The logical layer that lets a half-migrated roll-up still answer one question consistently — model once, federate the data, generate insights anyway.
Legrand can't wait for every plant and newly-acquired business to migrate to SAP before it gets answers. The fix isn't one warehouse — it's a shared ontology (so everyone means the same thing) over a data mesh (each family owns its data as a product), with a semantic layer that federates them. Insights generate today; they just carry a confidence flag where a family isn't on SAP yet.
Ten classes everything maps to. The Site / Plant is the keystone: it's where family, leader, entity and geography reconcile.
82% of revenue is already site-grain actual; the rest is read in place from legacy site/acquired systems and reconciled — no big-bang migration required.
Every metric has one definition and a grain. The layer federates it across on-SAP and legacy domains, flagging where a value is allocated.
| Metric | Definition | Grain | How it federates across segments |
|---|---|---|---|
| Revenue | Σ recognized revenue | site · order | actuals where on SAP; allocated from area where not |
| Adjusted operating profit | revenue − COGS − opex (+ add-backs) | family · entity | entity P&L normalized to one chart of accounts |
| Software & Services revenue | annuity-like recurring revenue | contract | from SAP SD / order systems across all families |
| Software & Services mix | software & services ÷ revenue | family | federated — same formula, many sources |
| DSO | AR ÷ revenue × 365 | entity · site | project / acquired entities measured at area grain, flagged |
| Gross margin | (revenue − COGS) ÷ revenue | order · family | mapped via canonical cost categories |
| Subscription retention | expansion − attrition on base | customer / channel | resolved across duplicate channel records |
Entity resolution matches legacy site / brand / acquired-company codes to one canonical node — so the acquired-brand data lines up with everything else.
Query reads each family's data product in place; the semantic layer maps native SAP / order-system fields to canonical metrics.
Where a family reports at area level, allocation disaggregates to site on learned drivers and marks it an estimate with a confidence band.
Allocated parts must tie back to the source total; anomalies and duplicate channel records & suppliers across families are surfaced.
This is not theoretical — it's how this cockpit already works. The Story, Briefing and 360 views read the same governed metrics over on-SAP and legacy families alike; 82% of the numbers are site-grain actuals and the balance is SAP-allocated and labelled. As each family migrates to SAP, its data product's grain rises and estimates flip to actuals — the mesh closes itself.