Expanding Global Inventory & Supply Chain Planning Analytics with an Enterprise Data Platform
Extended the enterprise data warehouse and analytics platform to deliver unified visibility across Inventory Management, Supply Chain Planning, Demand, and Financial Reporting Groupings across global operations.
5
Regions integrated through structured discovery and analytics requirements
1
Centralized analytics platform extended for global inventory and supply chain planning
1
Governed Power BI analytics foundation supporting standardized KPIs and self-service insights
Executive Summary
The client faced challenges managing inventory and supply chain planning information across multiple systems, regional processes, and varying business definitions. Inconsistent inventory and planning metrics, manual KPI calculations, limited integration between inventory and sales information, and difficulty reproducing historical inventory valuations made it challenging to establish a consistent global view.
Building on the enterprise data warehouse and analytics foundation established in Phase 1, DiLytics implemented Phase 2 to extend the centralized analytics platform across Inventory Management, Supply Chain Planning, and Financial Reporting Groupings.
The solution integrated SAP S/4HANA, SAP IBP, regional files, and financial grouping data into the centralized repository, established governed data and Power BI semantic models, standardized regional KPI definitions, and enabled historical inventory and forecast analysis.
The solution established a unified view of inventory, demand, supply planning, and financial groupings while extending the enterprise analytics foundation for future global analytics modernization.
The client faced fragmented inventory and supply chain data across multiple systems and regions, resulting in inconsistent KPIs, manual reporting, and limited global visibility.
DiLytics extended the Phase 1 enterprise data platform to integrate inventory, demand, supply planning, and financial data. The solution standardized KPIs, enabled governed Power BI analytics, and created a unified view for global decision-making.
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Client Overview
The client is a leading medical device company specializing in minimally invasive neuroendovascular technologies used in the treatment of neurovascular disorders. The company operates globally across North America, Europe, Asia-Pacific, China, and Latin America, with business functions spanning sales, marketing, finance, supply chain, manufacturing, and regulatory operations.
- Industry: Medical Devices & Healthcare Technology
- Location: Global Operations
- Focus Areas: Inventory Management, Supply Chain Planning, Demand & Forecast Analytics
- Market Position: Recognized Leader in Medical Device Solutions
Managing Fragmented Inventory & Supply Chain Data Across Global Operations
Inventory and supply planning information was distributed across multiple systems and regional processes, creating inconsistent metrics, manual calculations, limited integration between inventory and sales information, and challenges in reproducing historical inventory valuations.
Fragmented Inventory & Planning Data
Fragmented Inventory & Planning Data
Inconsistent Regional Metrics
Inconsistent Regional Metrics
Manual KPI & Reconciliation Processes
Manual KPI & Reconciliation Processes
Limited Cross-Functional Visibility
Limited Cross-Functional Visibility
Managing Fragmented Inventory & Supply Chain Data Across Global Operations
Fragmented Inventory & Planning Data
Fragmented Inventory & Planning Data
Inconsistent Regional Metrics
Inconsistent Regional Metrics
Manual KPI & Reconciliation Processes
Manual KPI & Reconciliation Processes
Limited Cross-Functional Visibility
Limited Cross-Functional Visibility
Enabling Unified Inventory & Supply Chain Planning Analytics
Building on the enterprise data warehouse and analytics foundation established in Phase 1, DiLytics designed Phase 2 to extend the centralized analytics platform across Inventory Management, Supply Chain Planning, and Financial Reporting Groupings.
The solution leveraged shared dimensions and the existing governed Power BI architecture to create a unified view of inventory, demand, supply, and financial groupings across global operations.
- Conducted structured discovery sessions with Supply Chain, Inventory, Finance, and regional stakeholders across five regions.
- Defined business requirements, KPIs, measures, calculations, and regional variations for Phase 2.
- Extended the Phase 1 enterprise data warehouse and conformed dimensional model to support inventory and supply chain analytics.
- Integrated SAP S/4HANA, SAP IBP, regional flat files, and FCCS/Stravis grouping data into the centralized repository.
- Established governed data models and Power BI semantic models for Inventory and Supply Chain Planning.
- Standardized inventory, forecasting, supply planning, and financial reporting definitions across regions.
- Implemented historical snapshot capabilities for inventory cost, FX, and forecast information.
- Established security and governed access mechanisms aligned with business confidentiality requirements.
- Performed testing, user validation, training, and deployment activities.
- Extended the scalable analytics foundation for future enterprise-wide subject areas.
Phase 2 delivered analytics capabilities across the following business areas:
- Inventory Management Analytics: Visibility into inventory balances, statuses, quantities, values, movements, and inventory positions across global operations.
- Inventory Valuation & Aging Analytics: Analysis of inventory using standard, moving-average, and transfer-price costing, together with aging, shelf-life, and expiration insights.
- Inventory Accuracy & Field Inventory Analytics: Support for cycle-count accuracy, consignment, trunk, clinical-representative inventory, and Schedule A/PAR compliance monitoring.
- Demand & Forecast Analytics: Visibility into demand forecasts, forecast accuracy, forecast bias, and Forecast Value-Add using SAP IBP data.
- Supply Planning & Inventory Health Analytics: Analysis of rolling supply plans, safety stock, Months on Hand, inventory health, plan-versus-actual variance, and backorders.
- Financial Reporting Groupings: Standardized FCCS and Stravis financial groupings based on Cost Center and GL Account combinations.
