Develop a stepwise long-term roadmap

It of course makes sense to start out in developing digital twins by addressing repetitive pain points or strategic issues, because that’s the quickest way to see results. But it makes sense at the same time to put a roadmap in place. This will help the organization identify the gaps in each function of the organization, and the enablers (such as data management and skillsets) that will be needed to plug those gaps. The roadmap can also scope anticipated value and sustainability outcomes.

Set up well-balanced governance

While it’s true that digital twins can and should be designed to address the key issues first, that doesn’t mean the approach should be piecemeal. A well-planned governance structure that covers the management of all the digital twins used by an organization helps to avoid developments descending into chaos, and introduces and sustains a necessary level of consistency.

Strengthen enablers for scaling

The foundations on which the scaling of digital twin deployments should be built are consistent with the principles of the Frictionless Enterprise . They are as follows:

• Secured connectivity – to ensure continuity of information from edge to cloud, from design to operations and services
• Data management – digital twins need to mine, model, simulate, predict, and monitor effectively, which necessitates integration with multiple data sources. Scaling makes this harder still, and so organizations must develop a data management strategy to qualify the right data; to understand the data flows across various systems and processes; and to transform the data into actionable insights
• Capabilities – organizations will also need to strengthen skillsets in areas including design and operations. Given the importance of removing friction from the equation, building collaborative skills all along the value chain, across both internal and external ecosystems, is also a prime requirement
• User experience and user interface – an intuitive UX/UI is necessary to exploit the full potential of smart, connected systems and processes in the field.

Anticipate and enable end-to-end integration

As we’ve seen in principle, the transformation that digital twins can bring to business processes is predicated on cohesiveness – on removing friction beyond the immediate scope of the twin. In practice, and to anticipate and enable this goal, what’s needed is a single and up-to-date source of truth, federating:

• Cold data (such as historical information, system specifications and models)
• Hot data (such as IoT data, operational data, and real-time events)
• Descriptive data (such as GISs)
• Transactional data (such as ERP)

Digital twins are an the technology-agnostic concept. The approach to implementing a digital twin should be flexible, and should be able to offer advanced data services such as: modeling and simulation, intuitive visualization, analytics and AI/ML, and event orchestration services to efficiently manage predictive/preventive alerts or real-time incidents.

Enhance data security and privacy

Digital twins replicate real-world systems, and hence are privy to operational and possibly strategic information that may be highly sensitive. Unauthorized access to this information could compromise not only the performance of the twin, but the integrity of business functions. Communication between the twin and its physical counterpart therefore needs to be absolutely secure – which is why almost three-quarters (73%) of respondents to the CRI report said they were making changes to their end-to-end cybersecurity to accommodate digital twins.

Empower the ecosystem

A fully frictionless model encompasses enterprise processes from end to end – but it also extends beyond that, and out into the organization’s ecosystem of suppliers, technology partners, and customers. The greatest value of a digital twin comes from being able to predict or simulate the impact of a particular change on this entire network of partners.

Droughts, famine, plague, floods storms, heat, new diseases are all caused by climate change and all impact business cash flow. Sustainability mitigates against external risks – a company that doesn’t is exposed . This is possible only when data or inputs from or about partners can be fed into the digital twin, which is why it’s a good idea for organizations to include their partners in the process.

The ultimate digital twins?

In summary, then, building a digital twin into a frictionless business model means that it can more accurately reflect real-world scenarios, because it is responding not just to the immediate circumstances it is being designed to address, but to entire function of which it forms part – whether that be HR, customer operations, finance, or processes in the physical world, such as manufacturing or supply chain operations.

In fact, digital twins may in time be able to go even further. The CRI report tells us that work is under way to create a digital twin of the entire planet, to help combat climate change by simulating the atmosphere, the oceans, and also human systems. If that’s possible, then creating a digital twin of an entire global enterprise is surely also only a matter of time.

