Pharma, pharmaceuticals, digital transformation, AI, articifial intelligence

The Pharma Industry Needs a Cultural Shift to Achieve Industry 4.0

June 20, 2021

The concept of Industry 4.0 and digitally transformed smart factories has changed the corporate agenda in pharmaceutical manufacturing.

Many boardrooms in the pharma industry are aware of the transformative potential of digitalization and have started to embrace it. The industry’s experience of working through the pandemic has also demonstrated how advanced digital technology underpins organizational agility. The result is that some companies are investing large amounts of money into solutions, including artificial intelligence (AI) and machine learning, from which they expect a return. 

Despite this growth of enthusiasm for digitalization, however, most of the pharmaceutical manufacturing industry remains at Digital 2.5, with culture still one of the biggest barriers to adoption and implementation. Organizations struggle with or fear the potential scale of change and how it can fundamentally reform processes. Many manufacturers, for example, are not set up organizationally to adapt to technology refresh rates of 18 months rather than five years as with many conventional process technologies. 

There may also be hesitancy in part because digitalization means something different in every organization and can embrace any process from the shopfloor to the top floor – from closed loop systems to continuous manufacturing, predictive maintenance, scheduling or digital twin technology. We know that digitalization has the potential to improve the entire value network all the way from R&D through to the patient, but where do you start?


Culture is Key to Progressing Digital Transformation

Cultural barriers are, however, so significant that whoever is tasked with driving digitalization within an organization must address them first to build trust and confidence. Boards, for example, may not have a firm idea of what they want specifically, but they will be looking for improved outcomes across financial, operational, quality and regulation. 

It is important they are made aware that the solutions are available, but that their organization first needs to manage and understand data so it knows what to measure. The whole industry is data-rich but intelligence-poor. Many companies, it’s worth remembering, could well be sitting on 35 years of data, which once managed properly will provide efficiency-transforming insight, built from a highly accurate holistic view of the entire organization. 

To win confidence and break down the cultural barriers those responsible for digitalization should initially narrow their focus to a business case that can deliver transparent benefits. Although digitalization will fundamentally change the way manufacturing companies work, it is important to start with a tailor-made solution that solves a specific problem or provides immediate gains that will convince skeptical insiders. It is important to strike a balance between the need to maximize ROI by being bold, and the battle for hearts and minds. Equally, there is no value in automating processes just because it is easy to do so. They must deliver measurable benefits.

One of the most obvious targets should be the removal of paper documentation that many organizations still use every day to support manufacturing processes and regulatory compliance. Digitalized reviewing by exception, for example, will remove so much of the wasted time associated with paper, and improve the accuracy and timeliness of results. 

The cultural dimension also encompasses regulation, which often generates considerable anxiety. The digital leaders in a manufacturing organization should engage in closer dialogue with regulatory bodies in the U.S. and Europe about projects that include compliance or reporting. They are often more receptive than anticipated. Regulatory agencies are adjusting their guidance on compliance to encourage the adoption of newer technology, but they acknowledge the culture that has formed over years around validation will need to evolve for the new guidance to gain traction. More broadly the pharma industry needs to achieve greater consensus with regulators on solution validation, review by exception and real-time release testing (where process analytical technology has a major role to play). 

Once everyone has seen how effective the first project, companies should continue to transform their data management, using their new level of insight to move accomplish more projects. In the current recovery from the pandemic, when greater supply chain resilience has become a much sought-after corporate goal, manufacturers can use insights rather than data alone to strengthen themselves through the creation of smart networks. Insights, and not just good hunches, will give them a network of multiple suppliers and providers to whom they can switch for optimal performance as conditions require. In the event of another virus outbreak and restrictions on human movement, digitalization also opens the door to increased remote control of the manufacturing process, maintaining efficiency without major disruption or endangering employee safety. 

There are clearly multiple concepts and applications of digitalization in the pharma manufacturing sector and a growing appetite to see its vast potential realized throughout the value process. Yet as an essential prerequisite, organizations must tackle the cultural questions if they are to reap the full rewards. That change in culture should include a new approach to data and its management. Once they have achieved that all-important initial success and given themselves a data platform, the process of digitalization should gather pace, transforming performance and resilience throughout the organization. 


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