These capabilities provided a governed analytics foundation for Inventory, Supply Chain Planning, and Finance teams while standardizing business definitions and improving visibility across global operations.
- Integrated SAP S/4HANA Global and China data, SAP IBP exports, Korea and Japan regional files, and FCCS/Stravis grouping data.
- Extended the enterprise data warehouse built on Azure SQL Server, leveraging the Phase 1 foundation.
- Implemented an ETL framework using Microsoft SSIS for scheduled extraction, cleansing, transformation, and loading.
- Developed dimensional models using conformed Product, Customer, Calendar, Plant, Storage Location, Inventory Status, Cost Center, GL Account, Currency/FX, and Forecast Cycle dimensions.
- Implemented snapshot-based architecture to preserve historical inventory cost, FX, and forecast information for reproducible analysis.
- Established governed semantic models with role-, row-, and column-level security aligned to business requirements.
- Developed Microsoft Power BI dashboards and reports providing interactive, self-service analytics across Inventory, Supply Chain Planning, and Finance.
- Established a scalable architecture capable of integrating additional enterprise subject areas in future phases.
- Conducted structured discovery sessions with Supply Chain, Inventory, Finance, and regional stakeholders across five regions.
- Defined business requirements, KPIs, measures, calculations, and regional variations for Phase 2.
- Extended the Phase 1 enterprise data warehouse and conformed dimensional model to support inventory and supply chain analytics.
- Integrated SAP S/4HANA, SAP IBP, regional flat files, and FCCS/Stravis grouping data into the centralized repository.
- Established governed data models and Power BI semantic models for Inventory and Supply Chain Planning.
- Standardized inventory, forecasting, supply planning, and financial reporting definitions across regions.
- Implemented historical snapshot capabilities for inventory cost, FX, and forecast information.
- Established security and governed access mechanisms aligned with business confidentiality requirements.
- Performed testing, user validation, training, and deployment activities.
- Extended the scalable analytics foundation for future enterprise-wide subject areas.
Phase 2 delivered analytics capabilities across the following business areas:
- Inventory Management Analytics: Visibility into inventory balances, statuses, quantities, values, movements, and inventory positions across global operations.
- Inventory Valuation & Aging Analytics: Analysis of inventory using standard, moving-average, and transfer-price costing, together with aging, shelf-life, and expiration insights.
- Inventory Accuracy & Field Inventory Analytics: Support for cycle-count accuracy, consignment, trunk, clinical-representative inventory, and Schedule A/PAR compliance monitoring.
- Demand & Forecast Analytics: Visibility into demand forecasts, forecast accuracy, forecast bias, and Forecast Value-Add using SAP IBP data.
- Supply Planning & Inventory Health Analytics: Analysis of rolling supply plans, safety stock, Months on Hand, inventory health, plan-versus-actual variance, and backorders.
- Financial Reporting Groupings: Standardized FCCS and Stravis financial groupings based on Cost Center and GL Account combinations.
These capabilities provided a governed analytics foundation for Inventory, Supply Chain Planning, and Finance teams while standardizing business definitions and improving visibility across global operations.
- Integrated SAP S/4HANA Global and China data, SAP IBP exports, Korea and Japan regional files, and FCCS/Stravis grouping data.
- Extended the enterprise data warehouse built on Azure SQL Server, leveraging the Phase 1 foundation.
- Implemented an ETL framework using Microsoft SSIS for scheduled extraction, cleansing, transformation, and loading.
- Developed dimensional models using conformed Product, Customer, Calendar, Plant, Storage Location, Inventory Status, Cost Center, GL Account, Currency/FX, and Forecast Cycle dimensions.
- Implemented snapshot-based architecture to preserve historical inventory cost, FX, and forecast information for reproducible analysis.
- Established governed semantic models with role-, row-, and column-level security aligned to business requirements.
- Developed Microsoft Power BI dashboards and reports providing interactive, self-service analytics across Inventory, Supply Chain Planning, and Finance.
- Established a scalable architecture capable of integrating additional enterprise subject areas in future phases.
Creating Unified Visibility Across Inventory & Supply Chain Planning
The Phase 2 analytics platform unified inventory, demand, supply planning, and financial grouping information while improving KPI consistency, historical analysis, and self-service access to governed insights across global operations.
Unified Global Inventory Visibility
Established a consolidated view of inventory balances, positions, values, movements, aging, and status across global operations.
Improved Supply Chain Planning Insights
Enabled better visibility into demand forecasts, forecast performance, supply plans, safety stock, inventory health, and backorders.
Standardized Business Metrics
Established consistent KPI definitions and governed calculations across regional operations.
Reproducible Historical Analysis
Preserved historical inventory cost, FX, and forecast information through snapshot-based architecture.
Reduced Manual Reconciliation
Connected Phase 1 sales analytics with Phase 2 inventory information through shared business dimensions and a governed semantic layer.
Self-Service Analytics
Enabled governed Power BI analytics across Inventory, Supply Chain Planning, and Finance.
Tech Stack Summary
The solution extended the existing enterprise data and analytics architecture to integrate global inventory, supply planning, demand, and financial grouping data into a centralized analytics platform.
Data Sources
Data Integration
Data Warehouse
Data Visualization
Regional Flat Files, FCCS/Stravis
Azure SQL Server
Data Sources
Regional Flat Files, FCCS/Stravis
Data Integration
Data Warehouse
Azure SQL Server
Data Visualization
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