To learn more about how implementing a digital twin can help your organization to drive improved business operations and transition to the Frictionless Enterprise, contact: mariia.nalapko@capgemini.com  

Twenty years ago, we bought mobile phones for their hardware. Since then, a lot has changed, and now, embedded software delivers the primary value – offering entertainment, navigation, augmented reality, productivity apps, and so on.

However, such software does not work alone. It requires the phone’s hardware (connectivity, cameras accelerometers, etc.), and a cloud ecosystem to download new apps and share data. But it is the software – the operating system and firmware on the phone – that runs the show.

As a result, consumers now have sky-high expectations of technology. And if industrial companies can’t deliver products with a similar software-driven user experience, they will lose these customers. Manufacturers of cars, planes, trains, satellites, solar panels, cameras, home appliances, and so on are all undergoing a similar shift driven by embedded software.

That shift has huge implications – not just for the product itself, but for the company designing it.

Ever more products become software-driven

Let’s start with the product. Take a car or a plane – products that are increasingly software-driven. Both are developing software for automation and route optimization on the one hand, and to improve user experience and entertainment on the other.

They are not alone. Trains need one type of software with smart signal controls for optimal route planning, and another type that allows users to order food from the buffet car on their phone. Satellites must make real-time decisions about trajectory, data capture, and energy management. In-home batteries must control energy in and out, and track what they sell back to the grid.

Embedded software drives a change in organizational thinking

Embedded software is not entirely new in these industries – cars and planes, for example, have long had bits of control software. But its scale and sophistication are now skyrocketing.

A ��ѻ��ý Research Institute (CRI) survey – of 1,350 $1bn+ revenue companies with goals to become software-driven – found software accounted for 7% of revenue in 2022, but was expected to rise to 29% by 2030. That same report also found that 63% of Aerospace & Defense organizations believe software is critical to future products and services, with industries from automotive to energy making comparable claims.

But getting there will mean some big changes at these organizations.

Unlike a phone – which was designed to be a single integrated device – cars, planes, satellites, drones and other industrial systems were originally designed with multiple ECUs (electronic control units), each running multiple pieces of software. Each ECU was developed separately by different parts of the organization.

But now there is a need to integrate everything. For example, autopilot won’t work if its underpinning software can’t communicate seamlessly with the separate control units for sensors, steering, and brakes.

The importance of transversal software

Doing this in the current siloed way would create unmanageable complexity. Software needs to be ‘transversal’ – ie. developed consistently across the organization, rather than in silos. There must be a centralized team defining strategy, and managing and developing embedded software as a product across the organization. This must all be done with the same standards to facilitate interoperability, scalability, upgrades and reuse – whether it’s a landing control system, energy management system, in-flight infotainment, or smart cockpit. This transversal operating model makes software teams the backbone of software-defined organizations, continuously developing software solutions across the company.

That doesn’t mean all software must be connected to the final system, or that everything will be developed in the same way. Software can be very different. For example, rear-seat entertainment software can offload some data-heavy functions to the cloud, and developers can launch beta versions to get user feedback. On the other hand, high-integrity software for braking must do everything on board, work every time, and be separate from any hackable entry points into the system.

There are separate development tracks for different software components, so that less safety-critical software can quickly get to market, while more safety-critical parts can be carefully managed through verification and validation (V&V), and certification. But all development tracks should be within a centralized software team, which works together, sharing a consistent system architecture, standards and learnings, and creating products the entire business can access once complete.

A positive example

Consider Stellantis, which owns multiple car brands, including Opel, Peugeot, Dodge and Fiat, among others. It has invested in developing three core software platforms: one which is the backbone of the car (STLA brain), one for safety-critical assisted driving (STLA AutoDrive), and one for the connectivity and cockpit services (STLA SmartCockpit).

