microsoft Agentic AI",
      "authorId": "Forrester",
      "authorName": "Forrester",
      "documentKindSlug": "consulting-deck",
      "documentKindLabel": "Consulting deck",
      "sourceTypeSlug": "industry_analyst",
      "sourceTypeLabel": "Industry analyst",
      "presentationDate": null,
      "orientation": "portrait",
      "aspectRatio": 0.773,
      "pageNumber": 14,
      "slideType": "appendix_methodology",
      "function": "quantify_impact",
      "notes": "Includes a table of B2B product/portfolio use cases and specific financial assumptions like a 7.33% net margin and 15% risk adjustment.",
      "imagePath": null,
      "matchCount": 1,
      "evidence": null,
      "slideHref": "/slides/019dd923-5ca1-7489-b637-2c79eb4da4f7/14",
      "deckHref": "/decks/019dd923-5ca1-7489-b637-2c79eb4da4f7",
      "deckAnchorHref": "/decks/019dd923-5ca1-7489-b637-2c79eb4da4f7#slide-14",
      "loopMatches": [
        {
          "to": 15,
          "from": 10,
          "name": "Waterfall Value",
          "slug": "31-waterfall-value",
          "bestFor": "Financial analysis, value bridges, variance explanations",
          "matchId": "019de8c9-ff48-750f-8798-525f365fb210",
          "evidence": "Benefits table p10 then p12-15 break GTM into marketing/sales/CS and product/market innovation drivers.",
          "position": 4,
          "objective": "Quantify Go-to-market transformation benefits",
          "structure": "The Total -> Driver 1 Impact -> Driver 2 Impact -> Driver 3 Impact -> The Remainder",
          "confidence": 84,
          "description": "Break down a big number into its component drivers to show where value is created or lost"
        }
      ],
      "arcBeatMatches": [
        {
          "to": 31,
          "from": 10,
          "beatId": "019de8c9-fdf5-7511-a886-09c1ac2e7bff",
          "arcName": "The Consultant's Gambit",
          "arcSlug": "consultants-gambit",
          "beatName": "Evidence & Proof",
          "beatSlug": null,
          "evidence": "Detailed quantified benefits and costs with risk-adjusted tables and quotes.",
          "position": 4,
          "confidence": 88,
          "parentBeatName": null,
          "parentBeatSlug": null
        },
        {
          "to": 31,
          "from": 10,
          "beatId": "019de8c9-fe8a-778d-ae50-87ab43e9ed55",
          "arcName": "The Triple Take",
          "arcSlug": "triple-take",
          "beatName": "The Implications (So What)",
          "beatSlug": null,
          "evidence": "Per-category benefit and cost analyses with risk-adjusted PV.",
          "position": 2,
          "confidence": 60,
          "parentBeatName": null,
          "parentBeatSlug": null
        }
      ],
      "imagePathAlt": null,
      "thumbSrc": null,
      "thumbSrcAlt": null,
      "locked": true
    },
    {
      "docId": "019dd923-5ca1-7489-b637-2c79eb4da4f7",
      "docSlug": "fd1a22c5f6d95a06",
      "documentTitle": "TEI Microsoft Agentic AI",
      "authorId": "Forrester",
      "authorName": "Forrester",
      "documentKindSlug": "consulting-deck",
      "documentKindLabel": "Consulting deck",
      "sourceTypeSlug": "industry_analyst",
      "sourceTypeLabel": "Industry analyst",
      "presentationDate": null,
      "orientation": "portrait",
      "aspectRatio": 0.773,
      "pageNumber": 15,
      "slideType": "appendix_data",
      "function": "quantify_impact",
      "notes": "The slide combines a quantitative financial model (B1-Btr) with qualitative interview-based evidence supporting operational transformation.",
      "imagePath": null,
      "matchCount": 1,
      "evidence": null,
      "slideHref": "/slides/019dd923-5ca1-7489-b637-2c79eb4da4f7/15",
      "deckHref": "/decks/019dd923-5ca1-7489-b637-2c79eb4da4f7",
      "deckAnchorHref": "/decks/019dd923-5ca1-7489-b637-2c79eb4da4f7#slide-15",
      "loopMatches": [
        {
          "to": 15,
          "from": 10,
          "name": "Waterfall Value",
          "slug": "31-waterfall-value",
          "bestFor": "Financial analysis, value bridges, variance explanations",
          "matchId": "019de8c9-ff48-750f-8798-525f365fb210",
          "evidence": "Benefits table p10 then p12-15 break GTM into marketing/sales/CS and product/market innovation drivers.",
          "position": 4,
          "objective": "Quantify Go-to-market transformation benefits",
          "structure": "The Total -> Driver 1 Impact -> Driver 2 Impact -> Driver 3 Impact -> The Remainder",
          "confidence": 84,
          "description": "Break down a big number into its component drivers to show where value is created or lost"
        }
      ],
      "arcBeatMatches": [
        {
          "to": 31,
          "from": 10,
          "beatId": "019de8c9-fdf5-7511-a886-09c1ac2e7bff",
          "arcName": "The Consultant's Gambit",
          "arcSlug": "consultants-gambit",
          "beatName": "Evidence & Proof",
          "beatSlug": null,
          "evidence": "Detailed quantified benefits and costs with risk-adjusted tables and quotes.",
          "position": 4,
