From Architecture Assessment to a Sustainable Data Platform at Lohmann & Rauscher

The Customer

Lohmann & Rauscher is an international provider of medical products, system solutions, and services for therapy, care, and prevention. Operating in a highly regulated environment, the company relies on trustworthy, high-quality data to support operational management, innovation, and digital services.

Initial Situation

Lohmann & Rauscher faced the challenge of strategically redesigning its evolving data and analytics landscape. Different systems and integration approaches had led to increasing complexity, limited scalability, and growing IT bottlenecks. At the same time, requirements for data quality, governance, self-service capabilities, and support for new use cases—from traditional BI to IoT and AI initiatives—continued to grow.

Key questions included:

• What should a future-ready target architecture for data, analytics, and integration look like?
• What role should cloud technologies, the modern data stack, and data products play within the organization?
• How can self-service and governance be combined effectively?
• How can business teams be empowered without losing control and consistency?

The objective was to establish a clear architectural and organizational framework and gradually transform it into a sustainable data platform. Lohmann & Rauscher sought to bring clarity to a complex and organically grown data landscape. The focus was on creating a robust architectural foundation that combines scalability, governance, and self-service capabilities, forming the basis for the gradual development of a sustainable data platform.

Solution

INFORM DataLab began the engagement with a structured architecture assessment. Through interviews, workshops, and detailed analyses, existing systems, use cases, roles, and organizational structures were evaluated. The findings were consolidated into a consistent target architecture and aligned with both management and business stakeholders.

Building on this foundation, INFORM DataLab has continued to support Lohmann & Rauscher as both a strategic advisor and implementation partner throughout the introduction of the data platform:

• Advising on architecture and platform decisions
• Defining and establishing best practices for the modern data stack and data products
• Preparing management presentations and strategic decision-making materials
• Delivering training on Data Vault 2.0, data products, and modeling approaches
• Supporting data quality and governance initiatives
• Assisting with deployments and technical implementations
• Providing ongoing consulting for new requirements and use cases

The focus has consistently been on enablement, clarity, and sustainable structures rather than short-term, isolated solutions.

“The continuous consulting support has been particularly valuable—both strategically and operationally.”

— Dennis Faßbender, Lead BI, Lohmann & Rauscher

Benefits for Lohmann & Rauscher

As a result of the project, Lohmann & Rauscher now has a jointly developed target vision for both data architecture and data organization. Existing structures have been analyzed, classified, and made transparent. The initiative created clarity around the future direction of the data landscape and the principles that will guide its evolution.

At the same time, a shared understanding was established across IT, business departments, and management. This provides a reliable foundation for future architecture and management decisions. Self-service concepts have been strategically prepared and aligned with a governance framework. Standards, guidelines, and quality requirements have been clearly defined, enabling internal teams to implement future use cases in a structured and consistent manner.

The organization is now well positioned to drive its transformation forward in a controlled and purposeful way:

• Shared vision for data architecture and data organization
• Transparency across existing structures, dependencies, and areas for improvement
• Common understanding between IT, business departments, and management
• Strategic preparation for self-service within a clear governance framework
• Defined standards and principles for future use cases
• Reliable decision-making foundation for the next implementation phases

Next Steps

In the next phases, the focus will be on further scaling the data platform and expanding the organization’s data products. In parallel, self-service capabilities and enablement programs will continue to evolve, additional systems will be integrated, and new analytics, IoT, and AI use cases will be implemented.

• Further scaling of the data platform and data products
• Expansion of self-service and enablement capabilities
• Integration of additional systems
• Support for additional analytics, IoT, and AI use cases