It implemented centralized software standards that are systematically used across all brands and models. This is similar to a trend we’re seeing across all markets – ‘platforming’. The platforming approach leverages generic components (computer vision, voice command, navigation services, etc.) that are applied to several projects, products and use cases – sometimes used with customizations to different brands and marketings – all without needing to build, test and certify everything from scratch.

Innovate or fail

All of this requires a major shift in thinking from organizations. But they must make this shift to survive.

And largely, they are. The auto industry is taking the threat from Tesla (and its advanced on-board computing) seriously. They may soon be pushed to move faster by software-driven Chinese competitors, like BYD and Nio, whose car interiors can transform into immersive cinemas at the push of a button. Industries from aviation to energy are no longer complacent – all recognize that embedded software is critical to their future. And all know they must undergo radical organizational change to turn legacy hardware into future-proof, software-driven products.

See how embedded software is helping industries transform their business – and how ��ѻ��ý can help along your journey.

The key challenge? Bridging the gap between consumers’ good intentions and their purchasing behavior. By integrating sustainability into the everyday shopping experience, brands can influence buying decisions and accelerate both their sustainability goals and profitability.

In today’s economic climate, practical concerns like price and convenience often overshadow sustainability during the shopper journey—despite widespread agreement on its importance. So how can companies continue to advance their sustainability agenda, and achieve growth and profitability goals, when many consumers are unwilling or unable to pay a premium for it?

The solution isn’t to convince everyday shoppers to shift left, but to make sustainability a central part of the everyday shopping experience for the “mainstream middle”.

This creates an action-intention gap, wherein mainstream middle shoppers would like to buy sustainable products more often, but their purchases are more influenced by other factors, like cost. So how do brands and retailers move that agenda forward?

Three ways to jumpstart sustainability goals in retail

1. Encourage sustainable shopping and healthy choices through education and guidance

For the average consumer, sustainability is a complex and potentially confusing topic.

Our 2025 consumer data revealed that almost two-thirds of shoppers (63%) report insufficient information to verify sustainability claims, while 54% say they do not trust those claims.

The good news is that consumers want more guidance and input from retailers throughout the shopper journey to help them make more informed choices. Brands and retailers have the opportunity to stand out to consumers by improving transparency around sustainability claims, such as through standardized certifications, easy-to-understand labels, or transparent packaging.

For example, front-of-pack nutritional labeling systems—such as Nutri-Score (used in several European countries), the Traffic Light system in the UK, and the Keyhole label in Sweden—are helping consumers make healthier food choices by leveraging standardized algorithms to assess both positive and negative aspects of a product’s nutritional content. A similar approach could be applied to sustainability labeling, simplifying complex claims and supporting consumers in making more informed, responsible decisions at a glance.

Core retail mechanics can also play a crucial role in making sustainable and healthy choices more accessible to consumers. Tactics like strategic product placement, targeted promotions, educational displays, and local produce partnerships can help guide shoppers toward better choices without requiring them to go out of their way.

By making sustainable and healthy choices clearer and more accessible, it becomes a more justifiable choice, especially among price-conscious consumers.

2. Leverage AI and technology: AI in sustainability to engage consumers

Digital technology has an important role to play in making sustainability more understandable, accessible and tangible to consumers. This is definitely the case for Gen Z, who have grown up with digital, and who are now gaining more mainstream spending power.

For example, 2D barcodes on products can help brands share sustainability details beyond what fits on labels or packaging. By simply scanning a code with their phone, shoppers can “talk” to a product—enabling them to learn about its origins, ingredients, and certifications, or even engaging in a two-way dialogue with a brand.

L’Oréal is one notable trailblazer on this front. The brand has integrated QR codes on its skincare and cosmetic products, directing consumers to an AI-powered chatbot that offers detailed ingredient information, usage guidance, and personalized skincare routines tailored to each user’s skin type and concerns.

Our research showed strong demand among consumers to be able to connect with brands in this way. Overall, 65% of consumers want “rapid verbal responses from AI chatbots.” This highlights a prime opportunity for companies to embed sustainability messaging into natural language interactions, such as via AI assistants, voice search, or digital assistants.

