{
  "docId": "019dd923-5ca1-7489-b633-ed30207fe34d",
  "docSlug": "01932b757118df5b",
  "documentTitle": "Oil and Gas EP Incentive Plan Design",
  "authorId": "AlvarezMarsal",
  "authorName": "Alvarez & Marsal",
  "documentKindSlug": "consulting-deck",
  "documentKindLabel": "Consulting deck",
  "sourceTypeSlug": "strategy_consulting",
  "sourceTypeLabel": "Strategy consulting",
  "presentationDate": null,
  "orientation": "portrait",
  "aspectRatio": 0.773,
  "pageNumber": 6,
  "pageCount": 20,
  "prevPage": 5,
  "nextPage": 7,
  "slideType": "other",
  "function": "present_framework",
  "density": "balanced",
  "nDataPoints": 0,
  "notes": "The slide provides a taxonomy for classifying executive bonus structures.",
  "elementsJson": [
    "headline_text",
    "subtitle_text",
    "paragraph",
    "bullet_list"
  ],
  "metadataConfidence": 0.9,
  "imagePath": null,
  "slideHref": "/slides/019dd923-5ca1-7489-b633-ed30207fe34d/6",
  "deckHref": "/decks/019dd923-5ca1-7489-b633-ed30207fe34d",
  "deckJsonHref": "/decks/019dd923-5ca1-7489-b633-ed30207fe34d.json",
  "deckAnchorHref": "/decks/019dd923-5ca1-7489-b633-ed30207fe34d#slide-6",
  "components": [
    {
      "bbox": null,
      "kind": "callout",
      "text": "AIPs utilize performance metrics that are generally measured over a one-year period.",
      "attrs": null,
      "subkind": null,
      "toolName": "Visual emphasis",
      "toolSlug": "visual-emphasis",
      "confidence": null,
      "componentId": "019dd951-a671-77dc-a368-9ae9e11bbb65",
      "frameworkName": null,
      "frameworkSlug": null
    },
    {
      "bbox": {
        "h": 0.22,
        "w": 0.56,
        "x": 0.36,
        "y": 0.32
      },
      "kind": "list",
      "text": "Formulaic – the plan utilizes pre-determined performance criteria with established targets that will determine payout and the compensation committee does not have discretion to adjust payouts (other than negative discretion).\nDiscretionary – the plan may or may not utilize specific, pre-established performance criteria but the compensation committee maintains absolute discretion to adjust payout levels upward or downward.\nPart Formulaic / Part Discretionary – The plan utilizes certain metrics where payout is determined formulaically and others where payout is determined at the discretion of the compensation committee.",
      "attrs": null,
      "subkind": "bullet",
      "toolName": null,
      "toolSlug": null,
      "confidence": null,
      "componentId": "95ec559f-ab03-4ee4-98e7-1d38444f41b7",
      "frameworkName": null,
      "frameworkSlug": null
    },
    {
      "bbox": {
        "h": 0.07,
        "w": 0.56,
        "x": 0.36,
        "y": 0.18
      },
      "kind": "paragraph",
      "text": "As is the case with most industries, companies in the E&P sector generally provide an opportunity for executives to participate in an annual incentive plan (AIP), also commonly called bonus programs. AIPs utilize performance metrics that are generally measured over a one-year period.",
      "attrs": null,
      "subkind": "paragraph",
      "toolName": null,
      "toolSlug": null,
      "confidence": null,
      "componentId": "8f5f8617-6592-4cae-aeda-6ad9268e248e",
      "frameworkName": null,
      "frameworkSlug": null
    },
    {
      "bbox": {
        "h": 0.09,
        "w": 0.34,
        "x": 0.07,
        "y": 0.11
      },
      "kind": "title",
      "text": "ANNUAL INCENTIVE PLANS",
      "attrs": null,
      "subkind": "headline",
      "toolName": null,
      "toolSlug": null,
      "confidence": null,
