Building a Unified Analytics Vision for a Global Medical Device Leader
Established a strategic roadmap for enterprise analytics modernization by defining a future-state data warehouse architecture, standardizing reporting, and enabling scalable, data-driven decision-making across global business functions.
6
Weeks to assess the global analytics landscape and define strategy
7
Business Functions assessed across Sales, Marketing, Finance, Supply Chain and IT
4
Phase roadmap defined for enterprise analytics and data warehouse modernization
Executive Summary
The client, a global medical device manufacturer, faced challenges arising from fragmented data sources, inconsistent reporting processes, manual spreadsheet-based analytics, and limited visibility across sales, marketing, finance, and supply chain functions. These issues hindered reporting efficiency, data consistency, and enterprise-wide decision-making.
DiLytics conducted a comprehensive Analytics Strategy and Roadmap engagement covering seven business functions and IT. The team assessed the current-state analytics landscape, captured future-state requirements, designed a target architecture, defined an enterprise data warehouse model, recommended technologies, and developed a phased implementation roadmap.
The engagement delivered a clear blueprint for analytics modernization, including governance, security, data quality, integration, and reporting recommendations. The client gained a strategic roadmap to establish a scalable enterprise analytics platform, improve reporting consistency, reduce manual effort, and enable data-driven decision-making across the organization.
The client, a global medical device manufacturer, faced challenges arising from fragmented data sources, inconsistent reporting processes, manual spreadsheet-based analytics, and limited visibility across sales, marketing, finance, and supply chain functions. These issues hindered reporting efficiency, data consistency, and enterprise-wide decision-making.
DiLytics conducted a comprehensive Analytics Strategy and Roadmap engagement covering seven business functions and IT. The team assessed the current-state analytics landscape, captured future-state requirements, designed a target architecture, defined an enterprise data warehouse model, recommended technologies, and developed a phased implementation roadmap.
The engagement delivered a clear blueprint for analytics modernization, including governance, security, data quality, integration, and reporting recommendations. The client gained a strategic roadmap to establish a scalable enterprise analytics platform, improve reporting consistency, reduce manual effort, and enable data-driven decision-making across the organization.
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Client Overview
Terumo Neuro is a leading medical device company specializing in minimally invasive neuro endovascular 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: Neurovascular Medical Devices, Business Intelligence Strategy, Data Governance
- Market Position: Recognized Leader in Medical Device Solutions
Navigating a Complex Analytics and Data Landscape
The client’s rapid growth introduced increasing complexity across business functions, systems, and reporting requirements. Data existed across multiple enterprise platforms, making it difficult to establish consistent metrics, governance standards, and reporting practices. To maximize future BI investments and reduce implementation risks, the organization needed a clearly defined analytics strategy and execution roadmap.
Fragmented Data Landscape
Fragmented Data Landscape
Inconsistent Metrics & Reporting
Inconsistent Metrics & Reporting
Limited Strategic Alignment
Limited Strategic Alignment
Unclear Modernization Path
Unclear Modernization Path
Navigating a Complex Analytics and Data Landscape
Fragmented Data Landscape
Fragmented Data Landscape
Inconsistent Metrics & Reporting
Inconsistent Metrics & Reporting
Limited Strategic Alignment
Limited Strategic Alignment
Unclear Modernization Path
Unclear Modernization Path
Developing a Strategic BI Roadmap for Enterprise Analytics Transformation
DiLytics conducted a comprehensive Analytics Strategy and Roadmap engagement to assess the current analytics landscape, identify business and technical gaps, define the target-state architecture, and establish a phased roadmap for enterprise analytics modernization. The engagement covered stakeholders across sales, marketing, finance, supply chain, operations, and IT functions globally across USA, EMEA and Asia Pacific Regions.
DiLytics successfully completed the assessment and roadmap exercise within 6 weeks.
