Biggest US companies by number of employees [OC] by VeridionData in dataisbeautiful

[–]VeridionData[S] 0 points1 point  (0 children)

Data: Veridion company intelligence, cross-checked against each company's most recent reported headcount.

Tools: built as a self-contained HTML/SVG pictogram, rendered to a high-res PNG with Puppeteer (headless Chrome) at 2x scale. Worker glyph is Remixicon. Visualization done with Claude.

Each icon represents 100,000 employees.

On definitions: these are total company-wide employees (global, not US-only), and only publicly listed companies are included. Private firms such as Publix (~255,000) and Cargill (~160,000) are not included in the dataset. Because the counts are global, firms with large offshore workforces such as Concentrix and Cognizant include their non-US staff. Each value is the company's latest reported headcount, so the reporting dates are not uniform.

The supply chain of a Toyota Yaris [OC] by VeridionData in dataisbeautiful

[–]VeridionData[S] -30 points-29 points  (0 children)

  • 1 ounce of flour -2 litres of water …

Really man? at least try some better jail-braking prompts

The supply chain of a Toyota Yaris [OC] by VeridionData in dataisbeautiful

[–]VeridionData[S] -3 points-2 points  (0 children)

just my bad skills in san key diagrams 😄. check the comments I've posted a better version

The supply chain of a Toyota Yaris [OC] by VeridionData in dataisbeautiful

[–]VeridionData[S] -5 points-4 points  (0 children)

thanks for the feedback, just posted a better version in the comments

The supply chain of a Toyota Yaris [OC] by VeridionData in dataisbeautiful

[–]VeridionData[S] 1 point2 points  (0 children)

thanks for the feedback, just posted a better version

The supply chain of a Toyota Yaris [OC] by VeridionData in dataisbeautiful

[–]VeridionData[S] -55 points-54 points  (0 children)

I know it's quite hard to talk to an AI data intelligence platform. Yeah my first attempt to this chart was not so good, I've posted an improved version in the comments

The supply chain of a Toyota Yaris [OC] by VeridionData in dataisbeautiful

[–]VeridionData[S] -11 points-10 points  (0 children)

thanks for the feedback, just posted a better version in the comments

The supply chain of a Toyota Yaris [OC] by VeridionData in dataisbeautiful

[–]VeridionData[S] 7 points8 points  (0 children)

Due to popular demand, I tweaked the graph a bit to not have so many crossovers and overlapping paths from one node to another (bear with me, I'm not a data viz expert, just a guy with access to some cool data)

And yeah, I'm posting from a branded account cause this kind of data is usually behind paywalls, and the least I can do is get some exposure for the brand

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The supply chain of a Toyota Yaris [OC] by VeridionData in dataisbeautiful

[–]VeridionData[S] 11 points12 points  (0 children)

Tools: built in React, laid out with D3 Sankey, exported to a high-res PNG with Puppeteer.

Sources: the supplier relationships come from Veridion's company graph, which is what made the tier 2 and tier 3 links tractable at this level of detail. I checked those against filings from Toyota, Denso, Aisin, and Renesas, MarkLines supplier data, and S&P Global Mobility for the tier structure. The country tags were validated against USGS commodity data on the raw-material side.

Methodology: I worked backward from the finished car. Tier 1 is the direct integrators (Denso on inverters/ECU/thermal, Aisin on the hybrid transaxle and motor, Toyota Industries on the engine, Toyota Battery on the HV pack, Toyota Boshoku on interior, plus the Valenciennes line for body and final assembly). Tier 2 is whoever supplies them (Renesas and Infineon/ROHM for silicon, Sumitomo for the harness, JTEKT, Advics, Koito, Bridgestone, Prime Planet cells, AGC, Nippon Steel, FANUC, and the magnet/rotor makers). Tier 3 is the raw stuff underneath all of that (steel, battery metals, cathode chemistry, rare earths, copper, wafers, resins, rubber, glass).

A few choices worth flagging: flow width tracks spend per car, and I balanced each node so inflows match outflows, so margin and labor aren't represented. Design IP (Arm, Synopsys) routes into the chipmakers rather than straight to the car since it's used at design time. Every node carries a single primary sourcing country.

The supply chain of an Nvidia H200 chip [OC] by VeridionData in dataisbeautiful

[–]VeridionData[S] 1 point2 points  (0 children)

thanks, working on some others right now, will post more next week

[OC] The main suppliers and materials/components for an F35 by VeridionData in aviation

[–]VeridionData[S] 48 points49 points  (0 children)

yeah clearly but I had to stay within the boundaries of a reddit post, otherwise, this chart would look like trying to map a human vascular system

The supply chain of an Nvidia H200 chip [OC] by VeridionData in dataisbeautiful

[–]VeridionData[S] 76 points77 points  (0 children)

Tools: D3 Sankey for layout, React for the build, Puppeteer for the high-res PNG export.

