{ "docId": "019dd923-5de0-76bd-a16b-451df9a6d149", "docSlug": "e97464cc0a103dac", "documentTitle": "Southeast Asia's Green Economy", "authorId": "Bain", "authorName": "Bain & Company", "documentKindSlug": "consulting-deck", "documentKindLabel": "Consulting deck", "sourceTypeSlug": "strategy_consulting", "sourceTypeLabel": "Strategy consulting", "presentationDate": null, "orientation": "landscape", "aspectRatio": 1.778, "pageNumber": 93, "pageCount": 174, "prevPage": 92, "nextPage": 94, "slideType": "market_landscape", "function": "analyze_data", "density": "overcrowded", "nDataPoints": 24, "notes": "The slide uses a combination of key metrics (left) and comparative charts (right) to illustrate the economic importance of the auto sector and the shift in import dynamics.", "elementsJson": [ "headline_text", "big_number", "bar_chart_100pct", "bar_chart_stacked", "callout_box", "footnote" ], "metadataConfidence": 1, "imagePath": null, "slideHref": "/slides/019dd923-5de0-76bd-a16b-451df9a6d149/93", "deckHref": "/decks/019dd923-5de0-76bd-a16b-451df9a6d149", "deckJsonHref": "/decks/019dd923-5de0-76bd-a16b-451df9a6d149.json", "deckAnchorHref": "/decks/019dd923-5de0-76bd-a16b-451df9a6d149#slide-93", "components": [ { "bbox": { "h": 0.06, "w": 0.35, "x": 0.05, "y": 0.18 }, "kind": "callout", "text": "Auto manufacturing is important to SEA-6 economy", "attrs": null, "subkind": "primary", "toolName": null, "toolSlug": null, "confidence": null, "componentId": "6bbe9b41-f014-408f-afbd-4592de8e9917", "frameworkName": null, "frameworkSlug": null }, { "bbox": { "h": 0.06, "w": 0.53, "x": 0.42, "y": 0.18 }, "kind": "callout", "text": "ICE dominates SEA production; EV imports from global leaders (e.g., CN) are rapidly growing, posing competition risks to incumbent manufacturing hubs", "attrs": null, "subkind": "primary", "toolName": null, "toolSlug": null, "confidence": null, "componentId": "ae326b31-bf8f-4234-b992-7ccdc4761a97", "frameworkName": null, "frameworkSlug": null }, { "bbox": { "h": 0.45, "w": 0.23, "x": 0.72, "y": 0.35 }, "kind": "chart", "text": "SEA-6 Import of EV ($ billion, 2022-23)", "attrs": null, "subkind": "bar-stacked", "toolName": null, "toolSlug": null, "confidence": null, "componentId": "f3edcd65-f7f7-46c5-ad4d-8b05e4b1edc6", "frameworkName": null, "frameworkSlug": null }, { "bbox": { "h": 0.45, "w": 0.28, "x": 0.38, "y": 0.35 }, "kind": "chart", "text": "4W production (million vehicles, 2024)", "attrs": null, "subkind": "bar-stacked-100pct", "toolName": null, "toolSlug": null, "confidence": null, "componentId": "f2ef57ee-c9ef-4fb3-a4a3-9a2bfd1b78bd", "frameworkName": null, "frameworkSlug": null }, { "bbox": { "h": 0.1, "w": 0.25, "x": 0.05, "y": 0.74 }, "kind": "metric", "text": "~850K employment in auto sector", "attrs": null, "subkind": "big-number", "toolName": null, "toolSlug": null, "confidence": null, "componentId": "125fef2e-2e67-4cfe-a184-86b6e228f9b1", "frameworkName": null, "frameworkSlug": null }, { "bbox": { "h": 0.1, "w": 0.25, "x": 0.05, "y": 0.58 }, "kind": "metric", "text": "~1M employment in auto sector", "attrs": null, "subkind": "big-number", "toolName": null, "toolSlug": null, "confidence": null, "componentId": "56b7fef4-7903-4ab2-9dc9-43b5a8f504aa", "frameworkName": null, "frameworkSlug": null }, { "bbox": { "h": 0.1, "w": 0.25, "x": 0.05, "y": 0.42 }, "kind": "metric", "text": "~10% contribution to GDP in both Indonesia and Thailand", "attrs": null, "subkind": "big-number", "toolName": null, "toolSlug": null, "confidence": null, "componentId": "a4c7cf44-3d9c-4ebe-9e15-b5f04420477d", "frameworkName": null, "frameworkSlug": null }, { "bbox": { "h": 0.1, "w": 0.25, "x": 0.05, "y": 0.28 }, "kind": "metric", "text": "~$300B contribution to total SEA-6 GDP", "attrs": null, "subkind": "big-number", "toolName": null, "toolSlug": null, "confidence": null, "componentId": "d7549729-d375-4407-b293-0161a14d7d0b", "frameworkName": null, "frameworkSlug": null }, { "bbox": null, "kind": "metric", "text": "GDP contribution: $300B", "attrs": null, "subkind": "primary", "toolName": "Quantification", "toolSlug": "quantification", "confidence": null, "componentId": "019dd952-0490-77fe-9d35-b2c56495e61e", "frameworkName": null, "frameworkSlug": null }, { "bbox": { "h": 0.05, "w": 0.6, "x": 0.05, "y": 0.94 }, "kind": "source-note", "text": "Notes: (1) Data from S&P Global; (2) Employment as of 2023; (3) Employment as of 2024; (4) Import of EV data excludes Vietnam as data is not available for 2023. Sources: EVAT; S&P Global; Thailand National Statistical Office; Bain analysis; UN Comtrade; Lit. search", "attrs": null, "subkind": null, "toolName": null, "toolSlug": null, "confidence": null, "componentId": "6d12cd00-8c86-4edd-b283-8e4d94418550", "frameworkName": null, "frameworkSlug": null }, { "bbox": { "h": 0.08, "w": 0.85, "x": 0.04, "y": 0.06 }, "kind": "title", "text": "SEA auto manufacturing is an important economic contributor that faces increasing competition from EV imports due to its high reliance on ICE", "attrs": null, "subkind": "headline", "toolName": null, "toolSlug": null, "confidence": null, "componentId": "9041f84f-9f56-4acd-acbd-711f55e2070f", "frameworkName": null, "frameworkSlug": null } ], "metrics": [], "tools": [ { "name": "Big Idea Formula", "slug": "big-idea-formula", "agent": "Storyteller", "layer": "slide", "matchId": "5968a764-2bb1-4d7b-a707-d2bc06d35f9a", "evidence": "metric/big-number: ~10% contribution to GDP in both Indonesia and Thailand", "confidence": 0.7 } ], "frameworks": [], "arcBeats": [ { "to": 145, "from": 59, "beatId": "019dd95a-07a5-761b-9144-94c0617c4e8b", "arcName": "The Consultant's Gambit", "arcSlug": "consultants-gambit", "beatName": "Evidence & Proof", "beatSlug": "consultants-gambit-evidence-proof", "evidence": "Bioeconomy, grid, EV, finance, carbon markets, green AI deep dives with sizing and case studies", "position": 4, "confidence": 88, "parentBeatName": "Evidence", "parentBeatSlug": "evidence" }, { "to": 151, "from": 59, "beatId": "019dd95a-07a5-761b-9144-a5b7a27b3bf4", "arcName": "The Triple Take", "arcSlug": "triple-take", "beatName": "The Action (Now What)", "beatSlug": "triple-take-the-action-now-what", "evidence": "Per-system implementation levers and recommendations", "position": 3, "confidence": 70, "parentBeatName": "Resolution", "parentBeatSlug": "resolution" } ], "loops": [ { "to": 103, "from": 89, "name": "Root Cause Tree", "slug": "37-root-cause-tree", "bestFor": "Problem diagnosis, quality issues, operational failures", "matchId": "019dd95a-088c-724c-b313-5aace09b95bc", "evidence": "Takeaways -> emissions/adoption data -> systemic challenges -> $53B impact -> levers -> investable ideas -> recommendations.", "position": 11, "objective": "Diagnose EV adoption gap and lay out a dual demand+production strategy", "structure": "The Problem -> Branch 1 (Cause A) -> Branch 2 (Cause B) -> Branch 3 (Cause C) -> The Primary Root", "confidence": 80, "description": "Branch out from a problem to its multiple contributing causes" } ], "imagePathAlt": null, "thumbSrc": null, "thumbSrcAlt": null, "locked": true }