          "confidence": 88,
          "parentBeatName": null,
          "parentBeatSlug": null
        },
        {
          "to": 31,
          "from": 10,
          "beatId": "019de8c9-fe8a-778d-ae50-87ab43e9ed55",
          "arcName": "The Triple Take",
          "arcSlug": "triple-take",
          "beatName": "The Implications (So What)",
          "beatSlug": null,
          "evidence": "Per-category benefit and cost analyses with risk-adjusted PV.",
          "position": 2,
          "confidence": 60,
          "parentBeatName": null,
          "parentBeatSlug": null
        }
      ],
      "imagePathAlt": null,
      "thumbSrc": null,
      "thumbSrcAlt": null,
      "locked": true
    },
    {
      "docId": "019dd923-5ca1-7489-b637-2c79eb4da4f7",
      "docSlug": "fd1a22c5f6d95a06",
      "documentTitle": "TEI Microsoft Agentic AI",
      "authorId": "Forrester",
      "authorName": "Forrester",
      "documentKindSlug": "consulting-deck",
      "documentKindLabel": "Consulting deck",
      "sourceTypeSlug": "industry_analyst",
      "sourceTypeLabel": "Industry analyst",
      "presentationDate": null,
      "orientation": "portrait",
      "aspectRatio": 0.773,
      "pageNumber": 16,
      "slideType": "appendix_methodology",
      "function": "quantify_impact",
      "notes": "The slide contains a mix of anecdotal evidence from interviews and specific percentage-based metrics from survey respondents, followed by methodological assumptions.",
      "imagePath": null,
      "matchCount": 1,
      "evidence": null,
      "slideHref": "/slides/019dd923-5ca1-7489-b637-2c79eb4da4f7/16",
      "deckHref": "/decks/019dd923-5ca1-7489-b637-2c79eb4da4f7",
      "deckAnchorHref": "/decks/019dd923-5ca1-7489-b637-2c79eb4da4f7#slide-16",
      "loopMatches": [
        {
          "to": 19,
          "from": 16,
          "name": "Waterfall Value",
          "slug": "31-waterfall-value",
          "bestFor": "Financial analysis, value bridges, variance explanations",
          "matchId": "019de8c9-ff70-7189-a529-ade0d65ed5b7",
          "evidence": "p16-17 labor efficiencies; p18-19 external spend reduction with risk-adjusted PV per driver.",
          "position": 5,
          "objective": "Quantify Operations transformation benefits",
          "structure": "The Total -> Driver 1 Impact -> Driver 2 Impact -> Driver 3 Impact -> The Remainder",
          "confidence": 84,
          "description": "Break down a big number into its component drivers to show where value is created or lost"
        }
      ],
      "arcBeatMatches": [
        {
          "to": 31,
          "from": 10,
          "beatId": "019de8c9-fdf5-7511-a886-09c1ac2e7bff",
          "arcName": "The Consultant's Gambit",
          "arcSlug": "consultants-gambit",
          "beatName": "Evidence & Proof",
          "beatSlug": null,
          "evidence": "Detailed quantified benefits and costs with risk-adjusted tables and quotes.",
          "position": 4,
          "confidence": 88,
          "parentBeatName": null,
          "parentBeatSlug": null
        },
        {
          "to": 31,
          "from": 10,
          "beatId": "019de8c9-fe8a-778d-ae50-87ab43e9ed55",
          "arcName": "The Triple Take",
          "arcSlug": "triple-take",
          "beatName": "The Implications (So What)",
          "beatSlug": null,
          "evidence": "Per-category benefit and cost analyses with risk-adjusted PV.",
          "position": 2,
          "confidence": 60,
          "parentBeatName": null,
          "parentBeatSlug": null
        }
      ],
      "imagePathAlt": null,
      "thumbSrc": null,
      "thumbSrcAlt": null,
      "locked": true
    },
    {
      "docId": "019dd923-5ca1-7489-b637-2c79eb4da4f7",
      "docSlug": "fd1a22c5f6d95a06",
      "documentTitle": "TEI Microsoft Agentic AI",
      "authorId": "Forrester",
      "authorName": "Forrester",
      "documentKindSlug": "consulting-deck",
      "documentKindLabel": "Consulting deck",
      "sourceTypeSlug": "industry_analyst",
      "sourceTypeLabel": "Industry analyst",
      "presentationDate": null,
      "orientation": "portrait",
      "aspectRatio": 0.773,
      "pageNumber": 17,
      "slideType": "appendix_data",
      "function": "analyze_data",
      "notes": "The slide contains a Forrester TEI methodology table for labor efficiency calculations.",
      "imagePath": null,
      "matchCount": 1,
      "evidence": null,
      "slideHref": "/slides/019dd923-5ca1-7489-b637-2c79eb4da4f7/17",
      "deckHref": "/decks/019dd923-5ca1-7489-b637-2c79eb4da4f7",
      "deckAnchorHref": "/decks/019dd923-5ca1-7489-b637-2c79eb4da4f7#slide-17",
      "loopMatches": [
        {
          "to": 19,
          "from": 16,
          "name": "Waterfall Value",
          "slug": "31-waterfall-value",
          "bestFor": "Financial analysis, value bridges, variance explanations",
          "matchId": "019de8c9-ff70-7189-a529-ade0d65ed5b7",
          "evidence": "p16-17 labor efficiencies; p18-19 external spend reduction with risk-adjusted PV per driver.",
          "position": 5,