On the supply chain side, increasing transparency, especially in light of upcoming regulations in various regions, presents a major opportunity for retailers. By leveraging technologies such as electronic labeling and digital product passports, they can offer consumers clear visibility into every stage of a product’s journey, from how it was grown or sourced to how it should be responsibly disposed of.

3. Incentivize behavior change: Smart grocery shopping and eco-friendly packaging

Brands and retailers can encourage more sustainable shopping habits by making them more affordable, accessible, convenient, and rewarding.

For example, smart dynamic pricing that encourages and incentivize consumers to purchase food before it goes to waste not only benefits shoppers—it also boosts retailer margins and advances sustainability goals.

Minimizing food waste is an issue that is being actively embraced by many retailers and grocers around the world precisely because of its double benefit for the consumer and the business. For example, Carrefour has extended its collaboration with Wasteless in Argentina, rolling out to enable dynamic discounting of perishable products. This collaboration aims to drastically reduce food waste, while lowering markdown costs by 54%. At the same time, it also offers consumers fresh products at low prices.

Reducing food waste can also be an in-home activity. In the Netherlands, Albert Heijn is piloting a “” feature within their mobile app. The “leftover scanner” allows consumers to snap a photo of their refrigerator contents and receive recipe suggestions based on what they already have. The retailer also launched its app, to help customers make smart choices and adopt healthy behaviors. The app provides personalized advice, inspiration, and wellness challenges across key areas like nutrition, exercise, relaxation, and sleep.

Leveraging sustainability as a revenue driver

For retailers and brands, sustainability isn’t just an exercise in altruism. Setting aside the fact that it is a real imperative to our collective future and the overall health of people and planet, companies should also recognize that sustainability can be a top-line growth driver.

In fact, found that sustainable products are not only capturing a larger market share but also growing at a faster rate compared to their non-sustainable counterparts. Despite high inflation, sustainable products held 18.5% of the market in 2024, up 1.2 percentage points from 2023. Products with environmental, social, and governance (ESG) claims saw a 5-year CAGR of 9.9%, outperforming conventional products.

Overall, sustainability-marketed products accounted for about one-third of all CPG growth, despite representing less than 20% of the market share, showcasing a significant opportunity for brands in a challenging economic climate.

The key to scalable sustainability: Engaging the mainstream majority

The path to a more sustainable future isn’t about changing people’s beliefs and priorities—it’s about removing barriers to make responsible choices the default option for everyone. By making sustainability more accessible, convenient, affordable, and seamlessly integrated into daily life, brands and retailers can influence the behavior of everyday consumers—and earn their loyalty in return.

And that’s how sustainability will become a mainstream practice.

For more information about how ��ѻ��ý can help your organization accelerate sustainability goals and programs, please contact our authors and visit our Connected Society.

The rapidly evolving landscape of digital health was the focus of a recent digital health leadership panel hosted by ��ѻ��ý. This session brought together thought leaders from major pharmaceutical organizations, including Emre Ozcan, SVP of Digital Health & Devices at Merck KGaA; Mads Hofman-Thaysen, VP Head of Digital Health Solutions at Novo Nordisk; Ken Tubman, Head of Patient Digital Solutions & SaMD at Takeda; and Sonny Shergill, VP of Commercial Digital Health at AstraZeneca.

Moderated by Geoff McCleary, ��ѻ��ý’s Global Head of Connected Health, the discussion centered on overcoming challenges and seizing the opportunities in digital health to drive transformation in patient care and pharmaceutical innovation.

The role of digital health: A foundational shift

Digital health in the pharmaceutical industry is experiencing its “at scale” moment, as leading companies strategically transition from isolated initiatives and regional triumphs to comprehensive, enterprise-wide digital ecosystems. This transformation enables the seamless integration of diverse digital health programs across multiple regions, therapeutic areas, and a broad portfolio of drug and device assets.

