Implementing Industry 4.0 in Pharmaceutical Manufacturing

By Kim Loynes, 31 March 2021

How can companies go about bringing the next generation of advanced data capabilities into their organisation?

 Pharmaceutical companies are increasingly opening themselves up to the opportunities on offer from digital transformation. However, understanding its value is one thing, successfully implementing it is another. Each organisation will have to address a series of important questions such as:

  • How can we improve the quality of data collected?
  • How can we improve business operations?
  • Can we integrate new technologies into existing processes?
  • Should operations be controlled in house or should we choose a third-party provider?
  • Can we ensure data security and regulatory compliance?

The answers to those questions will determine how successfully firms integrate advanced analytics technologies into manufacturing processes.

Data Quality  

Transforming a business into a data driven enterprise starts with improving data quality. This is particularly challenging for the pharmaceutical industry where it can be difficult to obtain real time data in a usable format. However, developments in the health sector are contributing to an explosion of data generation from sources such as research and development process, retailers, patients and caregivers. However, quantity doesn’t necessarily translate to quality.

Advanced analytics systems have the capacity to store, manage and transform data in such a way that it can collate and derive usable insights from highly complex data sets and present it in an accessible format for key decision makers.

This has the potential to improve the overall quality of processes at every stage from research to manufacturing, trialling and distribution.

Some of the most promising avenues include:

  • Predictive modelling of biological processes can help drugs to become more sophisticated and widespread.
  • Leveraging available clinical and molecular data for predictive analytics to identify new candidate molecules with a high probability of being successfully developed into drugs.
  • Trials can be monitored in real time giving superior granular detail about performance. This can highlight potential problems at an earlier stage and reduce the occurrence of adverse events.

A company which wishes to transform itself into a data driven enterprise, therefore, needs to have access to high quality data, which can be integrated into the organisation and there is considerable progress.

Culture and Attitude 

Addressing culture within a business is vital if a company is to adopt industry 4.0 technologies. Although things are changing the biggest impediment to change is a fear of change and a feeling among companies, that they lack the expertise and infrastructure to integrate advanced analytics effectively.

Companies will face a challenge of integrating new technology with existing technology and systems. Attitude, culture and expertise are all obstacles, so these must be overcome. The most successful companies adopt a detailed step by step process which puts the fundamental building blocks in place which enable them to facilitate the transformation.

This starts with attitude. The adoption of digital technology is a business transformation as much as a technological challenge. The entire business will have to adapt to ensure its systems can cope with the coming changes.

Next firms must invest in people with the right skills and capabilities to help you move towards digital manufacturing. This process will include the use of third party organisations and providers

The rise of digital technology places an increased emphasis on the importance of partnerships. Digital transformation is driven by innovative and high performance small companies capable of delivering advanced technological solutions. Identifying best in class partners and providers will be vital. For this, firms can learn from the example of other industries.

The one advantage of being relatively slow moving in the uptake of digital technology is that the pharmaceutical industry can look to the examples of other sectors, which have already progressed a significant way down the path of their own transformations. These offer valuable learnings for any company wishing to explore the same path.

For example, the entertainment industry uses big data analytics to help inform customer choice; the financial sector harnesses data to highlight operational improvements, enhance customer engagements and identify investment opportunities. 

In the aviation industry early adopters such as Delta Airlines have seen enormous benefits. The company’s share price has soared over recent years, until the unexpected intervention of COVID 19. It attributes much of its success to a comprehensive adoption of data analytics which permeates throughout operations and has transformed airline operations, improving services and customer engagement. 

For example, a $100 investment in airport baggage systems allowed it to use data to transform baggage handling operations improving performances and identify key trends to help it identify the causes of baggage mishandling errors and improve process times. 

In House or Outsourced? 

The use of partners shines a light on a pressing question: whether to outsource this process or keep it in house. Both have advantages and disadvantages. 

By outsourcing, you can leverage expertise and technological infrastructure you might not possess internally. You can employ a team of experts with the capacity to understand the technology and apply it to your team.

The downside of outsourcing is that you relinquish control to a third-party provider who may or may not be up to the task. You understand your business needs and if you have a sufficiently sophisticated in-house team, you’ll be able to craft a truly bespoke solution designed specifically around you.

Third party providers will vary in terms of the quality of service they can offer, and to what extent they can provide bespoke solutions designed specifically for your requirements.

The use of a third party partner also potentially opens you up to security risks if their own infrastructure is not up to date.

Organisations will therefore have to assess their own operations and adopt the right approach for them. While larger organisations might over time have developed their own extensive and highly advanced internal functions, this might not be possible for other smaller and mid-tier operations.

They will benefit from adopting either a fully outsourced or hybrid model to leverage the expertise and capacity from specialist organisations.

In short there are three options to choose from.

In House:  

Data capabilities are built in house from the ground up. This will help to retain control and develop a company culture in which data analytics is at the heart of operations from the ground up. It helps companies control costs over the longer term and brings in talented individuals with the skills and experience required to deliver superior performance.

The down side of this approach is that it requires a substantial up front investment, requires planning and has a long lead in time. Companies will have to develop specialist in house teams and recruit expert individuals from what is still a limited talent pool and purchase state of the art technology.

Looking to the future this also lacks flexibility. Resources and functionality could be constrained by the infrastructure you have in place which will take time and be expensive to replace. In an environment in which new technology is being introduced continually new systems can quickly become outdated. 

Outsourced:

Choosing a third party provider, on the other hand allows firms to leverage the skills and expertise of a specialist company. Services are more flexible and can grow with the company and as the wider technological environment evolves. Start up costs are lower, with the firm leveraging the infrastructure of their partner companies.

However, you will be fully dependent on those third party organisations and will not develop the internal skills and culture to capitalise on digital transformation. You will need a closely managed service agreement to ensure the partnership meets its objectives. Equally, if you have entered into a long contract you might incur penalties if you wish to end the relationship early.

Hybrid model:

A best of all worlds approach in which you partner with some third party organisations for some operations. Others are built in-house.

This offers more control over data insights and the ability to start building a skilled in house team. Services are more flexible, with those which are not needed easily discarded in order to optimise costs. Over time it could be a stepping stone to evolving your own fully in house functionality.

However, firms are still dependent on third party organisations. It offers less control over analytics capabilities than a fully in house approach and may slow the development of internal expertise and understanding.

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