Four steps for pharma organisations to build their digital factory

In response, pharma leaders are investing in, building, and acquiring new production facilities. But this is a long-term, costly, and demanding solution. In the age of the intelligent enterprise, there’s a smarter solution: to digitise and automate existing assets to gain better operational efficiency and optimise capacity. Put plainly, today’s intelligent pharma enterprise needs to digitise its factory.

In the digital factory, sensors on pharma production lines generate sophisticated performance data that allow failures to be predicted with unprecedented accuracy, and traced back to their root cause. Data-led insight enables proactive maintenance strategies, which minimises downtime, frees up capacity, and reduces operational risk. Meanwhile, data from suppliers provides detail on the concentration of individual batches of raw, active materials. Production lines are more highly tuned to their inputs, environment, and operating conditions. In short: supply meets demand, and competitive advantage is gained.

How to get there

That’s the ambition. But too often, pharma organisations find themselves in reaction mode – working out plans on the fly in the race to expand capacity.

Instead, success calls for a structured plan. Where you start depends on your current maturity of digital factory adoption, and your current set of technological capabilities. But in our view, all pharma organisations have scope to further develop their digital factory and meet today’s demand with a focus on the following:

Start with a vision

To begin, forget the new, seductive technologies. Instead, success starts with a clear focus on the outcomes you want to achieve. It’s this clarity of vision that will determine what degree of digitisation is needed, where to apply it, and how to apply it.

The mission is to craft a dynamic strategy which ensures that every objective, key result, and strategic goal are as perfectly synchronised as possible – and supported by leaders across the organisation.

It’s an approach we’ve seen reap rewards. We worked with a leading global diabetes device manufacturer in defining their integrated smart factory and supply chain strategy. Bringing together a broad range of stakeholders, we kept momentum by quickly moving from future vision into a practical diagnosis of the data and digital foundations required. And this cued up planning around cloud deployment, the development of data analytics/machine learning use cases in the manufacturing processes, and an identification of the value potential for generative AI.

Catalyse the business to execute

Translating your visions into executable actions requires an appropriate operating model and strong prioritisation framework. Factors such as centralised/decentralised delivery, funding mechanisms, collaboration with internal and external stakeholders, and transparency around ongoing initiatives will all be topics for consideration and decision.

We’ve worked with a global pharmaceutical company where different entities focused on local digitisation initiatives, none of which were designed to be scaled or standardised. The result? A complicated and fragmented digitisation landscape with unclear roles, responsibilities and ownership.

To combat this, we helped the company assess the current ‘as is’ state, and then harmonised digitisation efforts across the company. We designed and established a streamlined portfolio management setup characterised by lean governance and prioritisation mechanisms. This framework enabled standardisation, scaling, and value realisation of digital initiatives. Then, three distinct organisational setups were designed to nurture future digital factories, to test the pros and cons of different approaches, along with specific use cases for reference.

Assess benefits based on the total value opportunity

Imagine a dynamic engine at the heart of your organisation, driving innovation, business transformation, and technical advancements. This powerhouse aligns investment decisions across the entire value chain, ensuring that every decision moves your portfolio strategy forward and assesses the benefits based on the total value opportunity.

At one pharma clients global manufacturing centre, we helped them understand where best to drive digitisation and disruptive change across manufacturing and supply chain. This was based on a collation of best practice and current trends, set against the client’s portfolio and market opportunities. Based on our analysis, they accelerated the application and adoption of sixteen new technologies, creating new value estimated in the order of billions. We then worked closely with the client to help generate the vision for internal communication and formulate a governance model for roll-out across the organisation.

Accelerate technology adoption

You are now at the point where you need to build a resilient and scalable landscape that can fully enable your vision and release the total value opportunity.

Some clients are aware of the areas that need performance improvement. In these cases, different technology types such as machine learning, digital twin, and generative AI can be chosen based on need. Where the need is less clear, a digital scan can be beneficial. Here, for example, technology experts and business representatives would ‘walk’ the production line to identify issues and potential improvements. The result is a report highlighting the most beneficial technology solutions for the organisation.

Along the way, DevOps and Agile principles encourage the development and testing of new ideas, ensuring they can seamlessly integrate into the broader system architecture. And by establishing domain centres of excellence, the organisation can standardise processes and set industry benchmarks for best practice. Working with a global client to create, protect, and globally scale their new-to-world smart milling technology, we helped them manage manufacturing supply chain risk and continuity. Together with the client, we identified and integrated enabling technologies, and built a half-sized pilot plant capable of fully autonomous operation via our novel self-learning algorithm. As a result, the client and PA created the specifications to turn the pilot mill into a fully operational production manufacturing process.

This structured approach offers pharma organisations a clear route to progress. It’s where they optimise before they augment, and where step-by-step success builds the momentum for the entire organisation to come on the journey to the intelligent enterprise. And for those already on the journey, it’s a way to further foster digital factory excellence.