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MES of the Future: Insights from MES Berlin 

Capgemini
Sep 26, 2024

In the first blog of this series, we discussed the current state of Manufacturing Execution Systems (MES) in the pharmaceutical industry, highlighting the challenges and limitations faced today. As a natural sequel, the second blog explored the future advancements in MES, promising greater integration, flexibility, and efficiency, and their potential impact on pharma manufacturing. Now it’s time for the third and last blog of this series, focusing on the outcome of the Pharma MES conference in Berlin.

On September 23rd, 2024, we hosted a session at MES Berlin, titled “MES of the Future.” The discussion brought together thought leaders and experts from various industries, spanning both information technology and manufacturing, to explore the evolving landscape of Manufacturing Execution Systems (MES). Below are our 7 key takeaways from the session, focusing on challenges, advancements, and the future of MES. 

1. Balancing Capacity Growth and Standardization 

One of the core themes of the discussion was the delicate balance between growing manufacturing capacity for some Manufacturers and the need for standardization across multi-site MES deployments. As industries expand, especially in global manufacturing environments, the integration of contract manufacturers has become essential. However, scaling up comes with significant investments, and aligning organizational expectations across different sites remains a challenge. 

Key Insight: Balancing capacity growth with standardization is critical for successful MES programs, especially when integrating with contract manufacturers and managing large-scale, Greenfield deployments. 

2. AI/GenAI and Data Challenges 

The integration of AI/GenAI with MES was another hot topic. Although enthusiasm is high, and proofs of concept exist, there are significant hurdles to overcome. For instance, the proprietary nature of manufacturing data may not always align well with large language models, which limits their utility in some cases. Additionally, skill levels among colleagues, especially in certain languages, can pose challenges for widespread GenAI adoption. GxP validation is another significant concern. 

Key Insight: While AI and GenAI are promising, there’s a significant need for foundational work and data strategy alignment before these technologies can be fully realized within MES environments. 

3. Pathways for AI/GenAI Integration with MES

Following on the current and future states of AI/GenAI, the session also distinguished between different areas of focus within MES deployments. As one example, AI/GenAI can be used to develop and translate manufacturing recipes; In another example, it can be used to optimize manufacturing goals, such as enhancing flow through constraint points. The former is an example of enabling program design and rollout, while the latter is an example of value delivery from the MES investment. The consensus was that while program implementation efficiency/accelerating using advanced technologies is beginning, these techniques are not yet being fully leveraged to optimize broader manufacturing processes. 

Key Insight: AI/GenAI potential in MES is far-reaching, but its full use in optimizing manufacturing goals is still in its infancy. At present, most of the AI/GenAI efforts in MES have been in system design and rollout vs. in use of MES data to drive Manufacturing goals.

4. Risk Assessment and GxP Validation

As industries adopt more advanced technology applications and SaaS models within MES, the importance of leveraging risk assessments, particularly in GxP-validated environments, was emphasized. Discussions also highlighted the benefits of learning from out-of-industry benchmarks, particularly the automotive sector, which has managed to accelerate technology deployments with a high degree of standardization and efficiency. 

Key Insight: Risk assessment and validation processes must be tailored for advanced technologies and SaaS models, leveraging best practices from industries like automotive to drive efficiencies.

 5. Unlocking Value from Data

The session also considered the challenge of turning vast amounts of data into actionable insights. While MES deployments generate large volumes of information, the consensus was that most organizations are still at the stage where more data is being gathered and stored vs. serving value extraction. The true promise of MES will be realized when organizations can effectively use this data to optimize manufacturing processes and achieve greater efficiencies. 

Key Insight: The true value of MES comes from transforming data into actionable insights that optimize operations and unlock efficiencies in real-time. 

6. Organizational Alignment and Change Management

The session also touched on the importance of organizational alignment when deploying MES and that driving change requires an understanding of the operational realities on the factory floor. Engaging operators where they are, while maintaining strong sponsorship from top-level management, is essential to ensure that MES initiatives do not lose momentum. Organizational ownership of MES itself is also variable (IT, OT, or hybrid) and in some cases has shifted in ownership, with further exacerbates challenges in driving change.

Key Insight: Effective change management for MES deployments involves bottom-up engagement with operators and top-down support from leadership, ensuring alignment across organizational layers. 

7. Leadership and Operator Engagement

Another key change management takeaway was the role of leadership in fostering an MES-friendly operating environment. Engaging operators from the outset and considering their perspectives throughout the MES deployment process is crucial. Leadership must drive the conversation, ensuring that technology implementation aligns with operational goals. 

Key Insight: Leadership must play a proactive role in integrating operator perspectives and driving the MES deployment forward. 

Closing Thoughts and Conclusion

The session concluded with a sense of achievement and an acknowledgment of the challenges ahead. While considerable progress has been made in MES development, the journey toward the MES of the future is far from complete. That said, the group left the session energized, with a shared commitment to pushing the boundaries of what MES can achieve. 

The “MES of the Future” session at MES Berlin highlighted both the progress and the challenges on the road to advanced MES deployments. From balancing capacity growth with standardization to leveraging AI/GenAI, the discussion covered a broad spectrum of critical topics shaping the future of manufacturing. As industries continue to adopt innovative technologies, there’s a shared understanding that while we’ve made great strides, there is still much work to be done. We’re excited to be on this journey and would love to connect with others who are passionate about MES and the future of manufacturing. Feel free to reach out to discuss further or share your own experiences. 

Authors

Brian Eden

Vice President, Global Life Sciences Technical Operations Leader, Capgemini

Laurent Samot 

Vice President, Head of Smart Factory / Digital Manufacturing 
As global head of the COE Smart Factory, Laurent is working with our digital manufacturing practices to implement the fourth industrial revolution: Industry 4.0.