SAP BW in Life Sciences – what now?

When we talk to colleagues in the medical technology, pharmaceutical or laboratory industries today, the same question always comes up sooner or later: What do we actually do with our SAP BW?

Many companies have built up stable reporting landscapes based on SAP BW over many years – some of them even validated.

The systems are running, the processes are established, and the expertise is in-house. And yet one thing is clear: the world of data is changing – and fast. New requirements arising from AI and predictive analytics, the desire to integrate external data sources, modern visualisation tools, self-service BI, data mesh – all of these are pushing traditional architectures to their limits.

At the same time, support for SAP BW 7.x will expire in a few years. And even BW/4HANA is no longer state of the art. SAP is positioning Datasphere and the SAP Business Data Cloud as the future. Others are relying on Microsoft Fabric, Snowflake or hybrid architectures.

Between investment protection and realignment

Should we stick with what we know – or dare to take the plunge into something new?

We encounter this question in almost every project. While investment protection and validation security are often the primary concerns from a business perspective, the question of innovation, scalability and efficiency arises from a technological point of view.

In practice, we see very different approaches: Some companies are modernising their existing BW/4HANA landscape and integrating new components step by step. Others are taking the opportunity to completely reposition themselves – often towards the cloud or data platform strategies outside SAP.

What matters in both cases is a structured, technology-neutral assessment that is both economically and technically viable.

From the status quo to a robust decision

In our projects, we almost always start with a joint analysis phase – a look into the engine room, so to speak. This is not just about systems, but also about usage, data flows, typical use cases and the actual requirements from the business departments. A reference application helps to make the real complexity tangible and to implement in-depth technical analyses efficiently.

On this basis, we develop several scenarios for the future architecture. Whether SAP-centric with Datasphere, Microsoft-based or a hybrid approach – it is important that we think through these options together with the customer teams: What fits the strategy? What is feasible? And what does this mean for operations, organisation, training and costs?

The end result is not a gut feeling, but a fact-based decision – with a clear management template, a clean TCO comparison and a well-founded evaluation of all relevant criteria: from AI capabilities to governance, from regulatory frameworks to FinOps.

What counts is the big picture

What unites our experience: The best technology stack is of little use if viewed in isolation. Integration is crucial – not only technically, but also organisationally. In the regulated life sciences environment in particular, validation, compliance and data sovereignty must be taken into account.

A good evaluation framework therefore not only highlights tools and functions, but also:

• Can existing regulatory requirements continue to be met?
• What resources need to be built up – in terms of technology and personnel?
• How will costs change over three and a half years or more?
• And how flexible is the solution for future business models?

Conclusion: Decision-making competence through teamwork

The world of data is evolving rapidly – and with it the demands on architecture, processes and organisation. Today, life sciences companies must not only decide what is technologically possible, but also what is right for them.

Our experience shows that the best results come when business and technology work hand in hand. When strategic goals, regulatory frameworks and technological possibilities are considered together, uncertainty turns into clarity. And SAP BW becomes the next step towards a modern analytics future.