The operational twin — for one factory / logistics cluster: its condition-monitored machines, fleet health, quality & compliance audits, maintenance posture, aftermarket contracts and field-service crew, with the data grain that says how bankable its P&L is.
7 of 15 clusters report at true site-grain actuals — leaving SEK 47.1 bn of revenue on softer grain. Convert the 8 estimated clusters to actuals to make the operational P&L bankable, then mine the healthy base to grow the aftermarket & services book.
5 of 6 headline metrics improving vs prior · still off target: Factory Uptime / OEE (weighted) 84.0% vs 90.0%, Customer / Distributor NPS 55 vs 60, Aftermarket & Services Revenue SEK 33.5 bn vs SEK 36.0 bn
SEK 47.1 bn of revenue sits on SAP-allocated or region-only grain — diligence discounts what it can't verify.
SEK 30.4 bn of aftermarket & services revenue sits on a fleet of 12,500 condition-monitored machines — the warmest expansion surface SKF has.
This is the view the manufacturing and maintenance teams act on. Each cluster is a living asset — pick one and see its machines by type, what's healthy vs degraded vs down, its next quality / compliance audit, the machines below the condition-monitoring baseline, and its aftermarket contracts. The SKF thread runs through it: the data grain tells you how much of this site's number you can bank. It's the single-cluster drill-down for Org Roll-up 360.
Machines · health · quality · maintenance · aftermarket · crew — plus the data grain and a next best action.
Maintenance drift tracks data-grain: low-coverage / off-ledger sites carry more machines past their service window.
Routed to the open non-conformances above; condition-monitoring telemetry opens the work order, the maintenance team closes it.
1,752 healthy machines, clean audits. Point the aftermarket flywheel here: attach condition monitoring & REP contracts onto the installed base.