          "objective": "Quantify Operations transformation benefits",
          "structure": "The Total -> Driver 1 Impact -> Driver 2 Impact -> Driver 3 Impact -> The Remainder",
          "confidence": 84,
          "description": "Break down a big number into its component drivers to show where value is created or lost"
        }
      ],
      "arcBeatMatches": [
        {
          "to": 31,
          "from": 10,
          "beatId": "019de8c9-fdf5-7511-a886-09c1ac2e7bff",
          "arcName": "The Consultant's Gambit",
          "arcSlug": "consultants-gambit",
          "beatName": "Evidence & Proof",
          "beatSlug": null,
          "evidence": "Detailed quantified benefits and costs with risk-adjusted tables and quotes.",
          "position": 4,
          "confidence": 88,
          "parentBeatName": null,
          "parentBeatSlug": null
        },
        {
          "to": 31,
          "from": 10,
          "beatId": "019de8c9-fe8a-778d-ae50-87ab43e9ed55",
          "arcName": "The Triple Take",
          "arcSlug": "triple-take",
          "beatName": "The Implications (So What)",
          "beatSlug": null,
          "evidence": "Per-category benefit and cost analyses with risk-adjusted PV.",
          "position": 2,
          "confidence": 60,
          "parentBeatName": null,
          "parentBeatSlug": null
        }
      ],
      "imagePathAlt": null,
      "thumbSrc": null,
      "thumbSrcAlt": null,
      "locked": true
    },
    {
      "docId": "019dd923-5ca1-7489-b637-2c79eb4da4f7",
      "docSlug": "fd1a22c5f6d95a06",
      "documentTitle": "TEI Microsoft Agentic AI",
      "authorId": "Forrester",
      "authorName": "Forrester",
      "documentKindSlug": "consulting-deck",
      "documentKindLabel": "Consulting deck",
      "sourceTypeSlug": "industry_analyst",
      "sourceTypeLabel": "Industry analyst",
      "presentationDate": null,
      "orientation": "portrait",
      "aspectRatio": 0.773,
      "pageNumber": 18,
      "slideType": "appendix_data",
      "function": "quantify_impact",
      "notes": "Page 18 of a Forrester Consulting study.",
      "imagePath": null,
      "matchCount": 1,
      "evidence": null,
      "slideHref": "/slides/019dd923-5ca1-7489-b637-2c79eb4da4f7/18",
      "deckHref": "/decks/019dd923-5ca1-7489-b637-2c79eb4da4f7",
      "deckAnchorHref": "/decks/019dd923-5ca1-7489-b637-2c79eb4da4f7#slide-18",
      "loopMatches": [
        {
          "to": 19,
          "from": 16,
          "name": "Waterfall Value",
          "slug": "31-waterfall-value",
          "bestFor": "Financial analysis, value bridges, variance explanations",
          "matchId": "019de8c9-ff70-7189-a529-ade0d65ed5b7",
          "evidence": "p16-17 labor efficiencies; p18-19 external spend reduction with risk-adjusted PV per driver.",
          "position": 5,
          "objective": "Quantify Operations transformation benefits",
          "structure": "The Total -> Driver 1 Impact -> Driver 2 Impact -> Driver 3 Impact -> The Remainder",
          "confidence": 84,
          "description": "Break down a big number into its component drivers to show where value is created or lost"
        }
      ],
      "arcBeatMatches": [
        {
          "to": 31,
          "from": 10,
          "beatId": "019de8c9-fdf5-7511-a886-09c1ac2e7bff",
          "arcName": "The Consultant's Gambit",
          "arcSlug": "consultants-gambit",
          "beatName": "Evidence & Proof",
          "beatSlug": null,
          "evidence": "Detailed quantified benefits and costs with risk-adjusted tables and quotes.",
          "position": 4,
          "confidence": 88,
          "parentBeatName": null,
          "parentBeatSlug": null
        },
        {
          "to": 31,
          "from": 10,
          "beatId": "019de8c9-fe8a-778d-ae50-87ab43e9ed55",
          "arcName": "The Triple Take",
          "arcSlug": "triple-take",
          "beatName": "The Implications (So What)",
          "beatSlug": null,
          "evidence": "Per-category benefit and cost analyses with risk-adjusted PV.",
          "position": 2,
          "confidence": 60,
          "parentBeatName": null,
          "parentBeatSlug": null
        }
      ],
      "imagePathAlt": null,
      "thumbSrc": null,
      "thumbSrcAlt": null,
      "locked": true
    },
    {
      "docId": "019dd923-5ca1-7489-b637-2c79eb4da4f7",
      "docSlug": "fd1a22c5f6d95a06",
      "documentTitle": "TEI Microsoft Agentic AI",
      "authorId": "Forrester",
      "authorName": "Forrester",
      "documentKindSlug": "consulting-deck",
      "documentKindLabel": "Consulting deck",
      "sourceTypeSlug": "industry_analyst",
      "sourceTypeLabel": "Industry analyst",
      "presentationDate": null,
      "orientation": "portrait",
      "aspectRatio": 0.773,
      "pageNumber": 19,
      "slideType": "financial_analysis",
      "function": "quantify_impact",
      "notes": "The slide contains a specific financial model table for 'Operations Transformation: External Spend Reduction' and a narrative section for 'People And Culture Transformation: Reduced Employee Attrition'.",
