In life sciences, integrity, authenticity, and reliability of data are paramount. The need for robust data supply, governance and delivery practices has never been more critical as organizations strive to deliver improvements to commercialization, accelerate new go-to-market models, enhance brand access and awareness, engage customers with more relevance, and gain new or predict future insights on a patient’s journey. This blog delves into the intricacies of data authenticity, highlighting key considerations and best practices that leaders should be aware of when assessing a reliable data partner.
The importance of transparency in data authenticity
From clinical to commercial, data authenticity is the cornerstone of effective decision-making. It ensures the information foundation is connected, consistent, accurate, and reliable, not just in the moment but in the future as well. Since our industry works to advance patient outcomes and surpass regulatory compliance, the significance of maintaining and improving data authenticity cannot be overstated. It is critical for data partners to have a clear and transparent long-term roadmap that addresses existing and emerging use cases. The roadmap should detail continuous investment in both new data sources and product innovations that are designed to support today’s business requirements, while also preparing to meet tomorrow’s business objectives.
The supplier roadmap
A robust and transparent data supplier roadmap reflects an ongoing commitment to stability and growth over time. This also enables a data partner to proactively address potential volatility generated by changing market dynamics while continuously evolving to support new use cases. It is critical that a supplier not only demonstrates this clear commitment to investing, but that they also communicate a clear pathway to organically increase coverage and comprehensiveness, and demonstrate an ability and willingness to innovate around the integration of non-traditional data sources.
Additionally, it's vital to ensure the supplier roadmap proactively addresses known data gaps, including, for example, new direct-to-consumer access points, site-of-care channels, medical claims coverage, and unique therapeutic area dynamics (e.g., oncology, obesity, neurology, etc.). A well-planned roadmap will address these gaps in the short and long term, so your foundation of information remains accurate and robust.
A data supplier that is unable to demonstrate and communicate a clear multi-year plan that addresses growth and change, including the potential loss of a key data source, or who relies solely on sourcing the majority of its panel from other data aggregators instead of primarily from direct sources, can jeopardize the integrity and continuity of the information foundation and lead to significant disruption in business continuity.
Considerations for aggregated data that is not directly sourced
When it comes to data sourcing, it’s important for pharmaceutical and medical device companies to understand the proportion of data coming from third-party aggregators versus direct supplier relationships. Here are three reasons why:
- Quality and accuracy: Data that’s sourced from multiple aggregators will reduce the overall data visibility and traceability, and likely introduce critical inconsistencies and unnecessary duplication.
- Speed to resolution: If a data issue arises, a data supply that is several steps removed from the actual data source can hinder timely investigations and resolutions of data anomalies and unexpected trend breaks. This challenge can be mitigated by a partner with solid supplier relationships who can source data directly, and can therefore work directly with the supplier to investigate and resolve data issues.
- Relevant insights: Partners that source data as close to the patient’s journey and experience as possible maintain high data fidelity and relevancy. Partners that deliver exceptional quality and insights prove they are delivering an information foundation that is ready to support the business.
Dedicated supplier services team
A strong indication that your data partner is committed to long-term data authenticity is the presence of a dedicated supplier services team responsible for fostering long-term partnerships with data suppliers. The team monitors the consistency and longevity of the data panel to ensure any potential supply risks are proactively identified and promptly mitigated. If a supplier loses a data source or faces other unexpected challenges (e.g., a major outage caused by an unplanned external event), that dedicated team, experienced in navigating existing and new supplier relationships, will ensure that there is a plan in place to address issues quickly and effectively.
Transactional-level data
In the realm of data supply, governance, and delivery, (i.e., ensuring all records represented in the detailed counts are available at the transactional level) are crucial for life sciences companies. As biopharma manufacturers and other consumers of information continue to invest in establishing internal infrastructure and analytics capabilities, ensuring these resources have access to true transactional level data is critical for executing both analytical and AI use cases that inform commercial decisions. To that end, companies need to perform due diligence when it comes to understanding and avoiding data suppliers who deliver aggregated and overblown counts just to satisfy business requirements.
It’s important to recognize that some suppliers may use aggregated counts to hide their lack of investment. Consequently, when it comes time to deliver the data at the transactional level, the actual data may fall short of the promised counts. Your commercial operations, data science, and analytics teams require transactional data to establish and confirm business performance KPIs (key performance indicators), internal reporting, and key decision-making.
Visibility, validation, and verification
Suppliers want increased transparency into how their data is being used, ensuring it is kept secure throughout the supply chain, and that their data usage aligns with their priorities. This chart emphasizes the consequences when these principles are not met in that suppliers may reduce the number of partners they work with or cease commercialization altogether, leading to a significant loss of supply panels.
As suppliers focus on the ‘3 V’s’ as a foundation for partnership, many are facing challenges maintaining a consistent data supply
Conclusion
Maintaining data authenticity in the life sciences sector is essential for effective decision-making, regulatory compliance, and patient outcomes. A partner who delivers a robust data supply roadmap, offers a dedicated supplier services team, and demonstrates transparency in terms of their proportion of aggregated datasets is essential to ensuring data reliability. By prioritizing partners with direct supplier relationships and minimizing sole reliance on third-party data aggregators, organizations can enhance data fidelity and traceability. Ultimately, these practices will help life sciences organizations navigate the complexities of data integrity and make informed decisions that drive commercial success and improve patient care.
