Why Addressing Data Complexity in Pharmaceutical Manufacturing Is Critical

Damien Fellowes | January 17, 2025 | 11 minute read

Why Addressing Data Complexity in Pharmaceutical Manufacturing Is Critical

Master Data Management Blog by Stibo Systems logo
| 3 minute read
January 17 2025
Why Addressing Data Complexity in Pharmaceutical Manufacturing Is Critical
7:14

In pharmaceutical manufacturing, data is more than an operational tool – it’s a cornerstone of compliance, efficiency and innovation. Yet, as the industry grows more complex, the data journeys behind key processes reveal unique challenges that demand attention.

Below, we explore some of the critical data-related challenges facing pharmaceutical manufacturing today and why addressing them is essential to ensure the industry’s continued success.

Data challenges in pharmaceutical manufacturing

  1. Aligning mass balance data across interoperable systems

Mass balance equations are fundamental to ensuring inputs, outputs and losses are accurately accounted for in pharmaceutical production. This requires seamless interoperability between MES, LIMS and ERP systems. However, misaligned or fragmented data can compromise compliance and operational accuracy.

Why it matters: Without accurate mass balance data, discrepancies can arise, leading to inefficiencies, regulatory issues or even halted production. Achieving unified data flows across systems ensures every material and process is accounted for with precision.

  1. Decentralizing product data for localized market needs

Pharmaceutical products often require adjustments for regional markets, such as different excipients or packaging standards. Managing decentralized product data while maintaining consistency for global oversight is critical to avoiding duplicative regulatory processes.

Why it matters: When product data isn’t managed effectively, manufacturers may face delayed approvals, increased costs and misaligned compliance efforts. A smooth data journey ensures local regulatory requirements are met without disrupting global consistency.

  1. Enabling local sourcing while managing perishable ingredients

Sourcing perishable raw materials locally introduces challenges in ensuring the right materials reach the right production sites while meeting stringent quality and compliance standards. Data errors can result in costly waste or production delays.

Why it matters: Managing ingredient data accurately helps manufacturers balance local flexibility with global compliance, reducing risks associated with the perishability and regulatory requirements of raw materials.

  1. Integrating real-time data for adaptive manufacturing

Continuous manufacturing and adaptive processes are becoming more prevalent in the pharmaceutical industry. Real-time data from IoT sensors, PAT systems and automation tools must be seamlessly integrated to enable dynamic adjustments during production.

Why it matters: Adaptive manufacturing depends on reliable, real-time data to optimize processes, reduce waste and maintain consistent product quality. Fragmented or outdated data can undermine these efforts.

  1. Harmonizing shelf-life variability across global supply chains

For biologics and other temperature-sensitive products, shelf life can vary based on storage and transportation conditions. Tracking these variables in real time and adjusting expiration dates dynamically is essential to minimizing waste and maintaining compliance.

Why it matters: Data-driven shelf-life management ensures products are distributed efficiently and remain effective, reducing spoilage and enhancing supply chain agility.

The broader importance of master and reference data management

Each of these challenges highlights the critical role that master data – and aligned reference data – play in pharmaceutical manufacturing. Master data serves as the foundation for consistent, accurate and reliable information, ensuring that key business processes – from compliance tracking to adaptive manufacturing – are based on a single source of truth.

Reference data, when tightly linked to master data, provides the contextual framework necessary for compliance and interoperability. For example:

  • Mass balance equations: Accurate master data ensures that raw materials, batch records and production outputs are consistently tracked. Reference data, such as unit conversions or material classifications, ensures that data from different systems speak the same language.
  • Localized product data: Master data underpins global product definitions, while reference data helps navigate regional regulatory requirements by providing the context needed for local adaptation.
  • Ingredient traceability: Master data governs the sourcing, movement and use of perishable ingredients, while reference data, like compliance standards and shelf-life parameters, supports decision making at every stage of the supply chain.

Example: Data migration for ERP modernization in a hybrid framework

Consider a pharmaceutical company undertaking an ERP modernization project to transition from a fully centralized data environment to a hybrid centralized-decentralized framework. This shift is designed to enable more localized decision making, such as sourcing region-specific ingredients or complying with local regulatory standards, while still maintaining global oversight.

Master data management (MDM) becomes pivotal in this scenario, not only during the migration process but in establishing a framework for sustainable data governance afterward. Centralized master data ensures that critical global standards – such as product definitions, compliance records and quality metrics – are upheld. Simultaneously, aligned reference data allows for regional flexibility by supporting localized material specifications, regulatory classifications and language-specific product descriptions.

This hybrid approach ensures that:

  • Global consistency is preserved: Centralized master data prevents duplication, inconsistencies or compliance gaps across regions.
  • Local adaptability is enhanced: Decentralized reference data provides the contextual flexibility needed for region-specific operations, enabling faster compliance and reducing costs associated with reapprovals.
  • Operational efficiency is increased: Data flows seamlessly between centralized and decentralized systems, reducing errors, enhancing traceability and supporting strategic decision making.

By establishing robust master data and aligning it with reference data, pharmaceutical manufacturers can:

  • Maintain compliance across diverse regulatory frameworks
  • Enable seamless integration between siloed systems
  • Reduce costly errors in production, sourcing and distribution
  • Support innovation with reliable data foundations for adaptive manufacturing

Investing in effective master and reference data management isn’t just an operational improvement, it’s a strategic enabler that drives precision, efficiency and resilience across the entire pharmaceutical manufacturing lifecycle.

Looking ahead: Tackling data complexity together

Pharmaceutical manufacturing faces growing pressures from regulatory bodies, consumers and internal stakeholders alike. Addressing these unique data challenges head-on will enable manufacturers to not only meet these demands but thrive in a competitive and ever-evolving industry landscape.

The pharmaceutical industry is becoming more digitally enabled and data intensive. Building a digital supply chain requires harvesting data.

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Damien’s career started out in manufacturing nearly 25 years ago, involving many aspects, from operations to sales, logistics, and distribution. He is driven to solve the challenges within the industry using technology which has led him to leverage his experience in solutions consultancy for manufacturing, architecture, building management, and automotive. Today, Damien works for Stibo Systems as the manufacturing practice lead for the EMEA region.

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