      "imagePath": null,
      "matchCount": 1,
      "evidence": null,
      "slideHref": "/slides/019dd923-5ca1-7489-b637-2c79eb4da4f7/19",
      "deckHref": "/decks/019dd923-5ca1-7489-b637-2c79eb4da4f7",
      "deckAnchorHref": "/decks/019dd923-5ca1-7489-b637-2c79eb4da4f7#slide-19",
      "loopMatches": [
        {
          "to": 19,
          "from": 16,
          "name": "Waterfall Value",
          "slug": "31-waterfall-value",
          "bestFor": "Financial analysis, value bridges, variance explanations",
          "matchId": "019de8c9-ff70-7189-a529-ade0d65ed5b7",
          "evidence": "p16-17 labor efficiencies; p18-19 external spend reduction with risk-adjusted PV per driver.",
          "position": 5,
          "objective": "Quantify Operations transformation benefits",
          "structure": "The Total -> Driver 1 Impact -> Driver 2 Impact -> Driver 3 Impact -> The Remainder",
          "confidence": 84,
          "description": "Break down a big number into its component drivers to show where value is created or lost"
        }
      ],
      "arcBeatMatches": [
        {
          "to": 31,
          "from": 10,
          "beatId": "019de8c9-fdf5-7511-a886-09c1ac2e7bff",
          "arcName": "The Consultant's Gambit",
          "arcSlug": "consultants-gambit",
          "beatName": "Evidence & Proof",
          "beatSlug": null,
          "evidence": "Detailed quantified benefits and costs with risk-adjusted tables and quotes.",
          "position": 4,
          "confidence": 88,
          "parentBeatName": null,
          "parentBeatSlug": null
        },
        {
          "to": 31,
          "from": 10,
          "beatId": "019de8c9-fe8a-778d-ae50-87ab43e9ed55",
          "arcName": "The Triple Take",
          "arcSlug": "triple-take",
          "beatName": "The Implications (So What)",
          "beatSlug": null,
          "evidence": "Per-category benefit and cost analyses with risk-adjusted PV.",
          "position": 2,
          "confidence": 60,
          "parentBeatName": null,
          "parentBeatSlug": null
        }
      ],
      "imagePathAlt": null,
      "thumbSrc": null,
      "thumbSrcAlt": null,
      "locked": true
    },
    {
      "docId": "019dd923-5ca1-7489-b637-2c79eb4da4f7",
      "docSlug": "fd1a22c5f6d95a06",
      "documentTitle": "TEI Microsoft Agentic AI",
      "authorId": "Forrester",
      "authorName": "Forrester",
      "documentKindSlug": "consulting-deck",
      "documentKindLabel": "Consulting deck",
      "sourceTypeSlug": "industry_analyst",
      "sourceTypeLabel": "Industry analyst",
      "presentationDate": null,
      "orientation": "portrait",
      "aspectRatio": 0.773,
      "pageNumber": 20,
      "slideType": "appendix_data",
      "function": "analyze_data",
      "notes": "Includes a Forrester TEI methodology table for attrition reduction and qualitative evidence for onboarding cost reduction.",
      "imagePath": null,
      "matchCount": 1,
      "evidence": null,
      "slideHref": "/slides/019dd923-5ca1-7489-b637-2c79eb4da4f7/20",
      "deckHref": "/decks/019dd923-5ca1-7489-b637-2c79eb4da4f7",
      "deckAnchorHref": "/decks/019dd923-5ca1-7489-b637-2c79eb4da4f7#slide-20",
      "loopMatches": [
        {
          "to": 22,
          "from": 20,
          "name": "Waterfall Value",
          "slug": "31-waterfall-value",
          "bestFor": "Financial analysis, value bridges, variance explanations",
          "matchId": "019de8c9-ff96-775f-9bed-7dc781117652",
          "evidence": "p20 reduced attrition PV; p21-22 onboarding cost savings with explicit per-driver PV math.",
          "position": 6,
          "objective": "Quantify People and Culture transformation benefits",
          "structure": "The Total -> Driver 1 Impact -> Driver 2 Impact -> Driver 3 Impact -> The Remainder",
          "confidence": 82,
          "description": "Break down a big number into its component drivers to show where value is created or lost"
        }
      ],
      "arcBeatMatches": [
        {
          "to": 31,
          "from": 10,
          "beatId": "019de8c9-fdf5-7511-a886-09c1ac2e7bff",
          "arcName": "The Consultant's Gambit",
          "arcSlug": "consultants-gambit",
          "beatName": "Evidence & Proof",
          "beatSlug": null,
          "evidence": "Detailed quantified benefits and costs with risk-adjusted tables and quotes.",
          "position": 4,
          "confidence": 88,
          "parentBeatName": null,
          "parentBeatSlug": null
        },
        {
          "to": 31,
          "from": 10,
          "beatId": "019de8c9-fe8a-778d-ae50-87ab43e9ed55",
          "arcName": "The Triple Take",
          "arcSlug": "triple-take",
          "beatName": "The Implications (So What)",
          "beatSlug": null,
          "evidence": "Per-category benefit and cost analyses with risk-adjusted PV.",
          "position": 2,
          "confidence": 60,
          "parentBeatName": null,
          "parentBeatSlug": null
        }
      ],
