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Methodology: Hardware Operating Metrics

What these figures are

The Operating Metrics card on a hardware maker’s stock page shows the operating statistics the company reports in its own quarterly earnings release — the SEC Form 8-K exhibit filed alongside the results. These are the numbers systems, networking and storage vendors use to describe demand (orders, backlog), the AI-driven part of the business, pricing and volume, and profitability. Oxford Ledge reads them directly from the as-filed exhibit and normalizes the labels so you can compare a company to itself over time.

They are an Oxford Ledge Signal: our reading of a public filing, not a re-audit of the company’s books and not a licensed data-vendor feed. Every value on the card carries its filing as-of date and links back to the SEC source.

The metrics, in plain English

MetricWhat it measures
AI revenueRevenue from AI infrastructure specifically — the dominant swing factor in the sector. Read with gross margin, since AI systems can dilute margins.
Orders, backlog & RPODemand booked but not yet delivered — the forward visibility into revenue. RPO is the GAAP remaining-performance-obligation version.
Book-to-billNew orders divided by revenue billed — above 1.0 means backlog is building.
Gross marginProfit on hardware sales as a percentage of revenue.
Exabytes shipped & storage ASPFor storage vendors: the capacity shipped (volume) and price per terabyte (pricing). Revenue is roughly capacity times price.

Why systems, networking and storage are compared separately

“Hardware” spans very different businesses that report different metrics on different units. A server maker leads with AI revenue and orders; a storage vendor reports exabytes shipped and price per terabyte; a networking company has its own measures. Pooling them into one ranking would be meaningless. So the peer table is split by subcohort (Systems, Networking, Storage), and you pick one. Each subcohort is its own comparable series, and a metric a subcohort does not report simply does not appear as a column for it; a blank cell inside a subcohort is an honest coverage gap.

How we read and normalize it

For each company we fetch the most recent quarterly earnings 8-K exhibit from SEC EDGAR, locate the operating table, and read each value verbatim from the reported column — never a prior-year or year-to-date column standing in for the quarter. We keep storage capacity in exabytes and pricing in dollars per terabyte as reported rather than converting between them, and we show consolidated figures — a single business segment’s revenue is not shown as the company total.

The reading is checked against a hand-verified golden set for each company before any figure is allowed to publish; a value whose scope or unit the extractor cannot confidently determine is withheld rather than shown.

What we deliberately do not do

Freshness

The stock page is cached at the edge, so a brand-new filing’s figures can lag up to a day on the cached page. Each value is stamped with the filing it came from, so the as-of date always tells you exactly how current the number is.