{
  "docId": "019dd923-5de0-76bd-a168-f2ba0a2cd584",
  "docSlug": "d726e8e4c68c4b19",
  "documentTitle": "Women in Work Index 2019",
  "authorId": "PwC",
  "authorName": "PwC",
  "documentKindSlug": "consulting-deck",
  "documentKindLabel": "Consulting deck",
  "sourceTypeSlug": "strategy_consulting",
  "sourceTypeLabel": "Strategy consulting",
  "presentationDate": null,
  "orientation": "landscape",
  "aspectRatio": 1.414,
  "pageNumber": 24,
  "pageCount": 44,
  "prevPage": 23,
  "nextPage": 25,
  "slideType": "key_takeaways",
  "function": "quantify_impact",
  "density": "overcrowded",
  "nDataPoints": 8,
  "notes": "Includes specific economic impact projections for China based on female employment and pay gap metrics.",
  "elementsJson": [
    "headline_text",
    "paragraph",
    "bullet_list",
    "big_number"
  ],
  "metadataConfidence": 1,
  "imagePath": null,
  "slideHref": "/slides/019dd923-5de0-76bd-a168-f2ba0a2cd584/24",
  "deckHref": "/decks/019dd923-5de0-76bd-a168-f2ba0a2cd584",
  "deckJsonHref": "/decks/019dd923-5de0-76bd-a168-f2ba0a2cd584.json",
  "deckAnchorHref": "/decks/019dd923-5de0-76bd-a168-f2ba0a2cd584#slide-24",
  "components": [
    {
      "bbox": null,
      "kind": "callout",
      "text": "Closing the gender pay gap would generate a 34% increase in female earnings, equivalent to a $2 trillion boost to female earnings.",
      "attrs": null,
      "subkind": null,
      "toolName": "Visual emphasis",
      "toolSlug": "visual-emphasis",
      "confidence": null,
      "componentId": "019dd952-3be9-762c-ba14-e0df315838aa",
      "frameworkName": null,
      "frameworkSlug": null
    },
    {
      "bbox": {
        "h": 0.2,
        "w": 0.45,
        "x": 0.52,
        "y": 0.25
      },
      "kind": "list",
      "text": "How much are the gains to China from improving female employment? China's female employment rate is very similar to that of our benchmark country, Sweden... the boost to GDP from increasing female employment to match Sweden's would increase Chinese GDP by $497 billion.",
      "attrs": null,
      "subkind": "bullet",
      "toolName": null,
      "toolSlug": null,
      "confidence": null,
      "componentId": "03acfcb6-4dbb-401f-a3c8-c87b5347d877",
      "frameworkName": null,
      "frameworkSlug": null
    },
    {
      "bbox": {
        "h": 0.2,
        "w": 0.45,
        "x": 0.05,
        "y": 0.55
      },
      "kind": "list",
      "text": "If included in our Index, how would China perform? China's significant economic advancement has generated economic opportunities for women... Women in China still face challenges in the workplace. It has a large gender pay gap (25%).",
      "attrs": null,
      "subkind": "bullet",
      "toolName": null,
      "toolSlug": null,
      "confidence": null,
      "componentId": "1803448a-b235-404c-a5e3-7cf7418bec9d",
      "frameworkName": null,
      "frameworkSlug": null
    },
    {
      "bbox": {
        "h": 0.2,
        "w": 0.45,
        "x": 0.52,
        "y": 0.45
      },
      "kind": "list",
      "text": "How much are the gains to China from closing the gender pay gap? At 25%, China's gender pay gap is higher than the OECD average... Closing the gender pay gap would generate a 34% increase in female earnings, equivalent to a $2 trillion boost to female earnings.",
      "attrs": null,
      "subkind": "bullet",
      "toolName": null,
      "toolSlug": null,
      "confidence": null,
      "componentId": "f875848c-c979-4f14-8976-9c0a5981c5e0",
      "frameworkName": null,
      "frameworkSlug": null
    },
    {
      "bbox": {
        "h": 0.15,
        "w": 0.2,
        "x": 0.55,
        "y": 0.75
      },
      "kind": "metric",
      "text": "2% Boost to GDP by matching female employment rates to Sweden's",
      "attrs": null,
      "subkind": "big-number",
      "toolName": null,
      "toolSlug": null,
      "confidence": null,
      "componentId": "2a62ac8a-eedf-442f-a016-63388364c0aa",
      "frameworkName": null,
      "frameworkSlug": null
    },
    {
      "bbox": {
        "h": 0.15,