      "imagePathAlt": null,
      "thumbSrc": null,
      "thumbSrcAlt": null,
      "locked": true
    },
    {
      "docId": "019dd923-5ca1-7489-b637-2c79eb4da4f7",
      "docSlug": "fd1a22c5f6d95a06",
      "documentTitle": "TEI Microsoft Agentic AI",
      "authorId": "Forrester",
      "authorName": "Forrester",
      "documentKindSlug": "consulting-deck",
      "documentKindLabel": "Consulting deck",
      "sourceTypeSlug": "industry_analyst",
      "sourceTypeLabel": "Industry analyst",
      "presentationDate": null,
      "orientation": "portrait",
      "aspectRatio": 0.773,
      "pageNumber": 21,
      "slideType": "appendix_methodology",
      "function": "quantify_impact",
      "notes": "Includes specific assumptions (50% reduction, 50% productivity capture) and risk-adjusted financial results ($6.5M PV).",
      "imagePath": null,
      "matchCount": 1,
      "evidence": null,
      "slideHref": "/slides/019dd923-5ca1-7489-b637-2c79eb4da4f7/21",
      "deckHref": "/decks/019dd923-5ca1-7489-b637-2c79eb4da4f7",
      "deckAnchorHref": "/decks/019dd923-5ca1-7489-b637-2c79eb4da4f7#slide-21",
      "loopMatches": [
        {
          "to": 22,
          "from": 20,
          "name": "Waterfall Value",
          "slug": "31-waterfall-value",
          "bestFor": "Financial analysis, value bridges, variance explanations",
          "matchId": "019de8c9-ff96-775f-9bed-7dc781117652",
          "evidence": "p20 reduced attrition PV; p21-22 onboarding cost savings with explicit per-driver PV math.",
          "position": 6,
          "objective": "Quantify People and Culture transformation benefits",
          "structure": "The Total -> Driver 1 Impact -> Driver 2 Impact -> Driver 3 Impact -> The Remainder",
          "confidence": 82,
          "description": "Break down a big number into its component drivers to show where value is created or lost"
        }
      ],
      "arcBeatMatches": [
        {
          "to": 31,
          "from": 10,
          "beatId": "019de8c9-fdf5-7511-a886-09c1ac2e7bff",
          "arcName": "The Consultant's Gambit",
          "arcSlug": "consultants-gambit",
          "beatName": "Evidence & Proof",
          "beatSlug": null,
          "evidence": "Detailed quantified benefits and costs with risk-adjusted tables and quotes.",
          "position": 4,
          "confidence": 88,
          "parentBeatName": null,
          "parentBeatSlug": null
        },
        {
          "to": 31,
          "from": 10,
          "beatId": "019de8c9-fe8a-778d-ae50-87ab43e9ed55",
          "arcName": "The Triple Take",
          "arcSlug": "triple-take",
          "beatName": "The Implications (So What)",
          "beatSlug": null,
          "evidence": "Per-category benefit and cost analyses with risk-adjusted PV.",
          "position": 2,
          "confidence": 60,
          "parentBeatName": null,
          "parentBeatSlug": null
        }
      ],
      "imagePathAlt": null,
      "thumbSrc": null,
      "thumbSrcAlt": null,
      "locked": true
    },
    {
      "docId": "019dd923-5ca1-7489-b637-2c79eb4da4f7",
      "docSlug": "fd1a22c5f6d95a06",
      "documentTitle": "TEI Microsoft Agentic AI",
      "authorId": "Forrester",
      "authorName": "Forrester",
      "documentKindSlug": "consulting-deck",
      "documentKindLabel": "Consulting deck",
      "sourceTypeSlug": "industry_analyst",
      "sourceTypeLabel": "Industry analyst",
      "presentationDate": null,
      "orientation": "portrait",
      "aspectRatio": 0.773,
      "pageNumber": 22,
      "slideType": "appendix_data",
      "function": "quantify_impact",
      "notes": "The slide includes a detailed TEI (Total Economic Impact) calculation table and qualitative descriptions of unquantified benefits.",
      "imagePath": null,
      "matchCount": 1,
      "evidence": null,
      "slideHref": "/slides/019dd923-5ca1-7489-b637-2c79eb4da4f7/22",
      "deckHref": "/decks/019dd923-5ca1-7489-b637-2c79eb4da4f7",
      "deckAnchorHref": "/decks/019dd923-5ca1-7489-b637-2c79eb4da4f7#slide-22",
      "loopMatches": [
        {
          "to": 22,
          "from": 20,
          "name": "Waterfall Value",
          "slug": "31-waterfall-value",
          "bestFor": "Financial analysis, value bridges, variance explanations",
          "matchId": "019de8c9-ff96-775f-9bed-7dc781117652",
          "evidence": "p20 reduced attrition PV; p21-22 onboarding cost savings with explicit per-driver PV math.",
          "position": 6,
          "objective": "Quantify People and Culture transformation benefits",
          "structure": "The Total -> Driver 1 Impact -> Driver 2 Impact -> Driver 3 Impact -> The Remainder",
          "confidence": 82,
          "description": "Break down a big number into its component drivers to show where value is created or lost"
        }
      ],
      "arcBeatMatches": [
        {
          "to": 31,
          "from": 10,
          "beatId": "019de8c9-fdf5-7511-a886-09c1ac2e7bff",
          "arcName": "The Consultant's Gambit",
          "arcSlug": "consultants-gambit",