By leveraging scalable technologies such as advanced data analytics, artificial intelligence, and interoperable platforms, pharma companies can enhance collaboration, streamline operations, and deliver personalized patient experiences on a global scale. As a result, digital health is transitioning into a key strategic resource for pharmaceutical firms to better position themselves to respond to diverse market needs, optimize resource allocation, and sustain long-term growth.

In the panel discussion, the industry experts were unanimous in their agreement that digital health has shifted from being a supplementary tool to becoming a foundational pillar of their organizations’ strategies. Ken Tubman of Takeda remarked, “The key to advancing digital health is creating personalized and predictive solutions that truly resonate with patients and their needs.” He emphasized that digital health is not merely an enabler but a core growth engine, deeply embedded in Takeda’s identity as a “digital biopharma” leader.

Mads Hofman-Thaysen of Novo Nordisk highlighted a strategic transition from standalone apps to integrated care platforms. “Integrated care solutions, not just standalone apps, are the future of scalable and impactful digital health,” he explained. This approach enables organizations to address broader therapy areas and focus on enhancing patient outcomes rather than delivering isolated product benefits. It reflects a commitment to building cohesive systems that support patients throughout their care journeys, from pre-diagnosis to long-term wellness.

Sonny Shergill of AstraZeneca reinforced this perspective, noting that digital health has become foundational across therapy areas. He described its role in enabling personalized engagement and leveraging advanced analytics to unlock new insights. According to Shergill, “Biometric data powered by AI can transform patient outcomes and unlock the future of predictive healthcare.” This transformation aligns with AstraZeneca’s broader goals of improving patient outcomes and delivering innovative healthcare solutions.

Overcoming challenges in 2025

Despite its promise, the panelists acknowledged significant challenges that must be addressed to unlock the full potential of digital health. These barriers span technology, regulation, adoption, and data governance.

1. Adoption and scaling: Hofman-Thaysen identified adoption and scalability as persistent hurdles, noting the difficulty in rolling out solutions to large patient populations while adapting them to local markets. “Global solutions that adapt to local markets allow us to address diverse healthcare needs without compromise,” he explained. This tension between global standardization and local customization remains a critical challenge for digital health innovators.
2. Regulatory complexity: Regulatory hurdles are a major barrier to progress. Emre Ozcan of Merck KGaA highlighted the disparities in regulatory environments, with the US often being more open to digital therapeutics than Europe. He stated, “When regulation is unclear or absent, the system becomes paralyzed, hindering progress and innovation.” Clearer guidelines would streamline processes and accelerate the adoption of new technologies, the panelists agreed.
3. Data utilization and governance: Both Shergill and Tubman emphasized the importance of robust data strategies. Shergill remarked, “A robust data strategy is essential to scaling meaningful digital health innovations.” Tubman echoed this sentiment, highlighting the need to turn aggregated data into actionable insights. Effective data governance, they agreed, is crucial to unlocking the full potential of digital health.

Opportunities driving the future of digital health

While challenges persist, the panelists explored transformative opportunities poised to redefine the industry. These opportunities span cutting-edge technologies, innovative care models, and strategies for global impact.

1. Generative AI and hyper-personalization: Generative AI was highlighted as a transformative tool for personalization. Ozcan described its potential to create tailored digital therapeutics, stating, “Generative AI will transition apps from generic solutions to tools built specifically for individual patients and their needs.” This innovation promises to enhance patient engagement and improve outcomes across diverse conditions. By leveraging AI’s capabilities, organizations can deliver highly individualized care that resonates deeply with patients.
2. Biometric data and predictive analytics: Shergill and Hofman-Thaysen underscored the untapped potential of biometric data. According to Shergill, advancements in AI will help organizations to predict patient outcomes with more precision. Hofman-Thaysen added that AI-powered diagnostics could enable holistic care solutions, revolutionizing the way diseases are identified and managed. These advancements have the potential to significantly improve both patient outcomes and clinical decision-making processes.
3. Remote monitoring and digital biomarkers: Tubman and Ozcan pointed to remote patient monitoring and digital biomarkers as game-changing opportunities. Tubman shared a compelling example from Parkinson’s care, where sensor data provides real-time insights into tremor patterns, benefiting both patients and healthcare providers. Ozcan remarked, ”Digital biomarkers eliminate adoption barriers and unlock the potential for predictive and personalized medicine.” These tools, when integrated into care pathways, can revolutionize how patients interact with their healthcare systems. 

