Capabilities / Data Platforms
Enterprise Data Platforms
Unify ERP, EAM, historian, and OT data to power reliable asset decisions and clean material records.
Astrid Partners architects reference data platforms that integrate SAP PM/MM, plant historians, sensor streams, and maintenance records, giving reliability engineers, planners, and procurement teams a single, trusted source of truth.
From prior engagements
25%+
Duplicate materials eliminated
Average material master deduplication rate, improving MRP accuracy and procurement efficiency.
30 days
Time to governed data products
Time to unlock trusted asset and materials data for maintenance and procurement teams after engagement start.
3–15×
Return on engagement fee
From working capital and procurement savings tied directly to cleaner materials and MRP.
How We Approach This
What makes this work.
The mechanics behind our engagements: what separates a diagnostic that produces a real business case from one that produces a slide deck.
Pre-built asset domain models
Data models for equipment hierarchy, functional location, BOM, and spare parts that compress deployment from months to weeks across plants.
Material master governance that holds
Automated deduplication, classification, and quality scoring. Not a one-time cleanup. Built to keep records clean as new materials enter the system.
Secure OT/IT connectivity
Zero-trust connectivity from shop floor historians and PLCs to enterprise data platforms, with continuous monitoring and no operational disruption.
Decision products, not dashboards
Asset health, work order analytics, and inventory visibility packaged with role-based KPIs, built with maintenance teams, not handed to them.
What We Deliver
The work, scoped
and priced to move.
Each offering below is designed to produce a specific deliverable, not an ongoing program. We scope to outcome, not to time-and-materials.
Platform Strategy & Roadmap
Define the architecture, data products, and operating model needed to connect asset, maintenance, and materials data.
- –Asset data landscape assessment
- –SAP PM/MM and EAM integration architecture
- –Material master governance roadmap
- –Operating model & data ownership plan
Modern Data Foundation
Build ingestion, modeling, and governance pipelines for OT, ERP, and CMMS data with reusable accelerators.
- –Historian and sensor ingestion
- –SAP PM/MM data extraction and modeling
- –Semantic layers for asset and materials
- –Automated cataloging and quality checks
Asset & Materials Data Products
Co-create decision-ready data products with maintenance, reliability, and procurement teams.
- –Equipment health and failure data products
- –BOM and material master clean-up products
- –Spare parts demand and inventory data
- –MRP variable and exception analytics
Platform Operations
Run, optimize, and continuously improve data platforms with dedicated SRE and data quality disciplines.
- –24/7 monitoring and support
- –Material master stewardship workflows
- –Data quality scoring and alerting
- –Lifecycle management and cost governance
How we build it
From assessment to scaled operations across asset domains in 90-day increments.
01
Foundational Assessment
Inventory ERP, EAM, historian, and CMMS data sources; benchmark material master quality; define reference architecture.
02
Pilot & Productization
Stand up core platform, deliver first asset health and materials data products, and establish governance intake.
03
Scale & Operate
Expand to additional plants and domains, automate material master deduplication, and transition to co-managed operations.
In Practice
Replaced fragmented SAP MM and historian feeds with a unified data mesh spanning 14 plants, eliminating 28% of duplicate material records and giving maintenance teams real-time asset health visibility.
Outcome
Single source of truth across 14 plants in 4 months.
Find out what your data can already tell you. Start by connecting it.
A diagnostic engagement runs 6–8 weeks and returns a prioritized roadmap with a dollar value on every initiative. If we can't see a clear path to 10× return on our fee, we won't take the work.