9 Takeaways from AstraZeneca’s Digital Transformation that Pharmaceutical Manufacturers Can Apply Today

Digital transformation in the pharmaceutical industry can be slow, fragmented, and difficult to scale across sites. Validation cycles introduce delays. IT-led platforms don’t reflect operational needs. And global rollouts stall under the weight of compliance, change control, and disconnected systems.

But that’s starting to shift. At Ops Calling 2025, AstraZeneca’s digital operations leaders shared how they scaled Tulip-based apps across 120 packaging lines in 17 global sites in under three months. They achieved a 29% reduction in changeover time, 50% less variability, and full GxP compliance. Their results illustrate a broader shift in pharma: transformation strategies built around operational usability, modular architecture, and structured, scalable rollouts.

AstraZeneca’s session offers a compelling blueprint for digital scale in regulated operations. This article builds on those insights, distilling 9 takeaways for pharmaceutical leaders driving transformation with speed, structure, and sustained impact.

In regulated manufacturing, lean manufacturing has long been the foundation for operational improvement focused on reducing waste, improving flow, and enabling structured, frontline-driven problem solving. But paper-based lean hits a ceiling. Without real-time data, variability remains hidden, and gains are difficult to scale.

To address this, AstraZeneca developed and applied a concept they call Lean Digital.

Lean Digital combines core lean principles with embedded digital tools to make execution measurable, repeatable, and scalable. It doesn’t replace lean, it amplifies it with real-time insights and compliance-aligned workflows.

At Operations Calling, AstraZeneca shared how this approach helped them move beyond static instructions and spreadsheets. By capturing task-level data at the point of work, they reduced variability, sped up improvement cycles, and scaled standardized execution across 17 global sites.

Step 1: Start with a Structured, Phased Rollout

Start small, like a phased rollout, ideally in a non-critical area so you can gather feedback, refine workflows, and resolve bugs early.

“When we initially scaled this we only deployed one line. So quite quickly we did start to get some immediate feedback of how it actually could be improved."

This phased strategy gives each site a consistent entry point while allowing local adaptation for factors like equipment, staffing, and language. It also creates space for your central team to refine deployment methods, address issues early, and ensure that key elements like user experience, validation processes, and governance roles are fully established before scaling further.

Step 2: Treat the First Rollout as Version 1, Not the Final Product

Don’t expect your first deployment to be perfect. Encourage immediate feedback from operators e.g. on layout, task flow, instructions, and more. Review performance data regularly and act quickly on insights. Small adjustments (like UI tweaks or improvements to the app logic) can add up to major usability gains over time.

Maintain a regular cadence for updates and version control across sites. While localization may be necessary for language or compliance, aim to keep the core application consistent. This preserves scalability while still supporting local needs.

Step 3: Create a Digital Deployment Playbook

Before you scale, capture what worked in early deployments into a structured, shareable playbook. This should act as a deployment guide for every site and include:

• Validation steps aligned with GxP requirements

• Resource planning and site readiness criteria

• Inputs needed for digitizing standard work

• Data preparation guidance for system integrations (e.g. SAP)

• Clear processes for requesting and approving changes

Your playbook should strike the right balance: enough structure to ensure consistency, but flexible enough to adapt to site-level realities.

Step 4: Focus on Use Cases That Show Early Impact

When scaling digital systems, some workflows make better pilots than others. Start where the work is frequent, variable, and low risk. These are ideal places to prove value quickly without slowing production.

Digital changeovers are one of the most effective starting points. These transitions between batches or products are common across lines but often unstructured and undocumented. By digitizing them, teams can capture task-level data, reduce variability, and cut downtime all while keeping validation straightforward.

Other good entry points include:

• GxP logbooks: Replace paper with traceable, audit-ready records

• Goods receipt: Digitize inbound material handling with SAP links

• Batch records (MES-lite): Capture process data in compliant, structured forms

• Lab execution (LES): Digitize lab workflows and test records for full traceability
  

These aren’t IT projects. They’re operational tools that make work visible, reduce errors, and accelerate improvement cycles. Start with the ones that show results early. Once they’re stable, expand them. Early wins build momentum for everything that follows.

Step 5: Build a Reliable Data Backbone and Integration Layer

Digital systems only work as well as the data underneath them. If the data is messy or disconnected, progress stalls fast. Building a solid backbone from the start makes everything that follows easier to manage.

That means having two things in order:

• Master data: production areas, equipment, material codes, and similar reference sets

• Transactional data: process orders, operator inputs, task records, and real-time events

To keep this information consistent across systems and sites, you need a shared source of truth. That’s where an external data management (EDM) layer comes in.

Think of EDM as the central source of truth. It makes sure everyone — from ERP to quality to production, is pulling from the same, up-to-date information. No duplicates, no confusion, no chasing down the “real” data. Just one place to manage it all.