Patient-centricity: Meeting patients where they are

A recurring theme throughout the discussion was the need for patient-centric digital health solutions. Panelists emphasized designing tools that integrate seamlessly into patients’ lives and care pathways, ensuring accessibility and relevance. These solutions must not only be intuitive but also tailored to address the unique challenges patients face, such as managing chronic conditions or navigating complex healthcare systems. By aligning digital tools with real-world patient behaviors, organizations can foster greater engagement and adherence to treatments.

Accessibility, the panelists noted, involves addressing barriers such as technological literacy, device compatibility, and socioeconomic disparities. Ensuring equitable access allows digital health innovations to be impactful across diverse populations and varied healthcare environments. This holistic approach establishes a foundation for improved health outcomes on a global scale.

Hofman-Thaysen emphasized a shift from standalone apps to modular, integrable solutions. “Meet patients where they are with solutions that fit into existing ecosystems,” he advised, underscoring the importance of accessibility and equity in digital health design. By embedding tools into established systems, companies can reduce friction and encourage broader adoption.

Shergill expanded on this, noting that patients increasingly expect personalized, equitable care experiences. “Patients will leverage their health data to inform decisions about their care,” he said. Panelists agreed that patient empowerment through digital tools will remain a central focus in the coming years.

Conclusion: A vision for 2025 and beyond

The ��ѻ��ý digital health advisory panel offered a forward-looking roadmap for addressing challenges and leveraging opportunities in 2025. Through a combination of innovative technologies, patient-centric design, and collaborative approaches, the industry is poised to redefine healthcare delivery.

As Ozcan aptly summarized, “Generative AI and digital biomarkers are the game changers that will redefine personalization in healthcare.” The insights shared by the panelists reflect a collective optimism and a shared vision for a future where digital health solutions enhance care, improve outcomes, and transform lives globally.

��ѻ��ý is a leader in the digital health space and constantly works with leaders across the industry to help understand and shape the conversation, drive progress, and foster innovation in digital health. By staying ahead of trends and championing collaborative innovation, ��ѻ��ý solidifies its role as a catalyst for change in the digital health revolution.

Want to learn more about how digital health can drive transformation in patient care and pharmaceutical innovation?

Visit ��ѻ��ý’s Connected Health

This year’s event marked a noticeable shift from the excitement of previous years to a more grounded and realistic approach to the advancements in AI and biotechnology. We had a great time at the event and are excited to share our key takeaways with you.

1. The Realization of AI’s Potential

One of the standout themes at BioTechX 2024 was the real progress in AI, especially Generative AI. Last year, we were all about the potential of large language models and generative AI. This year, it was all about real-world applications and measurable impacts. For example, a keynote presentation showcased a generative AI platform that’s been scaled up, boosting efficiency by 10-20% for its 15,000 users. This shift from theoretical potential to practical implementation was a recurring theme throughout the event.

2. The Importance of Trustworthy Data

As organizations continue to explore AI applications, the emphasis on trustworthy data has never been greater. Several sessions highlighted that the success of AI models in life sciences heavily depends on reliable data. While defining and obtaining trustworthy data is challenging, there were successful examples where robust data foundations led to significant advancements. The consensus was clear: without trustworthy data, AI models can’t reach their full potential.

