95% Faster Reporting of Downtime at Multi-Plant Manufacturer using Microsoft Fabric

Client Overview

A multi-plant manufacturer operating across North America needed faster, trustworthy visibility into equipment downtime and incidents. The client lacked real-time visibility into Asset Performance Intelligence, leaving them unable to predict equipment failures or standardize downtime tracking across North American plants.

But, vital equipment health data was scattered across disconnected spreadsheets and legacy software, forcing teams to waste hours chasing numbers instead of fixing floor issues.
 

Project Summary

Ray Business Technologies unified incident and downtime data in Microsoft Fabric (OneLake) and delivered governed semantic models, role-based Power BI dashboards and a conversational Copilot layer. Leaders can now ask questions in plain language and get instant, decision-ready answers.
 

Eliminating Data Silos and High-Cost Inefficiencies

• Fragmented logs across CMMS/EAM, MES, and spreadsheets with inconsistent definitions
• Slow reporting cycles and manual reconciliations that delayed action
• Limited self-service, heavy reliance on IT report queues
• Low confidence in KPIs like downtime, availability, MTBF and incident rate

The Solution: Implemented Technical ROI of Microsoft Fabric

Ray Business Technologies replaced fragmented legacy workflows with a unified AI-driven data ecosystem. By leveraging the Microsoft Fabric architecture, we delivered a platform where technical efficiency translates directly into operational savings:

 

Unified Data Foundation (OneLake & Data Factory)

• Centralized Source of Truth: We ingested disparate incident and downtime tables from CMMS/EAM and MES into a single OneLake environment, eliminating the "data tax" caused by siloed systems.
• Zero-Maintenance Ingestion: By utilizing Azure Data Factory for automated, scheduled loads, we reduced manual data handling, leading to a 90% reduction in reconciliation errors.

Business-Ready Semantics (The Metric Engine)

• Standardized Hierarchies: We developed a governed semantic layer that standardizes definitions across Plant → Line → Machine. This ensures 100% metric alignment, meaning a "downtime event" is defined identically in every facility.
• Drill-Down Granularity: Curated Power BI models now allow for instant variance analysis by shift, product, and cause code, transforming raw data into actionable root-cause insights.

Conversational Analytics (Power BI Copilot)

• Democratized Intelligence: We enabled Power BI Copilot, allowing floor managers and executives to bypass IT queues and ask questions in plain language.
• Self-Service ROI: This "Ask-the-Data" capability reduced ad-hoc BI ticket volume by 60–80%, freeing IT resources for higher-value engineering tasks.

Governance & Secure Scale

• Role-Based Access Control (RBAC): Implemented enterprise-grade security and lineage tracking to ensure sensitive production data is only accessible to authorized personnel.
• Automated Refresh Policies: Optimized data refresh cycles to move the plant toward near real-time visibility, reducing report preparation time from 6 hours to less than 1 minute.

 

Hard-Dollar Savings & Workforce Optimization

• Labor Recovery: Report preparation time crashed from 6 hours to less than 1 minute (95% faster).
• Overtime Control: Real-time visibility led to a 10–15% reduction in overtime costs.
• IT Efficiency: Ad-hoc BI ticket volume dropped by 60–80%.
• Rapid Payback: Full ROI achieved within a 3–6 month window.

 

Microsoft Fabric Technical Component	Operational/Financial Outcome	Metric of Success
OneLake & Data Factory: Unified ingestion of CMMS, MES and spreadsheet data.	Elimination of "Data Silos": Provides a single source of truth, ending manual data reconciliation.	90% Reduction in reconciliation errors.
Governed Semantic Layer: Standardized metric definitions for plant, line and machine analysis.	Process Optimization: Enables root-cause analysis of unplanned stops and scrap.	20% Fewer unplanned stops.
Power BI Copilot & Q&A: Natural language conversational insights layer.	Labor Efficiency: Drastic reduction in time spent by staff on manual report preparation.	95% Time Saved (from 6 hrs to <1 min).
DirectLake Connectivity: High-performance analytics without data movement or duplication.	Cost Containment: Real-time visibility allows for immediate action against production variances.	10–15% Reduction in overtime costs.
Self-Service Analytics: Role-based dashboards with drill-down views by cause code.	IT Resource Optimization: Shifts the burden of ad-hoc reporting from IT back to the business users.	60–80% Lower BI support ticket volume.

 

The Roadmap to Industry 4.0 by achieving Operational Excellence

With a clean semantic layer and conversational analytics, the manufacturer now runs a continuous improvement loop: weekly KPI reviews, targeted actions against the top downtime causes, and monthly value checkpoints. Next steps include incremental refresh for near real- time views, predictive maintenance models, and expanding the blueprint to quality, energy and procurement turning insights into sustained operational gains.
 

Metric Category	Key Performance Indicator (KPI)	Impact Achievement
Operational Efficiency	Unplanned Stops	20% Reduction
Equipment Reliability	Mean Time Between Failures (MTBF)	10–15% Increase
Maintenance Speed	Mean Time to Repair (MTTR)	15–25% Faster
Production Velocity	Line Cycle Time	5–10% Reduction
Quality & Waste	Scrap from Repeat Incidents	8–12% Reduction
Supply Chain	Freight Spend (Expedited Shipping)	20–30% Savings

About Ray Business Technologies

Ray Business Technologies is a Global Information Technology (IT) Services and Solutions company. We are a CMMI Level 3 company, providing cutting-edge IT Solutions to Enterprises worldwide, enabling them to utilize available resources effectively and manage the operations. Our excellent team of Technology Professionals work with enterprise clients in North America, Latin America, Australia, Europe, Middle East and Asia.

www.raybiztech.com