The average cost to bring a new drug to market is $1.3 billion dollars. That’s no light figure. With median gross profits predicted to be around 76%, the potential ROI per drug is a blank check for pharma companies and their investors. What impacts this number and the success of the drug development is largely dependent on the data produced- how it is collected, stored and used. Ignoring MDM is not just going to cost pharma development in terms of loss of revenue, but it has far wider implications if they get it wrong. For example, getting a recipe wrong could be fatal. In this blog, we will explore the importance of this often-overlooked area and the importance it holds in modern pharma.
What is master data in the pharmaceutical industry?
In the pharmaceutical industry, master data management (MDM) is like keeping all important information in one place. It helps everything run smoothly by making sure everyone has the right data at the right time. This means fewer delays and better decisions, which is crucial for the production of medicines. This all sound fairly straight forward, but for this industry, the implications run much deeper.
For life science companies, master data isn’t just an efficiency question, it’s a regulatory one. The MHRA expects the same standard of accuracy and traceability that underpins Good Distribution Practice (GDP) and the wider GxP framework covering how medicines are manufactured, tested, and distributed. When a regulatory submission or an audit asks where a batch came from, what it contains, and who touched it along the way, the answer comes from your master data, not from a system’s ability to process a transaction quickly. Inaccurate or inconsistent product, batch, or supplier data doesn’t just slow the business down, it creates genuine compliance exposure.
Pharma master data in SAP: specific challenges
Pharma and life sciences organisations running SAP face master data challenges that go beyond what most industries deal with, largely because the data itself carries regulatory weight.
- Batch management. Every batch needs to be traceable end to end, from raw material through to finished product, which means batch master data has to be accurate and complete before manufacturing even starts, not corrected after the fact.
- Unit-level serial numbers for tracking individual packs through the supply chain depend entirely on clean, consistent product master data underneath them. Get the product master wrong and serialisation data inherits the same errors at a much larger scale.
- Product lifecycle management. Pharma products go through distinct regulatory stages, development, trial, approval, commercial, that all need to be reflected accurately and consistently in master data as the product moves through them.
- Material and supplier master complexity. Life sciences supply chains involve more regulatory detail per material and per supplier than most industries, certifications, approved manufacturing sites, and audit history all need to sit alongside the basic material or vendor record, not in a separate spreadsheet somewhere.
S/4HANA and the 2027 deadline
Pharma organisations still running ECC face the same 2027 mainstream maintenance deadline as everyone else, but with less room for error. Batch and serialisation records that have accumulated inconsistencies over years of ECC use need proper cleansing before they move into S/4HANA, since carrying regulatory-relevant errors into a new system doesn’t just create operational problems, it creates compliance ones. If you’re planning that move, our SAP S/4HANA migration guide covers the approaches and the data preparation work in more detail.
Six benefits of MDM in pharmaceuticals
1. Regulatory Compliance: MDM ensures that pharmaceutical companies maintain accurate and consistent data, aiding them in complying with stringent regulatory requirements imposed by authorities such as the MHRA or EMA.
2. Data Volume and Complexity: With vast amounts of data generated across the pharmaceutical supply chain, MDM helps in managing the volume and complexity of this data by organising it systematically, making it easier to access and analyse.
3. Operational Efficiency: By centralising and standardising data across various departments and systems, MDM streamlines operations, reduces redundancies, and improves overall efficiency in processes such as drug development, manufacturing, and distribution.
Check out how Maextro can support directly with manufacturing master data management here.
4. Data Quality: MDM ensures data accuracy, completeness, and consistency by establishing data governance policies and data stewardship practices. This high-quality data is essential for conducting reliable research, clinical trials, and ensuring patient safety.
5. Cost Reduction: Through improved data management practices, pharmaceutical companies can reduce costs associated with data errors, redundant processes, and compliance violations. Additionally, MDM helps optimise inventory management, leading to cost savings in supply chain operations.
6. Better Decision Making: With reliable, up-to-date, and well-managed data, pharmaceutical companies can make informed decisions regarding drug development, marketing strategies, supply chain optimisation, and risk management, ultimately leading to better business outcomes.
Master data management ROI in pharma
How soon can you start? That’s the simple answer for achieving an ROI on master data management in pharma. Why? Because the main tools are already sitting in your business ecosystem- the data. As soon as an MDM solution is deployed, and processes and rules are configured you can begin leveraging this untapped resource. Once you start, immediate benefits will be noticed in decision-making, supplier relations, customer insights, clinical trials and recipe management.
Typical issues with master data management in Pharma.
1. Data Fragmentation: Pharmaceutical companies often struggle with fragmented data spread across multiple systems, departments, and geographic locations, leading to inconsistencies and difficulties in data integration.
2. Data Quality Challenges: Maintaining data accuracy, completeness, and consistency is a significant challenge in the pharmaceutical industry due to the high volume and complexity of data, as well as the need to comply with strict regulatory standards.
3. Integration with Legacy Systems: Many pharmaceutical companies have legacy IT systems that are not designed to support modern MDM practices, making it challenging to integrate and centralise data effectively.
4. Regulatory Compliance: Meeting regulatory requirements such as those set by the FDA, EMA, or other health authorities adds complexity to MDM initiatives, as pharmaceutical companies must ensure that their data management practices align with regulatory standards.
5. Complex Data Relationships: Pharmaceutical data often involves complex relationships between products, ingredients, formulations, clinical trials, regulatory filings, and safety information. Managing these interdependencies requires sophisticated MDM capabilities.
6. Data Security and Privacy: Pharmaceutical data is highly sensitive and subject to strict data security and privacy regulations. Ensuring data security while maintaining accessibility and usability presents a significant challenge for MDM implementations.
7. Organisational Resistance: Resistance to change within organisations, coupled with the complexity of implementing MDM across departments and business units, can hinder the success of MDM initiatives in the pharmaceutical industry.
FAQs
What is pharmaceutical master data management?
Pharmaceutical master data management is the discipline of governing core data, products, batches, materials, and suppliers, so it stays accurate, consistent, and traceable across the organisation, supporting both operations and regulatory compliance.
How does MDM help with MHRA compliance?
MHRA compliance depends on being able to demonstrate accurate, traceable records for products, batches, and suppliers. Effective master data management ensures that data is consistent and complete before it’s needed for a submission or an audit, rather than being reconstructed under pressure afterwards.
What are the master data challenges in pharma?
Common challenges include maintaining accurate batch and serialisation records, managing product data consistently across lifecycle stages, and handling the additional regulatory detail, certifications, approved sites, audit history, that material and supplier records carry in life sciences compared to other industries.
How does SAP support pharma data management?
SAP provides the underlying structures for batch management, material master, and supplier master data, but it doesn’t guarantee data quality on its own. Governance tools and processes are still needed to keep that data accurate and audit-ready, particularly for organisations migrating from ECC to S/4HANA.
How can Bluestonex help?
Our signature MDM solution, Maextro, addresses typical pharmaceutical MDM challenges by offering a unified platform for data integration, quality management, and compliance. Maextro’s capabilities include data consolidation to reduce fragmentation, data cleansing and validation for improved quality, and seamless integration with legacy systems. It ensures regulatory compliance through audit trails and reporting features while managing complex data relationships and prioritising data security with encryption and access controls. Maextro’s user-friendly interface and customisable features facilitate adoption and collaboration, ultimately enabling pharmaceutical companies to leverage MDM benefits such as operational efficiency, cost reduction, and better decision-making. Explore Maextro here.
Master Data is an underpinning essential for many industries. Check out its impact in another now in our blog about Manufacturing Master Data
