Bridging the Data Gap: Data Prioritization

In today's data-driven landscape, life sciences manufacturers face a critical challenge: how to make the best use of their revenue management data to generate meaningful insights. While this data has the potential to greatly influence decision-making across commercial operations, it is challenging to prioritize which data to integrate first. This is made even more complex by the lack of established precedents-successful examples that companies can follow-and the inherent challenges of working with large, complex datasets. Manufacturers not only need to navigate this complexity but also understand how to apply the data in meaningful ways to extract valuable commercial insights.

In this blog, we'll explore the efforts required to integrate revenue management data, highlighting the vital role of data warehouse custodians and the obstacles you may face without established precedents for using this data in decision-making. Prioritizing data effectively is essential to ensure the right insights are delivered.

"85% of executives classify their organizations as somewhat or very data driven"
(State of Revenue Report 2024)

The Role of Data Warehouse Custodians for Your Revenue Data Integration

Integrating revenue management data into a centralized data warehouse is a significant endeavor and having a dedicated data warehouse custodian is crucial to its success. A data warehouse custodian ensures the proper ingestion, alignment, and maintenance of diverse data sources, such as claims, longitudinal patient data, market access data, and account-level data. This role involves meticulously managing these data points to ensure they are accurately aligned and ready for analysis.

Integrating revenue management data into a company's data ecosystem is a complex task for data custodians. Post-launch, the volume and complexity of transactional data requires careful management to ensure seamless capture, processing, and storage for easy access and analysis. In addition, the data warehouse custodian will be responsible for aligning this complex dataset with other data sources and master data. This integration is imperative to analyzing the data in conjunction with the rest of the data lake content but comes with new and ongoing alignment and integration tasks that are imperative to maintaining data integrity and ensuring that the data ecosystem supports informed decision-making.

Tackling Decision-Making Without Precedents

Building a strong business case to support the integration and use of revenue management data is critical. While the potential for valuable insights is substantial, justifying the investment of time and resources can be challenging without existing precedents. To navigate this, you'll need to clearly define the value of revenue management data and set strategic goals for integrating it with other data assets. SMART goals for analyzing revenue management data may include:

• Greater insight into account payments and rebates to assess all-in discounting and optimize contracting
• Increased accuracy in distribution along the supply chain and better accounting for accruals
• Minimizing revenue leakage and identifying obstacles to cash flow with certain trade partners

Fostering greater collaboration between your revenue management and commercial teams is essential. By enhancing understanding of how revenue management data can drive commercial analytics, you can uncover new opportunities for optimizing revenue. This involves breaking down data silos, working toward a 360^o view of trade, and fostering a culture of data-driven decision-making throughout your organization.

Master Your Data and Overcome Prioritization Challenges

Data prioritization is a critical factor in optimizing revenue for life sciences manufacturers. By focusing on the scope of effort required for integrating revenue management data, and addressing the challenges posed by the absence of established precedents, organizations can unlock the full potential of their data. The journey to effective revenue optimization involves not only technical expertise but also a strategic vision and a commitment to leveraging data for informed decision-making.

To learn more about overcoming challenges with data prioritization and realizing revenue growth and efficiency, access our on-demand webinar, "Unlock Life Sciences Revenue Potential: Bridging the Data Gap," and stay tuned for more insights in our "Bridging the Data Gap" blog series.

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