On top of that, an integration layer should handle the movement of data between systems like ERP, quality, and production apps. Automated, scheduled transfers reduce manual work and avoid version drift.

Integration doesn’t stop at software. Low-cost IoT hubs, vision sensors, and lightweight connectors can tie physical assets into the same digital thread. That’s where traceability and continuous improvement start to reinforce each other.

Step 6: Set Up Governance, Templates, and Version Control

If you want to scale fast without creating chaos, you need a structure that gives teams freedom, but with the right guardrails. That’s where smart governance comes in.

• Start by centralizing app development to prevent every site from building its own version of the same tools.

• Create reusable templates for high-impact workflows like changeovers, logbooks, and goods receipt, designed for quick deployment with minimal customization.

• Build templates that support GxP and multilingual needs from the start. Plan for translation length, layout, and validation in multiple languages.

• Define an escalation model that separates platform issues from local process changes, so support is targeted and efficient.

• Assign site-level champions to support adoption, train users, and act as the first line of feedback.

• Set up a cross-site network (like AstraZeneca’s Tulip Exploitation Network) so sites can share learnings and avoid rework.

• Hold monthly governance reviews to align on improvements, gather feedback, and manage upcoming changes.

• Appoint regional or capability leads to help coordinate scaling across functions and geographies.

• Treat digital tools like evolving products, built with clear ownership, regular updates, and ongoing support.

Step 7: Structure Your Deployment Across Multiple Instances

When digital systems start spreading across sites, regions, or functions, you’ll need a clear plan for how the different instances fit together. The goal is to let each site run its own operations while keeping shared standards in place.

Here’s how to set it up:

• Give every site its own instance. It keeps local teams in control of their data, timing, and validation work.

• Keep one central development space for building and testing new apps before they roll out.

• A global instance can help if you’ve got enterprise-wide apps, but use it carefully as it adds layers of access, ownership, and visibility to manage.

• Be clear about who owns what. Write down which instance holds each app, and who updates or supports it.

• Keep core apps aligned.

• Capture your instance setup early, before the system grows. It saves a lot of rework when new teams come online.

This approach lets sites move at their own pace without losing control of the bigger system. It keeps the structure clean, predictable, and easier to support long term.

Step 8: Workforce Enablement and Citizen Development

Scaling digital systems only works when people are ready for it. The tools matter, but the skills and structure around them matter more. You need to grow internal capability in a way that lasts.

Here’s how to approach it:

• Find the right people to build systems e.g. those who know the process, ask questions, and like to solve problems.

• Don’t turn everyone into a builder. App creation should be a skill, not a blanket expectation.

• Give builders what they need: solid training, working examples, and easy-to-follow documentation.

• Be clear on roles i.e. who builds, who reviews, who owns compliance and governance.

• Keep the balance right. Let internal builders handle day-to-day improvements, but bring in third-party help when the work gets complex.

• Have one person or small team leading the platform. Their job is to coach builders, coordinate across sites, and keep the system growing steadily.

• Keep feedback tight between builders and frontline users. Small changes made quickly usually drive the biggest gains.

• Set boundaries early so people can innovate without putting compliance or stability at risk.

• Watch how capacity grows. As more people start building, make sure training and support keep pace.

• Treat enablement as something ongoing. Skills fade if they’re not reinforced.

When people have the right training and the right support, the system doesn’t just stay running, it keeps improving on its own.

Step 9: Use Analytics and AI to Drive Continuous Improvement

Good data should make work easier and not just fill dashboards. The real advantage comes when teams use that information to see what’s changing and fix problems before they grow. Here’s a practical way to get there:

• Hold a monthly review where managers and engineers look at changeover times, task lengths, and operator differences.

• Use data to identify underperforming lines, recurring issues, or training gaps

• Don’t bury insights in reports. Get them in front of the people who can act on them.

• Add AI tools that can sift through data, spot repeating patterns, and suggest where to look next.

• Use those summaries to find bottlenecks and variation faster than you could by hand.

• Create a playbook for how sites use analytics (what to track, how often, what to act on)

• Keep operators in the loop so they see how their input feeds back into better processes.

• Treat analytics as part of everyday operations, not a side project.

• Let the findings steer decisions - whether that’s adjusting a line, adding training, or planning the next automation step.

When everyone can see clean, consistent data, the system starts pointing out what needs attention on its own. You get to problems early, when they’re still easy to fix.

Digital Transformation doesn’t need to be slow or complex. The nine steps above offer a proven path: start with a strong foundation, embed governance early, design with operators in mind, and scale with control. Progress comes from small, repeatable wins, shared across the network.

Tulip enables pharmaceutical manufacturers to scale digital systems without compromising compliance. Built for regulated environments, Tulip offers GxP-ready guardrails, modular building blocks, and seamless integration across systems like ERP, LIMS, and QMS. Teams can digitize frontline workflows, accelerate validation, and expand globally all with the speed and control the industry demands.