Manufacturing Power BI & Fabric Consulting

Yes, Power BI connects to SAP through multiple methods: SAP HANA connector (direct), SAP BW/4HANA connector, SAP Business Warehouse connector, and OData/REST APIs. We design extraction patterns that provide real-time or near-real-time data without impacting SAP performance.

We use Microsoft Fabric Real-Time Intelligence or Azure Event Hubs to ingest IoT data streams from PLCs, SCADA systems, and sensors. Power BI streaming datasets provide real-time factory floor dashboards, while historical data flows into a data lakehouse for trend analysis.

Yes, we build DAX measures that calculate OEE (Availability x Performance x Quality) from production data. The model supports drill-down from plant-level OEE to individual machine, shift, product, and operator dimensions with automatic downtime categorization.

We design a unified data model that normalizes data from different ERPs into a common star schema. Microsoft Fabric data pipelines handle the ETL from SAP, Oracle, Dynamics, and custom systems into a single analytical layer that supports cross-plant comparison and consolidation.

Power BI for manufacturing is the deployment of Microsoft Power BI and Microsoft Fabric in discrete and process manufacturers — automotive, aerospace, food and beverage, pharmaceuticals, industrial, and chemicals. Common workloads: OEE dashboards (Availability × Performance × Quality), supply chain visibility with supplier performance and inventory optimization, quality control (SPC charts, first-pass yield, defect tracking), IoT-based predictive maintenance, product costing and variance analysis, and safety/environmental compliance dashboards. Fabric Real-Time Intelligence enables sub-second updates for factory floor visibility.

Manufacturing Power BI implementation costs typically run $75,000-$250,000 for a single-plant departmental rollout (one ERP integration, one MES) and $500,000-$3,500,000 for global multi-plant enterprise deployments (SAP + Oracle + Dynamics normalization, IoT ingestion, predictive maintenance ML). Microsoft Fabric F64 is the recommended starting capacity; multi-plant global manufacturers with heavy real-time IoT volumes typically scale to F256+. Annual maintenance retainer: $60,000-$300,000 depending on plant count and integration complexity.

OEE (Overall Equipment Effectiveness) is the manufacturing gold-standard metric measuring productive time as a percentage of planned production time: OEE = Availability × Performance × Quality. Power BI OEE dashboards calculate: (1) Availability = actual runtime / planned runtime; (2) Performance = actual output / theoretical output at ideal cycle; (3) Quality = good parts / total parts. World-class OEE is 85%; typical manufacturing is 60%. We build DAX measures that calculate OEE at plant, line, machine, shift, product, and operator granularity with automatic downtime categorization tied to SCADA/PLC signals.

Power BI supply chain analytics is the deployment of Power BI dashboards across the end-to-end supply chain: supplier performance (on-time delivery, quality, capacity), inventory optimization (turns, days of supply, obsolescence risk), demand forecasting (statistical + ML), logistics tracking (transit time, damage rate, cost per unit), and network optimization. Common integrations: SAP ECC/S4, Oracle SCM, Dynamics 365 Supply Chain, JDA/Blue Yonder, Kinaxis, and IoT tracking systems. Advanced deployments include Fabric ML models for demand forecasting and reorder-point optimization.