3. The Role of Multi-Agent Systems

Another hot topic was multi-agent systems. It’s clear that the future of AI in life sciences involves multiple specialized AI models working together. This approach, known as agentic AI, uses a suite of models, each with its own specialization, to tackle complex scientific workflows. This method not only enhances AI efficiency but also addresses the unique challenges of life sciences research.

4. The Need for Pragmatic Approaches to FAIR Data

Discussions also touched on the need for pragmatic approaches to FAIR (Findable, Accessible, Interoperable, and Reusable) data. While everyone agrees on the importance of FAIR data, achieving perfect FAIRness isn’t always practical. The key takeaway was that data should be FAIR enough to be functional and useful, without overcomplicating the process.

Stay tuned for our next blog, where we’ll dive deeper into our panel discussion on FAIR data.

5. The Future of Quantum Computing in Drug Discovery

Quantum computing was another exciting topic at the event. While it is still seen as a technology with a 5 to 10-year horizon, its potential to revolutionize drug discovery was widely discussed. Quantum computing is expected to solve problems that current technologies cannot, offering new ways to understand and manipulate biological systems. However, it was also acknowledged that quantum will be more complementing rather than replacing existing technologies. One takeaway is that we have to think about how to combine classical technologies and high-performance computing (HPC) cleverly with quantum technologies and think out of the box to achieve revolutionary advancements.

In addition to its potential, the event highlighted various use cases and benchmarks of existing quantum algorithms and hardware. These discussions underscored the significant hardware development needed to address interesting use cases in the pharmaceutical industry. Nevertheless, it is crucial to start now. Beyond hardware advancements, there is a substantial amount of work required on the implementation side, such as developing effective error correction strategies. On the software side, optimizing quantum algorithms is essential to achieve these goals as soon as possible.

6. Addressing the Productivity Crisis in R&D

No it’s not new, but a recurring topic at BioTechX 2024 was the ongoing productivity crisis in R&D. Despite increased spending, the number of new drug approvals has not kept pace (.). The event highlighted the need for innovative solutions to boost productivity while reducing costs. AI and other advanced technologies were seen as crucial to achieving these goals, with a focus on practical applications that can deliver measurable results.

Conclusion

In conclusion, BioTechX 2024 was a pivotal event that highlighted the shift towards realism and practical applications in the biotech and life sciences industries. The discussions underscored the importance of trustworthy data, the potential of multi-agent systems, and the future role of quantum computing. As the industry continues to evolve, these insights will be crucial in guiding future advancements and addressing the challenges ahead.

Current State of Pharma MES

Today, MES deployments and daily operations in the pharmaceutical industry are often siloed. MES usually operates separately from other critical systems like Enterprise Resource Planning (ERP), Quality Management Systems (QMS), and Laboratory Information Management Systems (LIMS). This separation creates a fragmented landscape, often requiring custom-built interfaces, and leads to several challenges:

• Integration: The lack of seamless connectivity means data flow is often interrupted, leading to inefficiencies and more manual work. Clients frequently struggle to understand and map their current system architectures, which hinders the overall effectiveness of MES.

• Data Accessibility: Extracting meaningful data from MES is another significant challenge. Current systems require substantial effort to retrieve and use data effectively. This often means shop floor personnel end up serving the MES system rather than the other way around, which is counterproductive.
• Complex Implementations: Implementing MES is a complex and time-consuming process. Traditional MES projects are resource-intensive and can take 12 to 24 months depending on the scope, making it difficult to bring value quickly. Additionally, the monolithic nature of typical MES deployments makes it hard to adapt to the specific needs and limitations of manufacturers.
• Compliance and Validation: Ensuring compliance with regulatory standards without slowing down deployment is another hurdle. The validation process can be lengthy and resource-intensive, which can delay the benefits of MES implementation.

Conclusion

While MES is indispensable for the pharmaceutical industry, its current state presents several challenges. Addressing these issues is essential for clients to fully leverage the benefits of MES and drive efficiency in their manufacturing processes.