Manufacturing · SAP
Industrial leader cuts unplanned downtime 27% with connected-operations data
27% downtime reduction · $40M supply-chain savings, year one
At a glance
Key metrics
Challenge
The situation
Plant data sat in isolated historians. Global supply planning ran on weekly extracts. A single quality event could take days to trace back through the network.
Approach
How we delivered
- 01 Deployed SAP Datasphere as the harmonized semantic layer over SAP S/4HANA, plant historians, and supplier data.
- 02 Built a connected-operations data product catalog — quality, OEE, supplier risk, energy — each with a named business owner.
- 03 Rolled out SAP Business AI copilots for finance and supply planners on top of the governed layer.
Architecture
Solution architecture
SAP Datasphere federates S/4HANA, plant historians, and supplier data. Semantic models published as data products with SLAs. Business AI copilots grounded on the semantic layer. Azure used for high-volume sensor data where cost profile favored it, federated back into Datasphere.
Outcomes
Measured results
- 27% drop in unplanned downtime across the top-30 plants within 9 months.
- $40M first-year supply-chain savings from better allocation and reduced expedites.
- Quality root-cause trace time reduced from days to hours.
Technology
Tech stack
Platform
- SAP Datasphere
- SAP BTP
- SAP Business AI
Source systems
- SAP S/4HANA
- Plant historians (OSIsoft PI)
- Supplier networks
Hyperscaler
- Microsoft Azure (sensor landing)
“We finally treat plant data like a product, not a report.”
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