Bottom up market size

Bottom-up market size

Size a market the way a careful analyst would: take Economic Mind's bottom-up build as the spine, show every company that rolls up into it, say plainly how much the headline can be trusted and why, then put that number on a football field next to a few independent estimates so the reader can judge it. The deliverable is data - a Markdown report plus a JSON sidecar - not a styled document; this skill is about the research and the numbers, and layout is the client's job.

The whole value is credibility under scrutiny: a market size is only as good as the build beneath it and the cross-checks beside it. So nothing is hand-waved - the build is carried verbatim from the report, the confidence is reasoned from the report's own stamps, and every cross-check names a credible source.

Two source channels, never mixed

1. The bottom-up build - ONLY the Economic Mind report, unchanged. The headline size, the per-company revenue, share-in-market, in-market revenue, confidence ratings, justifications, the scope boundary and the vintage all come straight from the report. Do not recompute, re-estimate, re-rank, or "improve" any of them, and do not pull a player's revenue from elsewhere. You are presenting the report's build faithfully, not rebuilding it. (The only arithmetic permitted on it is summing the in-market revenues to show the build-to-total and reconciling that to the report's stated headline - shown transparently, never overriding the report.)
2. The cross-checks - a credible-source research pass. The alternative sizing approaches on the football field are not in the report; you construct 2-3 of them from independent credible sources (see the source rules). These sit beside the bottom-up for comparison and never alter it. This is the one place the web is used, and only for the cross-checks.

Keeping these apart is what makes the exercise honest: the anchor stays pristine and the triangulation is clearly a separate, independently-sourced opinion.

Work to files first, then read them back

Context can be compressed mid-task, and a market build has a lot of cells. So immediately after each tool call returns, write its raw output to a file before the next call - the report content, then each cross-check as you research it. Build the deliverable by reading the files back, not from recall. Create one working directory at the start, e.g. em-size/.

Source rules for the cross-checks (strict)

The football field is only as credible as its weakest source, so the bar is high. Use only: (a) primary filings & registries (Proff, Brønnøysund, Allabolag, S&P Capital IQ, Creditsafe, audited annual reports); (b) official statistics (Eurostat, SSB, SCB, national statistics offices); (c) regulators & standards bodies (IMO, USCG, national building authorities); (d) listed-company reports and reputable financial data; (e) named industry associations.

Never use market-research aggregator / press-release "market-size" mills - MarketsandMarkets, Grand View, IMARC, Verified Market Reports, SNS Insider, Precedence, FactMR, Custom Market Insights, SkyQuest, Fortune Business Insights, Mordor, Spherical and the like. Their figures are unreliable and scope-inconsistent. When web-searching, pass these as blocked_domains. Build cross-checks from first principles on credible bases (e.g. official installation statistics × a fire-protection share; a listed group's disclosed segment revenue grossed for the tail; installed base × annual value). If a number exists only from a mill, do not use it - say no credible independent estimate was available and lean on the build.

Restate scope. Any external estimate almost certainly uses a different market definition. Before it can sit on the football field, restate it to the report's in-scope definition (geography, product boundary, revenue basis) and say how you did so in its comment. Never fabricate; if you cannot scope-adjust an estimate honestly, drop it.

Workflow

Phase 1 - Resolve the market & pull the build

1. mkdir -p em-size.
2. search_markets("<the user's market phrase>") (limit ~5). If the top hit's score is ≥1.5× the second's (or there is one hit), use it and announce the choice. Otherwise show the top 3 (Market, Geography, Size, Relevance) and ask the user to pick. If nothing matches, say the market is not covered and stop - do not improvise a size.
3. get_market(slug) for the catalog, then get_market(slug, "bottom-up-supply-side") (use the catalog's actual element name) to get the definition, headline size, and the per-company build. Tables come back as markdown - read them, don't guess.
4. Immediately write the raw element to em-size/report-bottomup.md, and write em-size/build.csv - one row per company, every field carried verbatim from the report (leave blank only where the report itself is blank):

   rank,company,hq,total_revenue,basis,share_in_market_pct,in_market_revenue,confidence,revenue_source,justification
   1,Co A,NO,402.7,reported,38%,153.0,H,Proff (NO),"Disclosed FY24 revenue; share set by product-line split"
   2,Co B,SE,210.4,estimated,55%,115.7,M,S&P Capital IQ,"Revenue estimated from filings; share from end-market mix"
   ...
   