          "beatName": "Evidence & Proof",
          "beatSlug": null,
          "evidence": "Detailed quantified benefits and costs with risk-adjusted tables and quotes.",
          "position": 4,
          "confidence": 88,
          "parentBeatName": null,
          "parentBeatSlug": null
        },
        {
          "to": 31,
          "from": 10,
          "beatId": "019de8c9-fe8a-778d-ae50-87ab43e9ed55",
          "arcName": "The Triple Take",
          "arcSlug": "triple-take",
          "beatName": "The Implications (So What)",
          "beatSlug": null,
          "evidence": "Per-category benefit and cost analyses with risk-adjusted PV.",
          "position": 2,
          "confidence": 60,
          "parentBeatName": null,
          "parentBeatSlug": null
        }
      ],
      "imagePathAlt": null,
      "thumbSrc": null,
      "thumbSrcAlt": null,
      "locked": true
    },
    {
      "docId": "019dd923-5ca1-7489-b637-2c79eb4da4f7",
      "docSlug": "fd1a22c5f6d95a06",
      "documentTitle": "TEI Microsoft Agentic AI",
      "authorId": "Forrester",
      "authorName": "Forrester",
      "documentKindSlug": "consulting-deck",
      "documentKindLabel": "Consulting deck",
      "sourceTypeSlug": "industry_analyst",
      "sourceTypeLabel": "Industry analyst",
      "presentationDate": null,
      "orientation": "portrait",
      "aspectRatio": 0.773,
      "pageNumber": 23,
      "slideType": "appendix_data",
      "function": "summarize",
      "notes": "Part of a Total Economic Impact study by Forrester.",
      "imagePath": null,
      "matchCount": 1,
      "evidence": null,
      "slideHref": "/slides/019dd923-5ca1-7489-b637-2c79eb4da4f7/23",
      "deckHref": "/decks/019dd923-5ca1-7489-b637-2c79eb4da4f7",
      "deckAnchorHref": "/decks/019dd923-5ca1-7489-b637-2c79eb4da4f7#slide-23",
      "loopMatches": [
        {
          "to": 25,
          "from": 23,
          "name": "Build Up",
          "slug": "33-build-up",
          "bestFor": "Pricing justification, cost estimation, market sizing",
          "matchId": "019de8c9-ffbc-750f-913d-214f2d48e6c5",
          "evidence": "p23-25 add first-party agent value on top of base composite, totaling $3.48M risk-adjusted PV.",
          "position": 7,
          "objective": "Build incremental value of first-party Microsoft agents",
          "structure": "The Base -> Add Component A -> Add Component B -> Add Component C -> The Total",
          "confidence": 75,
          "description": "Start from zero and add components to arrive at a total"
        }
      ],
      "arcBeatMatches": [
        {
          "to": 31,
          "from": 10,
          "beatId": "019de8c9-fdf5-7511-a886-09c1ac2e7bff",
          "arcName": "The Consultant's Gambit",
          "arcSlug": "consultants-gambit",
          "beatName": "Evidence & Proof",
          "beatSlug": null,
          "evidence": "Detailed quantified benefits and costs with risk-adjusted tables and quotes.",
          "position": 4,
          "confidence": 88,
          "parentBeatName": null,
          "parentBeatSlug": null
        },
        {
          "to": 31,
          "from": 10,
          "beatId": "019de8c9-fe8a-778d-ae50-87ab43e9ed55",
          "arcName": "The Triple Take",
          "arcSlug": "triple-take",
          "beatName": "The Implications (So What)",
          "beatSlug": null,
          "evidence": "Per-category benefit and cost analyses with risk-adjusted PV.",
          "position": 2,
          "confidence": 60,
          "parentBeatName": null,
          "parentBeatSlug": null
        }
      ],
      "imagePathAlt": null,
      "thumbSrc": null,
      "thumbSrcAlt": null,
      "locked": true
    },
    {
      "docId": "019dd923-5ca1-7489-b637-2c79eb4da4f7",
      "docSlug": "fd1a22c5f6d95a06",
      "documentTitle": "TEI Microsoft Agentic AI",
      "authorId": "Forrester",
      "authorName": "Forrester",
      "documentKindSlug": "consulting-deck",
      "documentKindLabel": "Consulting deck",
      "sourceTypeSlug": "industry_analyst",
      "sourceTypeLabel": "Industry analyst",
      "presentationDate": null,
      "orientation": "portrait",
      "aspectRatio": 0.773,
      "pageNumber": 24,
      "slideType": "appendix_disclosure",
      "function": "summarize",
      "notes": "Includes a testimonial from a CTO and specific risk-adjustment methodology for financial projections.",
      "imagePath": null,
      "matchCount": 1,
      "evidence": null,
      "slideHref": "/slides/019dd923-5ca1-7489-b637-2c79eb4da4f7/24",
      "deckHref": "/decks/019dd923-5ca1-7489-b637-2c79eb4da4f7",
      "deckAnchorHref": "/decks/019dd923-5ca1-7489-b637-2c79eb4da4f7#slide-24",
      "loopMatches": [
        {
          "to": 25,
          "from": 23,
          "name": "Build Up",
          "slug": "33-build-up",
          "bestFor": "Pricing justification, cost estimation, market sizing",
          "matchId": "019de8c9-ffbc-750f-913d-214f2d48e6c5",
          "evidence": "p23-25 add first-party agent value on top of base composite, totaling $3.48M risk-adjusted PV.",
