Check that segments add up

Paste a list of segments with the revenue the filing reports, or a response of the numi API, and see whether each breakdown adds up to the total. Nothing leaves your browser.

[
  {
    "name": "MSFT",
    "total": 331839000000,
    "segments": [
      { "name": "Productivity and Business Processes", "revenue": 139996000000, "axis": "business" },
      { "name": "Intelligent Cloud", "revenue": 137791000000, "axis": "business" },
      { "name": "More Personal Computing", "revenue": 54052000000, "axis": "business" },
      { "name": "Server Products and Cloud Services", "revenue": 129425000000, "axis": "product" },
      { "name": "Microsoft 365 Commercial Products and Cloud Services", "revenue": 101997000000, "axis": "product" },
      { "name": "XBOX", "revenue": 21790000000, "axis": "product" },
      { "name": "LinkedIn Corporation", "revenue": 19817000000, "axis": "product" },
      { "name": "Windows and Devices", "revenue": 17084000000, "axis": "product" },
      { "name": "Search Advertising", "revenue": 15176000000, "axis": "product" },
      { "name": "Microsoft 365 Consumer Products and Cloud Services", "revenue": 9175000000, "axis": "product" },
      { "name": "Dynamics Products and Cloud Services", "revenue": 9006000000, "axis": "product" },
      { "name": "Enterprise and Partner Services", "revenue": 8260000000, "axis": "product" },
      { "name": "Other Products and Services", "revenue": 109000000, "axis": "product" },
      { "name": "United States", "revenue": 170794000000, "axis": "geography" },
      { "name": "Non-US", "revenue": 161045000000, "axis": "geography" }
    ]
  },
  {
    "name": "MSFT without axes",
    "total": 331839000000,
    "segments": [
      { "name": "Productivity and Business Processes", "revenue": 139996000000 },
      { "name": "Intelligent Cloud", "revenue": 137791000000 },
      { "name": "More Personal Computing", "revenue": 54052000000 },
      { "name": "Server Products and Cloud Services", "revenue": 129425000000 },
      { "name": "Microsoft 365 Commercial Products and Cloud Services", "revenue": 101997000000 },
      { "name": "XBOX", "revenue": 21790000000 },
      { "name": "LinkedIn Corporation", "revenue": 19817000000 },
      { "name": "Windows and Devices", "revenue": 17084000000 },
      { "name": "Search Advertising", "revenue": 15176000000 },
      { "name": "Microsoft 365 Consumer Products and Cloud Services", "revenue": 9175000000 },
      { "name": "Dynamics Products and Cloud Services", "revenue": 9006000000 },
      { "name": "Enterprise and Partner Services", "revenue": 8260000000 },
      { "name": "Other Products and Services", "revenue": 109000000 },
      { "name": "United States", "revenue": 170794000000 },
      { "name": "Non-US", "revenue": 161045000000 }
    ]
  }
]

A result of mixed_axes_likely means the rows come to more than the reported revenue, which is what rows from more than one breakdown counted together look like.

How segments are reconciled, in the docs.

The checker on GitHub, under the MIT licence.

On the command line: npx @numi-sh/reconcile segments.json