AI has been a great accelerator over the past 24 months in the life sciences field, especially with the rise of GenAI. GenAI has significantly lowered the barrier for our business users, enabling them to engage with data in a more intimate setting.

However, realizing the promise of AI is not only about having strong, reliable, and trusted data but also having a deep understanding of that data. Building data literacy across the organization and treating data as a strategic asset are fundamental pillars that will help us unlock the full potential of AI.

The other aspect that goes hand-in-hand with data is skills development. We need to focus on upskilling the organization in the use of AI, AI techniques, and the proper handling of data in a secure and compliant way — especially since, in a life sciences organization, we have to navigate various regulations while conducting business.

We must ensure that data is accessible in the right places, at the right times, and to the right people — all while maintaining security, compliance, and privacy standards.

We firmly believe that everyone within the organization should have access to the data they need, whether it’s internal or external. One of our key initiatives is to standardize how we ingest external data. This isn’t just about data procurement; it’s about ensuring security, compliance, privacy, and thoughtful design. We want to make informed design decisions as we bring data into the organization.

Our goal is to eliminate the friction that often arises when procuring both internal and external data, ensuring that business users can easily access the data they need when they need it.

What sets Merck/MSD apart is our creation of an enterprise-wide data marketplace, which went live over the past 12 months. This marketplace serves as a one-stop shop for all our data users. It enables them to discover, access, and interact with available data within a seamless user experience.

It’s not just about enforcing strong data governance and ensuring compliance; it’s equally about creating a frictionless user experience for those interacting with the data.

As a large pharmaceutical company, we certainly face our own set of complexities. However, I’m fortunate to have robust senior executive sponsorship for our efforts to manage, utilize, and leverage data as a strategic asset.

The key here is starting with strong business sponsorship and focusing on the major business outcomes we aim to achieve. This approach has been instrumental in demonstrating the value of the capabilities we’re building, aligning them with business value, and driving that value home with the support of our business sponsors.

We’re also witnessing a significant shift, not just within our organization but across the broader pharmaceutical sector. Data is becoming increasingly important across divisions. The need for data is no longer confined to individual business units; instead, there’s a growing enterprise-wide mindset, with a focus on horizontal collaboration and breaking down silos. Data is becoming inherently cross-divisional.

Take, for example, customer data. While customer information typically resides within the commercial division, it manifests in various forms throughout the organization. For instance, a customer could be a key opinion leader or an investigator, and we need to ensure that we deliver a consistent, unified experience across the business. This is where looking at data cross-divisionally becomes essential, and there are many other instances where this cross-divisional perspective applies.

The value of our data extends beyond the immediate needs of individual divisions and viewing it from an enterprise-wide perspective offers multiple benefits. The top three are:

1. Deepening collaboration around data: This ensures that teams share a unified understanding of how data is being used and which business processes it’s supporting.

2. Improving data procurement: By understanding where data already exists within the organization, we avoid purchasing the same data multiple times, streamlining procurement efforts.

3. Strengthening security, compliance, and privacy: Not all data should be democratized. The accessibility of data must be driven by specific use cases and desired outcomes, ensuring that proper controls are in place.

Our approach is cautious but effective. It’s not just about making data available, but ensuring it is discoverable and properly managed. Before anyone can access data, there’s a streamlined process in place that includes requests, training, and governance, all of which are essential for ensuring the right people have the right access at the right time.

All of our design decisions are guided by the business outcome and user experience, which serve as our North Star. We adopted a platform-centric approach to ensure that our marketplace is seamlessly connected to a data catalog, access control capabilities, and our cloud infrastructure.

There isn’t a single technology that can address all of our needs, even with our platform approach. We’ve selected the best technologies within our ecosystem because we recognize the importance of integrating them to create a cohesive system.

While we operate on one of the big three cloud providers, we are also committed to ensuring interoperability across different cloud environments. To achieve this, we’ve made specific architectural technology choices that allow our designs and implementations to be cloud-enhanced.

When it comes to business outcomes, it’s about understanding the experience you want to drive. Who are the personas using the data? When we think about data products, we consider the governance aspect, which divides the landscape into data producers — those creating data products — and data consumers — those using them.

This lens shaped how we designed our ecosystem. There’s no single technology that fits every need. Instead, you must identify the best technologies for your specific ecosystem and integrate them to deliver a unified experience for your users.