LLegrandExecutive Cockpit

Data platform — use case portfolio

Nine decisions the business cannot make reliably today, each sized from the governed model and traced to the systems that must feed it.

Legrand SA · FY2025 (31 Dec 2025, audited)
The global specialist in electrical & digital building infrastructures
39,600 employees · 50+ manufacturing & logistics sites · 90 countries
Solution · Legrand data platform

Every plant, part and counterparty, resolved to one governed record

9
Decisions sized
computed, not asserted
5
Deployable now
on data already modelled
4
Need a new feed
seeded as modelled rows
12
Source systems
2 stale or region-only
01The nine use cases

Nine decisions — pick one

Grouped by the function accountable for it. Each opens on its numbers, then the ontology it resolves against, the models that predict on it, the agents that act, and what to ask.

The nine · pick one
USE CASE 01💼 Finance & M&ALive now

M&A data onboarding

4 acquired clusters still report Region-only at 55–62% coverage against 98% at mature plants — and ~7 deals a year keep arriving.

€1.5 bn
of revenue invisible at plant level
Also servesOperationsSupply ChainGroup Control
M&A data onboarding 360Live
CO
Cleveland, OH
ACQUIRED 2025
Region
North & Central America
Sites
2
Recording grain
Region-only
Brand
Avtron · Kratos · ZPE
Golden record
SITE-1005 · 62%
Data coverage62%
Revenue not rolling up
€600 M
36 pts below benchmark
Coverage vs benchmark
62%
98% at mature plants
Onboarding progress
70
of 100 · group average
Revenue — trailing 12 months€600 M / yr
Monthly shape modelled from the group series
Where the data stops
Reported region-only55%
Plant-level detail34%
Reconciled to group11%
Onboarding workstreams — completion
SAP S/4 / ERP60%
Brand & Customer Master (MDM)55%
Order / Quote / CPQ Integration62%
Plant / PLM / Industry-4.058%
Next best actionAI · High · 95%

Exit region-only recording on a dated plan

€600 M does not reach plant level at 62% coverage, against 98% at mature plants. Every period it stays here, group OTIF and stock exclude it.

Map the ERP to the group model88%
90-day plant-level SLA76%
Hold revenue out of OTIF61%
Open the integration plan →
Recent activity — unified timeline
2025Revenue consolidated into the group P&L· SAP S/4
+30 daysPlants remained on the acquired company's ERP· legacy ERP
+90 daysRegion-only recording set as the interim grain· MDM
nowCoverage 62% — still excluded from OTIF and stock· governed model
Invisible revenue
€1.5 bn
4 clusters, region-only
Coverage gap
55–62%
vs 98% at mature plants
Onboarding progress
70%
2 under 60% · 2 high blockers
Deals still coming
9
€550 M in the live pipeline
Data coverage by acquired cluster
Cleveland, OH· acquired 202562% · €600 M
Middle East & Africa60% · €350 M
São Paulo, Brazil· acquired 2026at risk55% · €335 M
Australia / SE Asia· acquired 2025at risk58% · €195 M
98% coverage at mature plants
How a cluster goes dark
Deal closeRevenue consolidates into the group P&L· SAP S/4
+30 daysPlants still on the acquired company's ERP· legacy ERP
+90 daysRegion-only recording set as the interim grain· MDM
+1 yearStill region-only — OTIF and stock exclude it· governed model
Next best actionAI · High · 91%

Make plant-level onboarding a condition of deal close

Four clusters carrying €1.5 bn report region-only. At roughly seven deals a year this compounds — onboarding is a standing capability, not a project.

Data workstream owned pre-close91%
90-day plant-level SLA78%
Hold region-only revenue out of OTIF64%
Open M&A Integration 360
So what

Mature plants report at 98% coverage. Until these four match, group OTIF, yield and stock all exclude €1.5 bn of revenue — the fastest-growing part of the book.

Machine learning · what predicts here
Plant ↔ entity matcherEntity matchingProduction

Link acquired plant records to group legal entities

F10.94
Top features
Legal name similarity31%
Address / geo24%
Tax / VAT id19%
Brand overlap14%
Product overlap12%
Coverage-to-target forecastRegressionPilot

Days until a cluster reaches 95% plant-level coverage

MAE11 days
Top features
Workstream completion34%
Open blockers27%
Source ERP complexity22%
Integration headcount17%
Feeds from · SAP S/4 · acquired-company ERPs · MDM
02The hard part

First, resolve the record
— or the 360 is a lie

The same counterparty is coded differently in every system that touches it. Until those records resolve to one governed identity, every channel report, credit limit and DSO figure inherits the ambiguity.

Same customer · 3 fragmented records
SAPDistributors & wholesalers (billed)100%
SalesforceRexel / Sonepar / Graybar group96%
DistributorWholesaler EDI accounts92%

Different keys for the same counterparty — no shared identifier. Spend, credit and terms are split, and the real relationship never appears on one screen.

→
Match &
resolution engine
Entity matchSurvivorshipTerms reconcileLineage capture
One golden record
ED
Electrical distributors & wholesalers
GOLD-CUST-0001
100% match
Master source
SAP S/4survivorship
Revenue
€5.2 bnresolved
Records merged
3 → 1governed
Lineage
every field sourcedgoverned
So what

Landed cost, service level and credit exposure are only trustworthy on a resolved entity graph. Skip it and the 360 is a spreadsheet that disagrees with itself — 10 of 15 records are unmastered variants and the weakest match is 86%.

03What it unifies

Every source, one
governed profile

The platform reads the systems Legrand already runs — as they are, no rebuild — and resolves them into one profile per entity that every use case reads from.

The data you already have
🗄SAP S/4 (core ERP)
☁Salesforce CRM & CPQ
🔌Acquired-company ERPs
🏭MES & line telemetry
🧬PLM & product master
🔗Distributor EDI / POS
🛃Global trade management
📡Eliot / Netatmo cloud
Resolve &
unify
→
One governed profile
One governed profile per plant, part and counterparty
Golden recordLanded costLead timeChannel positionInstalled baseFootprintAsset healthLineageNext best action
04Why it matters

A real 360 — not a
report or a stale extract

Most “360s” assume the hard problems are already solved. On a multi-brand group absorbing seven acquisitions a year, they are not.

CapabilityGoverned 360Point toolsWarehouse + BI
Entity resolution & golden record✓Deterministic + survivorship—Exact keys only✕Assumes clean keys
Acquired-company onboarding✓Plant level, day one—Manual mapping✕Region-only for years
Landed cost & duty✓Per lane, per HS code—Ex-works only✕Not modelled
Channel sell-through✓POS reconciled to sell-in—Where EDI exists✕Sell-in only
Live lineage on every field✓Sourced & timestamped—Partial, per tool—Batch, stale
Agentic action & write-back✓Ask & act✕Read-only dashboards✕Reports only
05The payoff

See the business
— and act on it

A resolved, predictive, governed platform changes what each function can decide.

1

Resolved model — plants, parts and counterparties deduplicated across every source system

86–100%

Match confidence carried on every record, with the weakest surfaced rather than hidden

Live

Coverage, duty, discount, channel stock and asset risk on every entity that matters

5 of 9

Use cases deployable on data already modelled — no new feed required to start

On the data behind this page

5 of 9 use cases compute from sources the cockpit already modelled. The other 4 — trade lanes, distributor sell-through, connected installed base and product footprint — required new tables, seeded here as modelled rows so the decision can be sized and designed; they are not live system feeds today. Model metrics, agent autonomy levels and next-best-action confidences describe the intended design, not a running system.