        "w": 0.2,
        "x": 0.78,
        "y": 0.75
      },
      "kind": "metric",
      "text": "34% Increase to female earnings from closing the gender pay gap",
      "attrs": null,
      "subkind": "big-number",
      "toolName": null,
      "toolSlug": null,
      "confidence": null,
      "componentId": "ed265349-b15c-4b1d-be35-8abc2a699d56",
      "frameworkName": null,
      "frameworkSlug": null
    },
    {
      "bbox": null,
      "kind": "metric",
      "text": "GDP boost and female earnings increase: 34%",
      "attrs": null,
      "subkind": "primary",
      "toolName": "Quantification",
      "toolSlug": "quantification",
      "confidence": null,
      "componentId": "019dd952-3be9-762c-ba14-e73a4dd1dab8",
      "frameworkName": null,
      "frameworkSlug": null
    },
    {
      "bbox": {
        "h": 0.3,
        "w": 0.45,
        "x": 0.05,
        "y": 0.25
      },
      "kind": "paragraph",
      "text": "The world's second largest economy, China has experienced cumulative GDP growth of over 42% over the five years from 2012-2017, which has increased economic prospects for both genders. Over this period, China has continued to have one of the highest female labour force participation rates (69%) and female full-time employment rates (89%) in the world... There have been gains for women in educational attainment...",
      "attrs": null,
      "subkind": "paragraph",
      "toolName": null,
      "toolSlug": null,
      "confidence": null,
      "componentId": "64672bae-df82-4616-aa67-440e0d3412e3",
      "frameworkName": null,
      "frameworkSlug": null
    },
    {
      "bbox": {
        "h": 0.1,
        "w": 0.4,
        "x": 0.05,
        "y": 0.85
      },
      "kind": "source-note",
      "text": "1. World Bank 2. United Nations, National Bureau of Statistics 2017 All other data is from PwC analysis, using data sources listed in the appendix.",
      "attrs": null,
      "subkind": null,
      "toolName": null,
      "toolSlug": null,
      "confidence": null,
      "componentId": "c78d1334-5cae-4787-a975-828c10f0e5fc",
      "frameworkName": null,
      "frameworkSlug": null
    },
    {
      "bbox": {
        "h": 0.15,
        "w": 0.9,
        "x": 0.05,
        "y": 0.07
      },
      "kind": "title",
      "text": "China would rank in between Slovakia (26th) and Japan (27th) on our Index, highlighting that there is significant scope for further improvement in female employment prospects",
      "attrs": null,
      "subkind": "action-title",
      "toolName": null,
      "toolSlug": null,
      "confidence": null,
      "componentId": "4e651575-5a13-45c1-a04d-55c400abe2da",
      "frameworkName": null,
      "frameworkSlug": null
    }
  ],
  "metrics": [],
  "tools": [],
  "frameworks": [],
  "arcBeats": [
    {
      "to": 44,
      "from": 21,
      "beatId": "3fa89504-a775-4611-b3b2-934eebfed37a",
      "arcName": "Monroe's Motivated Sequence",
      "arcSlug": "monroes-sequence",
      "beatName": "Action",
      "beatSlug": "monroes-sequence-action",
      "evidence": "The report concludes with recommendations for organisations to translate policies into effective change.",
      "position": 3,
      "confidence": 0.8,
      "parentBeatName": "Resolution",
      "parentBeatSlug": "resolution"
    }
  ],
  "loops": [
    {
      "to": 26,
      "from": 23,
      "name": "Pattern Hunter",
      "slug": "02-pattern-hunter",
      "bestFor": "Time-pressed audiences, building consensus, when data is strong",
      "matchId": "908cf81f-1762-4ba6-874a-ebab87c53a6b",
      "evidence": "The report compares the performance of China and India on female economic empowerment.",
      "position": 1,
      "objective": "Identifying patterns and trends in female economic empowerment",
      "structure": "Evidence A -> Evidence B -> Evidence C -> Pattern/Conclusion",
      "confidence": 0.6,
      "description": "Group multiple pieces of evidence that together point to a pattern or conclusion"
    }
  ],
  "imagePathAlt": null,
  "thumbSrc": null,
  "thumbSrcAlt": null,
  "locked": true
}