   basis = reported vs estimated of the total revenue; confidence = the report's confidence on the share in market (the scope share, not a market share). Keep both - they mean different things.
5. Also capture, verbatim, into em-size/headline.txt: the report's stated headline size, its vintage ("2025 or latest available"), its methodology note (e.g. "top-N in-market revenue; no long-tail estimate"), the in-/out-of-scope boundary, any concentration figures (top-2/5/10 shares), and the player count.

Phase 2 - Build the cross-checks (credible research pass)

Construct 2-3 independent sizing approaches to triangulate the headline, following the source rules above. Typical approaches: a top-down (official statistic × a credible share), an installed-base × annual value, and one independent third-party/analyst range (credible only). For each, do the arithmetic from first principles, restate it to the report's in-scope definition, and record it - immediately after the research - in em-size/crosschecks.csv:

method,approach,low,point,high,confidence,scope_note,source
top_down_capex,"Official construction stats × fire-protection share",480,560,640,M,"Restated to Nordic, OEM revenue basis","Eurostat 2024; SSB"
listed_grossup,"Listed groups' segment revenue grossed for tail",500,590,690,M,"In-scope geography only","Company annual reports 2024"
analyst_range,"Independent analyst estimate (scope-adjusted)",430,520,610,L,"Broader-scope figure restated down","<named credible source>"

If a genuine research pass yields nothing credible (only mills), record that fact and present the bottom-up alone - do not invent a cross-check to fill the field.

Phase 3 - Verification (do not skip)

Work from the files.

1. cat em-size/build.csv em-size/headline.txt em-size/crosschecks.csv.
2. Fidelity check (the important one): confirm every figure in build.csv and headline.txt matches the report exactly - same numbers, same confidence stamps, same scope wording. You changed nothing.
3. Build-to-total reconciliation: sum in_market_revenue across companies and compare to the report's stated headline. They should match (bottom-up = sum of in-market revenues). If they differ (e.g. the report adds a long-tail estimate or rounds), show both and explain the difference - never silently adjust either. State the formula: Σ in-market revenue = … vs report headline = ….
4. Cross-check integrity: each cross-check names a credible source, was scope-restated to the report's definition, and uses no mill. Drop any that fails.

Phase 4 - Confidence read

Communicate how much to trust the headline and why, grounded in the report's own stamps - not a vibe. Carry the report's overall confidence/caveat verbatim, then add a transparent coverage summary computed from the per-row stamps (clearly labelled as derived from the report's own data, not new estimation):

• share of in-market revenue resting on reported vs estimated total revenue (basis);
• share of in-market revenue carrying high vs low confidence on the scope share (confidence);
• concentration (how much of the size sits in the top few names - a few large estimated lines can swing it);
• the standing caveats: vintage ("latest available", not one clean year), geography/Nordic emphasis, and "no long-tail" if the report says so. Write em-size/confidence.txt. The point is a reader should see exactly which parts of the number are solid and which are soft.

Phase 5 - Assemble the deliverable (data; the client styles it)

Build the Markdown and JSON from the files; do not re-key a number from memory. Markdown structure:

# Bottom-up market size - <market> (<currency>, <vintage>)
*From the Economic Mind "<market>" bottom-up report (figures carried verbatim). Cross-checks independently
researched from credible sources. AI-assisted - confirm against the report and the cited sources before
relying on it.*

## Headline
- **Market size:** <report headline> (<vintage>)
- **Basis:** <report methodology note, e.g. top-N in-market revenue; no long-tail>
- **Scope:** <in-/out-of-scope boundary, verbatim>
- **Players covered:** N  ·  **Concentration:** top-5 = …% (if stated)
- **Confidence:** <overall, with the one-line why from the confidence read>

