Let’s think about data use differently; not as discrete reports, but instead as an ongoing process of drill-down, questioning and analysis to reveal untapped value from our data assets.
I’m continually amazed at the breadth and depth of pharmaceutical manufacturer commercial data assets, and how little value these manufacturers are actually getting from these data assets. As any good consultant would, I’ve been noodling on this problem/opportunity a lot recently. There are often many contributing factors like analyst capacity, analyst capability, analytical tools, poor data integration, etc. I’ve settled on what I think is the primary driver for the disconnect between data potential vs actual value: how we think about data contextually. I’ve been facilitating data use workshops and interviews for the past twelve years. Data use discussions invariably focus on the types of discrete data visualizations that users are seeking, e.g. “I need to see medication possession ratio for each SPP in my network, so I can identify the best and worst performers in my network”, or “I want to see the monthly NRx and TRx trend for the past 12 months for each payer type and national.” I can honestly say that I’ve never heard anyone talk about data use as an ongoing process of drill-down, questioning and analysis.
I believe that approaching data use as ongoing and iterative processes is the path to unrivaled value creation from data, through mining meaningful insights and identifying impactful actions. Approaching data as a process is difficult to do when our data use cultures are based on ecosystems of discrete reports. Following are some things that have enabled me to get some traction for this concept with a few manufacturers:
- Identify business-critical topics that rally cross-functional commercial support, e.g. adherence for a mature primary care product or time to initiation for a specialty pharmacy product or sales performance within integrated delivery networks.
- Ensure cross-functional support and involvement, so that subject-matter experts can collaborate, question and digest, while analytical experts feed the iterative exploration with drill-downs and visualizations
These concepts of data use as discrete reports vs. an ongoing process are not mutually exclusive. Viewing data use as ongoing process of drill-down, questioning and analysis does require discrete views of data, but they are transitional, dynamic and the result of analytical tools applied to answer questions.
I believe that solutions to intractable problems like script abandonment and adherence can be found if we apply this idea at a more grand scope and scale, combining subject-matter experts from multiple health care stakeholders working with the data that they can each bring to the table.