          "position": 7,
          "objective": "Build incremental value of first-party Microsoft agents",
          "structure": "The Base -> Add Component A -> Add Component B -> Add Component C -> The Total",
          "confidence": 75,
          "description": "Start from zero and add components to arrive at a total"
        }
      ],
      "arcBeatMatches": [
        {
          "to": 31,
          "from": 10,
          "beatId": "019de8c9-fdf5-7511-a886-09c1ac2e7bff",
          "arcName": "The Consultant's Gambit",
          "arcSlug": "consultants-gambit",
          "beatName": "Evidence & Proof",
          "beatSlug": null,
          "evidence": "Detailed quantified benefits and costs with risk-adjusted tables and quotes.",
          "position": 4,
          "confidence": 88,
          "parentBeatName": null,
          "parentBeatSlug": null
        },
        {
          "to": 31,
          "from": 10,
          "beatId": "019de8c9-fe8a-778d-ae50-87ab43e9ed55",
          "arcName": "The Triple Take",
          "arcSlug": "triple-take",
          "beatName": "The Implications (So What)",
          "beatSlug": null,
          "evidence": "Per-category benefit and cost analyses with risk-adjusted PV.",
          "position": 2,
          "confidence": 60,
          "parentBeatName": null,
          "parentBeatSlug": null
        }
      ],
      "imagePathAlt": null,
      "thumbSrc": null,
      "thumbSrcAlt": null,
      "locked": true
    },
    {
      "docId": "019dd923-5ca1-7489-b637-2c79eb4da4f7",
      "docSlug": "fd1a22c5f6d95a06",
      "documentTitle": "TEI Microsoft Agentic AI",
      "authorId": "Forrester",
      "authorName": "Forrester",
      "documentKindSlug": "consulting-deck",
      "documentKindLabel": "Consulting deck",
      "sourceTypeSlug": "industry_analyst",
      "sourceTypeLabel": "Industry analyst",
      "presentationDate": null,
      "orientation": "portrait",
      "aspectRatio": 0.773,
      "pageNumber": 25,
      "slideType": "appendix_data",
      "function": "analyze_data",
      "notes": "The table uses a reference-based calculation method (G1-G12) to derive the final risk-adjusted impact.",
      "imagePath": null,
      "matchCount": 1,
      "evidence": null,
      "slideHref": "/slides/019dd923-5ca1-7489-b637-2c79eb4da4f7/25",
      "deckHref": "/decks/019dd923-5ca1-7489-b637-2c79eb4da4f7",
      "deckAnchorHref": "/decks/019dd923-5ca1-7489-b637-2c79eb4da4f7#slide-25",
      "loopMatches": [
        {
          "to": 25,
          "from": 23,
          "name": "Build Up",
          "slug": "33-build-up",
          "bestFor": "Pricing justification, cost estimation, market sizing",
          "matchId": "019de8c9-ffbc-750f-913d-214f2d48e6c5",
          "evidence": "p23-25 add first-party agent value on top of base composite, totaling $3.48M risk-adjusted PV.",
          "position": 7,
          "objective": "Build incremental value of first-party Microsoft agents",
          "structure": "The Base -> Add Component A -> Add Component B -> Add Component C -> The Total",
          "confidence": 75,
          "description": "Start from zero and add components to arrive at a total"
        }
      ],
      "arcBeatMatches": [
        {
          "to": 31,
          "from": 10,
          "beatId": "019de8c9-fdf5-7511-a886-09c1ac2e7bff",
          "arcName": "The Consultant's Gambit",
          "arcSlug": "consultants-gambit",
          "beatName": "Evidence & Proof",
          "beatSlug": null,
          "evidence": "Detailed quantified benefits and costs with risk-adjusted tables and quotes.",
          "position": 4,
          "confidence": 88,
          "parentBeatName": null,
          "parentBeatSlug": null
        },
        {
          "to": 31,
          "from": 10,
          "beatId": "019de8c9-fe8a-778d-ae50-87ab43e9ed55",
          "arcName": "The Triple Take",
          "arcSlug": "triple-take",
          "beatName": "The Implications (So What)",
          "beatSlug": null,
          "evidence": "Per-category benefit and cost analyses with risk-adjusted PV.",
          "position": 2,
          "confidence": 60,
          "parentBeatName": null,
          "parentBeatSlug": null
        }
      ],
      "imagePathAlt": null,
      "thumbSrc": null,
      "thumbSrcAlt": null,
      "locked": true
    },
    {
      "docId": "019dd923-5ca1-7489-b637-2c79eb4da4f7",
      "docSlug": "fd1a22c5f6d95a06",
      "documentTitle": "TEI Microsoft Agentic AI",
      "authorId": "Forrester",
      "authorName": "Forrester",
      "documentKindSlug": "consulting-deck",
      "documentKindLabel": "Consulting deck",
      "sourceTypeSlug": "industry_analyst",
      "sourceTypeLabel": "Industry analyst",
      "presentationDate": null,
      "orientation": "portrait",
      "aspectRatio": 0.773,
      "pageNumber": 26,
      "slideType": "appendix_data",
      "function": "analyze_data",
      "notes": "Includes qualitative evidence and interview insights regarding cost drivers.",
      "imagePath": null,
      "matchCount": 1,
      "evidence": null,