      "componentId": "60661f6b-3c76-4b74-a87b-684fa1118ad2",
      "frameworkName": null,
      "frameworkSlug": null
    },
    {
      "bbox": {
        "h": 0.03,
        "w": 0.21,
        "x": 0.36,
        "y": 0.27
      },
      "kind": "title",
      "text": "Discretionary vs. Formulaic",
      "attrs": null,
      "subkind": "subtitle",
      "toolName": null,
      "toolSlug": null,
      "confidence": null,
      "componentId": "158f16d6-eeb7-4a70-8a01-df33769a4160",
      "frameworkName": null,
      "frameworkSlug": null
    }
  ],
  "metrics": [],
  "tools": [
    {
      "name": "Data Story Arc",
      "slug": "data-story-arc",
      "agent": "Storyteller",
      "layer": "loop",
      "matchId": "019dd95a-10d4-718b-9f59-821066c2f344",
      "evidence": "Opens AIP loop: context -> conflict (discretion) -> insight (metrics) across p6-8.",
      "confidence": 70
    },
    {
      "name": "Progressive Disclosure",
      "slug": "progressive-disclosure",
      "agent": "Architect",
      "layer": "loop",
      "matchId": "019dd95a-10d4-718b-9f59-8524e0311b8e",
      "evidence": "AIP block reveals dimensions sequentially: definition, then mix, then metrics.",
      "confidence": 65
    },
    {
      "name": "Action Titles",
      "slug": "action-titles",
      "agent": "Architect",
      "layer": "slide",
      "matchId": "019dd95a-10d4-718b-9f59-7d0fc078edba",
      "evidence": "Callout asserts 'AIPs utilize metrics measured over a one-year period' as the so-what.",
      "confidence": 70
    },
    {
      "name": "Audience Definition",
      "slug": "audience-definition",
      "agent": "Storyteller",
      "layer": "slide",
      "matchId": "3b560843-d698-425a-be6d-7d514b09b2ec",
      "evidence": "As is the case with most industries, companies in the E&P sector generally provide an opportunity for executives to participate in an annual incentive plan (AIP), also commonly called bonus programs.",
      "confidence": 0.7
    }
  ],
  "frameworks": [
    {
      "name": "audience-segmentation",
      "slug": null,
      "matchId": "25ae79df-2dea-4899-a8f7-408c10f05d81",
      "evidence": "Categorizing incentive plans into three distinct types based on payout determination.",
      "confidence": 0.8
    }
  ],
  "arcBeats": [
    {
      "to": 8,
      "from": 3,
      "beatId": "019dd95a-0682-776c-8e36-dadd74b41723",
      "arcName": "The Triple Take",
      "arcSlug": "triple-take",
      "beatName": "The Facts (What)",
      "beatSlug": "triple-take-the-facts-what",
      "evidence": "Intro, methodology, AIP prevalence and metrics — pure descriptive findings.",
      "position": 1,
      "confidence": 65,
      "parentBeatName": "Setup",
      "parentBeatSlug": "setup"
    }
  ],
  "loops": [
    {
      "to": 8,
      "from": 6,
      "name": "Pattern Hunter",
      "slug": "02-pattern-hunter",
      "bestFor": "Time-pressed audiences, building consensus, when data is strong",
      "matchId": "019dd95a-07fe-70ce-8d3f-6e42bb2b7ed0",
      "evidence": "Three sequential AIP exhibits (definition, discretionary mix, metric ranking) build to '87% use production' conclusion.",
      "position": 1,
      "objective": "Stack AIP evidence (overview, discretion-vs-formulaic, metric prevalence) into a market pattern",
      "structure": "Evidence A -> Evidence B -> Evidence C -> Pattern/Conclusion",
      "confidence": 78,
      "description": "Group multiple pieces of evidence that together point to a pattern or conclusion"
    }
  ],
  "imagePathAlt": null,
  "thumbSrc": null,
  "thumbSrcAlt": null,
  "locked": true
}