- Conducted stakeholder interviews and discovery workshops across 7 business functions and IT
- Assessed the existing analytics landscape, reporting processes, data architecture, and technology stack
- Documented current-state challenges, future-state requirements, and analytics opportunities
- Evaluated data warehouse, data integration, analytics, governance, security, and data quality capabilities
- Developed enterprise analytics strategy and target-state operating model
- Created implementation roadmap, resource plan, architecture blueprint, and technology recommendations
DiLytics identified and defined enterprise analytics requirements across:
- Sales Performance & Forecasting
- Marketing & Market Intelligence Analytics
- Product Performance Analytics
- Financial Planning & Profitability Analytics
- Inventory & Supply Chain Analytics
- Demand Forecasting & Planning Analytics
- Manufacturing & Operations Analytics
- Backorder & Order Fulfillment Analytics
- Customer & Territory Analytics
- Accounts Receivable Analytics
The engagement also established requirements for:
- Self-service analytics
- Predictive analytics
- Role-based reporting
- KPI standardization
- Data governance, and
- Enterprise-wide reporting consistency
DiLytics designed a future-state analytics architecture comprising:
- Enterprise Data Warehouse with consolidated data models
- Integrated data pipelines across SAP, Hyperion, IBP, ETQ, RIMSYS, Workday, MobileFrame, Windchill, CAPS, Lexion, and third-party data providers
- Standardized fact and dimension models covering Sales, Finance, Inventory, Manufacturing, Forecasting, Shipping, Backorders, and Product Performance
- Microsoft-based reference architecture leveraging Azure SQL, SSIS, and Power BI
- Data governance, security, master data management, and data quality framework
- Four-phase implementation roadmap spanning data integration, data warehouse modernization, advanced analytics, and enterprise reporting
- Conducted stakeholder interviews and discovery workshops across 7 business functions and IT
- Assessed the existing analytics landscape, reporting processes, data architecture, and technology stack
- Documented current-state challenges, future-state requirements, and analytics opportunities
- Evaluated data warehouse, data integration, analytics, governance, security, and data quality capabilities
- Developed enterprise analytics strategy and target-state operating model
- Created implementation roadmap, resource plan, architecture blueprint, and technology recommendations
DiLytics identified and defined enterprise analytics requirements across:
- Sales Performance & Forecasting
- Marketing & Market Intelligence Analytics
- Product Performance Analytics
- Financial Planning & Profitability Analytics
- Inventory & Supply Chain Analytics
- Demand Forecasting & Planning Analytics
- Manufacturing & Operations Analytics
- Backorder & Order Fulfillment Analytics
- Customer & Territory Analytics
- Accounts Receivable Analytics
The engagement also established requirements for:
- Self-service analytics
- Predictive analytics
- Role-based reporting
- KPI standardization
- Data governance, and
- Enterprise-wide reporting consistency
DiLytics designed a future-state analytics architecture comprising:
- Enterprise Data Warehouse with consolidated data models
- Integrated data pipelines across SAP, Hyperion, IBP, ETQ, RIMSYS, Workday, MobileFrame, Windchill, CAPS, Lexion, and third-party data providers
- Standardized fact and dimension models covering Sales, Finance, Inventory, Manufacturing, Forecasting, Shipping, Backorders, and Product Performance
- Microsoft-based reference architecture leveraging Azure SQL, SSIS, and Power BI
- Data governance, security, master data management, and data quality framework
- Four-phase implementation roadmap spanning data integration, data warehouse modernization, advanced analytics, and enterprise reporting
Laying the Foundation for Enterprise-Wide Analytics Excellence
The strategic roadmap aligned business and technology stakeholders around a unified analytics vision while providing a practical, phased approach to modernizing reporting, governance, and enterprise data capabilities.
Unified Enterprise Analytics Vision
Established a common future-state strategy across sales, marketing, finance, supply chain, and IT functions
Prioritized Modernization Roadmap
Delivered a practical implementation plan that reduced uncertainty around future investments and transformation sequencing
Reduced Manual Reporting Dependency
Identified opportunities to eliminate spreadsheet-based reporting and streamline enterprise data preparation processes
Foundation for a Single Source of Truth
Defined a roadmap for consistent enterprise reporting and standardized business definitions across functions
Future-Ready Advanced Analytics
Created the strategic foundation for self-service, predictive, and advanced analytics capabilities
Optimized Existing Technology Investments
Recommended a phased modernization approach that leveraged current Microsoft-based analytics assets while enabling long-term scalability
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