      "slideHref": "/slides/019dd923-5ca1-7489-b637-2c79eb4da4f7/26",
      "deckHref": "/decks/019dd923-5ca1-7489-b637-2c79eb4da4f7",
      "deckAnchorHref": "/decks/019dd923-5ca1-7489-b637-2c79eb4da4f7#slide-26",
      "loopMatches": [
        {
          "to": 31,
          "from": 26,
          "name": "Waterfall Value",
          "slug": "31-waterfall-value",
          "bestFor": "Financial analysis, value bridges, variance explanations",
          "matchId": "019de8c9-ffe1-716f-abe7-541ee06fa868",
          "evidence": "p26 total $25.2M risk-adjusted; p27 planning, p28-29 agent dev, p30-31 subscriptions/consumption.",
          "position": 8,
          "objective": "Decompose total cost into planning, agent development, subscriptions",
          "structure": "The Total -> Driver 1 Impact -> Driver 2 Impact -> Driver 3 Impact -> The Remainder",
          "confidence": 80,
          "description": "Break down a big number into its component drivers to show where value is created or lost"
        }
      ],
      "arcBeatMatches": [
        {
          "to": 31,
          "from": 10,
          "beatId": "019de8c9-fdf5-7511-a886-09c1ac2e7bff",
          "arcName": "The Consultant's Gambit",
          "arcSlug": "consultants-gambit",
          "beatName": "Evidence & Proof",
          "beatSlug": null,
          "evidence": "Detailed quantified benefits and costs with risk-adjusted tables and quotes.",
          "position": 4,
          "confidence": 88,
          "parentBeatName": null,
          "parentBeatSlug": null
        },
        {
          "to": 31,
          "from": 10,
          "beatId": "019de8c9-fe8a-778d-ae50-87ab43e9ed55",
          "arcName": "The Triple Take",
          "arcSlug": "triple-take",
          "beatName": "The Implications (So What)",
          "beatSlug": null,
          "evidence": "Per-category benefit and cost analyses with risk-adjusted PV.",
          "position": 2,
          "confidence": 60,
          "parentBeatName": null,
          "parentBeatSlug": null
        }
      ],
      "imagePathAlt": null,
      "thumbSrc": null,
      "thumbSrcAlt": null,
      "locked": true
    },
    {
      "docId": "019dd923-5ca1-7489-b637-2c79eb4da4f7",
      "docSlug": "fd1a22c5f6d95a06",
      "documentTitle": "TEI Microsoft Agentic AI",
      "authorId": "Forrester",
      "authorName": "Forrester",
      "documentKindSlug": "consulting-deck",
      "documentKindLabel": "Consulting deck",
      "sourceTypeSlug": "industry_analyst",
      "sourceTypeLabel": "Industry analyst",
      "presentationDate": null,
      "orientation": "portrait",
      "aspectRatio": 0.773,
      "pageNumber": 27,
      "slideType": "appendix_data",
      "function": "analyze_data",
      "notes": "Includes a table detailing FTEs, time, costs, and risk adjustments over a three-year period.",
      "imagePath": null,
      "matchCount": 1,
      "evidence": null,
      "slideHref": "/slides/019dd923-5ca1-7489-b637-2c79eb4da4f7/27",
      "deckHref": "/decks/019dd923-5ca1-7489-b637-2c79eb4da4f7",
      "deckAnchorHref": "/decks/019dd923-5ca1-7489-b637-2c79eb4da4f7#slide-27",
      "loopMatches": [
        {
          "to": 31,
          "from": 26,
          "name": "Waterfall Value",
          "slug": "31-waterfall-value",
          "bestFor": "Financial analysis, value bridges, variance explanations",
          "matchId": "019de8c9-ffe1-716f-abe7-541ee06fa868",
          "evidence": "p26 total $25.2M risk-adjusted; p27 planning, p28-29 agent dev, p30-31 subscriptions/consumption.",
          "position": 8,
          "objective": "Decompose total cost into planning, agent development, subscriptions",
          "structure": "The Total -> Driver 1 Impact -> Driver 2 Impact -> Driver 3 Impact -> The Remainder",
          "confidence": 80,
          "description": "Break down a big number into its component drivers to show where value is created or lost"
        }
      ],
      "arcBeatMatches": [
        {
          "to": 31,
          "from": 10,
          "beatId": "019de8c9-fdf5-7511-a886-09c1ac2e7bff",
          "arcName": "The Consultant's Gambit",
          "arcSlug": "consultants-gambit",
          "beatName": "Evidence & Proof",
          "beatSlug": null,
          "evidence": "Detailed quantified benefits and costs with risk-adjusted tables and quotes.",
          "position": 4,
          "confidence": 88,
          "parentBeatName": null,
          "parentBeatSlug": null
        },
        {
          "to": 31,
          "from": 10,
          "beatId": "019de8c9-fe8a-778d-ae50-87ab43e9ed55",
          "arcName": "The Triple Take",
          "arcSlug": "triple-take",
          "beatName": "The Implications (So What)",
          "beatSlug": null,
          "evidence": "Per-category benefit and cost analyses with risk-adjusted PV.",
          "position": 2,
          "confidence": 60,
          "parentBeatName": null,
          "parentBeatSlug": null
        }
      ],
      "imagePathAlt": null,
      "thumbSrc": null,
      "thumbSrcAlt": null,
      "locked": true
    }
  ]
}