## Bottom-up build (per company, from the report)
| Rank | Company | HQ | Total revenue | Basis | Share in market | In-market revenue | Conf. | Justification |
|-----:|---------|----|--------------:|-------|----------------:|------------------:|:-----:|---------------|
| 1 | Co A | NO | 402.7 (reported) | … | 38% | 153.0 | H | Disclosed FY24 … |
*All figures carried verbatim from the Economic Mind report. Basis = reported/estimated revenue;
Conf. = confidence on the share in market.*
Σ in-market revenue = <sum>  ·  report headline = <headline>  (<match / difference explained>)

## Confidence & assumptions
- Overall: <report's confidence/caveat, verbatim>.
- Coverage (computed from the report's own stamps): <X>% of the size rests on reported revenue, <Y>% on
  estimated; <Z>% carries high confidence on the scope share. Top-<k> names = <…>% of the size.
- Key assumptions: <scope-share basis, geography, vintage, no-long-tail>.

## Triangulation (football field)
| Method | Approach | Low | Point | High | Conf. | Source & scope note |
|--------|----------|----:|------:|-----:|:-----:|---------------------|
| Bottom-up (anchor) | EM report build | - | <headline> | - | <conf> | Economic Mind "<market>" report |
| Top-down | … | 480 | 560 | 640 | M | Eurostat 2024 … |
| Listed gross-up | … | 500 | 590 | 690 | M | Annual reports 2024 |
**Converged view:** <range>, with the bottom-up at <headline>. <Does the anchor sit inside the
cross-check range? If it's an outlier, say why - scope, vintage, or tail.>

## Sources & method
- **Bottom-up** - Economic Mind "<market>" report (bottom-up supply-side); per-company revenue providers
  as stated (e.g. Proff, S&P Capital IQ). Carried verbatim; not recomputed.
- **Cross-checks** - <each method's named credible source>; scope-restated to the report's definition.
- **Excluded:** market-research "mills" (unreliable / scope-inconsistent). **Caveats:** <vintage,
  geography, long-tail>.

JSON sidecar (em-size/market-size.json) - machine-readable mirror:

{
  "market": "Nordic fire protection", "currency": "EUR", "vintage": "2025 or latest available",
  "headline": {"size": 590.0, "basis": "top-N in-market revenue; no long-tail",
               "scope": "...", "confidence": "M"},
  "build": [{"rank": 1, "company": "Co A", "hq": "NO", "total_revenue": 402.7, "basis": "reported",
             "share_in_market_pct": 38, "in_market_revenue": 153.0, "confidence": "H",
             "revenue_source": "Proff (NO)", "justification": "..."}],
  "reconciliation": {"sum_in_market": 588.4, "report_headline": 590.0, "note": "rounding"},
  "coverage": {"pct_reported_revenue": 64, "pct_high_conf_share": 58, "top5_pct": 71},
  "football_field": {
    "anchor": {"method": "bottom_up", "point": 590.0, "source": "Economic Mind report"},
    "crosschecks": [{"method": "top_down_capex", "low": 480, "point": 560, "high": 640,
                     "confidence": "M", "scope_note": "...", "source": "Eurostat 2024; SSB"}],
    "converged": {"low": 500, "high": 640}
  }
}

Phase 6 - Deliver

Hand back the Markdown and JSON. When presenting the output files (via present_files where available, e.g. Claude.ai), list the JSON sidecar (em-size/market-size.json) first and the Markdown report last, so the human-readable report is the final, most prominent artifact. In any prose summary, use the figures the deliverable produced; do not re-key, re-round, or introduce a number not in the files, and keep the bottom-up and the cross-checks clearly distinct.

What makes it trustworthy

The bottom-up build is carried verbatim from the Economic Mind report - never recomputed - and the sum is reconciled to the report's own headline in the open. Confidence is reasoned from the report's own reported-vs-estimated and share-confidence stamps, so the reader sees which parts of the number are solid. The football-field cross-checks are independently researched from credible primary, official and industry sources - mills explicitly excluded - and each is scope-restated to the report's definition before it stands next to the anchor. And the whole thing is built from files captured at collection time, so what you read is what the report and the cited sources actually say.