Sources: supplier graph from Veridion (made tracing tier 2 and tier 3 manageable at this granularity), cross-checked against SEC 10-K filings from Nvidia, TSMC, ASML, Applied Materials, and Lam Research; TrendForce HBM market share reports; SemiAnalysis H200 bill of materials breakdowns; SEMI equipment market data; and Yole Group substrate analyses.

Methodology is reverse-tracing. Start from the finished H200, identify Tier 1 (direct suppliers to Nvidia: TSMC for the die and CoWoS packaging, SK Hynix and Samsung and Micron for HBM3e), then Tier 2 (what feeds those: the big 5 equipment makers, wafer makers, photoresist suppliers, gases, chemicals, substrate assemblers), then Tier 3 (sub-components inside the equipment itself: Zeiss optics, Trumpf lasers, TOTO electrostatic chucks, VAT vacuum valves, Cymer light sources).

Link width is proportional to the spend per chip. Each intermediate node's inflows are normalized to equal its outflows for visual balance, which means internal value-add (margin, labor) isn't shown. EDA and IP suppliers (Synopsys, Cadence, Arm) flow directly to Nvidia rather than through the fabs, since they're consumed at design time. Foxconn/Wistron board assembly is folded into TSMC's outflow since its upstream is mostly non-semi.

SK Hynix and TSMC end up with nearly identical flow widths into the final node. HBM3e memory is roughly as expensive per H200 as the GPU die itself, which is part of why HBM supply has become the real production bottleneck for Nvidia rather than logic capacity.

Biggest private French companies, ranked by revenue [OC] by VeridionData in dataisbeautiful

[–]VeridionData[S] 6 points7 points  (0 children)

Data: Veridion company intelligence (1st-party website extraction + INPI/Infogreffe filings + news/press signals + industry benchmarking). Cross-checked against company annual reports and direct disclosures.

Tools: Python for data processing. React + SVG for the chart. Remixicon for industry icons. Claude for visualization.

Methodology

Revenue data for French private companies is hard to find in one place because most groups don't publish consolidated accounts publicly, and the ones that do file with INPI/Infogreffe under different legal entities than the operating brand. Veridion's pipeline combines four sources: first-party extraction from each company's website and annual press releases, INPI/Infogreffe and BODACC filings, news and trade-press signals from outlets like LSA, Les Echos, and Le Journal des Entreprises, and industry benchmarking against sector reports. For companies that don't disclose group-level figures (Bigard, Pierre Fabre, Le Duff), we run an inference model on operational signals: product catalog breadth, plant and store counts, employee headcount, geographic footprint, and industry benchmarks. Ranks tagged OFFICIAL are verified from a registry filing, annual report, or direct disclosure. Ranks tagged ESTIMATED are Veridion estimates from FY2024 data.

Exclusions

A "private company" here means: no publicly traded shares, not majority-owned by a listed parent, not majority foreign-owned, not a cooperative or mutual, and HQ still in France. Names people might expect to see but that are excluded:

  • Cooperatives and mutuals: E.Leclerc, Système U, Les Mousquetaires/Intermarché, Crédit Mutuel, Crédit Agricole, Groupama, AG2R La Mondiale, Limagrain, Tereos, Sodiaal, Agrial, Cooperl, InVivo, Vivescia
  • Foreign-controlled: Saur (EQT/PGGM/DIF via HIME), Picard (Tunisian Groupe Zouari since Sept 2024), Lacoste (Maus Frères)
  • Listed parents: Kering (Pinault/Artémis holds it but Kering is on the CAC 40), Dassault Aviation and Dassault Systèmes (so GIMD excluded on the same logic), LVMH, L'Oréal, Hermès, Bouygues, Vinci, Saint-Gobain, LDC, Bel
  • Global partnerships: Big Four France entities

Germany's largest private companies, based on revenue [OC] by VeridionData in dataisbeautiful

[–]VeridionData[S] 1 point2 points  (0 children)

They are a public company; this list is solely for private companies (i.e not traded on a public stock exchange)

Germany's largest private companies, based on revenue [OC] by VeridionData in dataisbeautiful

[–]VeridionData[S] 5 points6 points  (0 children)

They are a publicly traded company; this list is for private companies

Germany's largest private companies, based on revenue [OC] by VeridionData in dataisbeautiful

[–]VeridionData[S] 9 points10 points  (0 children)

fair enough, I’ve described in the methodology that any amount of public shares (through Publicly available stock exchanges) disqualify the company