Insights management is going through a process of rapid maturation. Just a few short years ago, Within3 collaborated with MAPS to publish a paper outlining the basic value and strategic implementation of insights management. Now, in our latest collaborative white paper, we’ve explored how companies have successfully implemented insights management processes in increasingly mature ways – up to and including the use of generative AI.
This blog post summarizes the latest MAPS and Within3 white paper to trace insights implementation through three distinct stages: The Age of Spreadsheets, The Age of Artificial Intelligence, and the Age of Generative AI.
First-generation insights implementation
It’s important to think of insights management less in terms of a linear technological progression, and more in terms of organizational preparedness, adoption, and implementation. While the first generation of insights implementation can be thought of as ‘The Age of Spreadsheets’, that isn’t to say that this approach is consigned to the past. The process of medical science liaisons (MSLs) recording meeting notes, extracting insights from these interactions, recording them in a spreadsheet and disseminating them to senior leadership will be familiar to most medical affairs professionals. In fact, polls conducted by MAPS and Within3 indicate that most organizations are now capable of generating insights from MSLs, medical information, and even social listening data. This shows us that the first generation of insights implementation has been broadly achieved.
“We grew and now are at the point we’re trying to organize an 800-row spreadsheet.” – MAPS roundtable Participant
Second-generation insights implementation
The second generation of insights implementation recognizes that humans don’t naturally process data all that well. Those increasingly-bloated spreadsheets aren’t especially user-friendly, and as data volumes expand, extracting actionable insights becomes an insurmountable challenge. Enter artificial intelligence. AI is capable of parsing large volumes of data and converting that information into a dashboard, making it easy for human beings to navigate relevant data and extract valuable insights. AI is also useful in both circumventing and surfacing the bias intrinsic in human-powered data analysis. MAPS and Within3 surveys reveal that the majority of medical affairs teams find themselves in this second phase of insights implementation. They’re familiar with insights management dashboards, and associated, AI-powered tools like natural language processing and sentiment analytics. But in this second generation of insights implementation, the technologies themselves have their limitations. Users often find that human analysis is still necessary to transform dashboard outputs into true insights – a resource and labor-intensive process. Often, the bulk of medical affairs efforts is devoted to producing the reports themselves – rather than using the insights those reports contain to inform strategic decision-making. Truly proactive insights management requires the third generation of insights implementation…The third generation of insights implementation sees the adoption of generative AI to further support and enhance human analysis. Generative AI is capable of ‘understanding’ your strategy, and outputting data in a way that is both easy to comprehend and immediately actionable. These systems use real, human language as both input and output, meaning users don’t need to be data scientists or have high levels of technical knowledge to interact with them.
Generative AI is similarly capable of aggregating and harmonizing data from numerous sources, without the need for tags or keywords – further reducing the manual workload. At this point, extracting insights becomes a case of simply querying the system as you would a real person. For example, “what do patients think of the current treatment landscape?”, or “do clinicians understand the benefits of our new drug?”, etc.
In the third generation of insights implementation, the pace of technological change is so fast that organizations that attempt to develop their own solutions are inevitably left behind. This reality is reflected in the experience of MAPS survey participants, who report that AI is developing so quickly that their ‘build your own’ (BYO) solutions become obsolete before they can even be completed. As one participant noted:
“If the tech is changing faster than your ability to develop, then developing makes no sense.” -MAPS Survey Participant.
Instead, it’s those organizations that have licensed purpose-built genAI-powered insights management solutions that have unlocked the full value of third-generation insights implementation. For these early adopters, insights are generated to a much higher standard of accuracy and relevance – allowing them to reduce the process of insight reporting from months to just days, and eliminate 90% of their manual workloads.
However, organizations need to recognize that generative AI is a tool with many potential use cases, rather than a monolithic system that can be implemented or not implemented in a purely binary way. It’s helpful to think of generative AI as like the apps on your smartphone, rather than as the smartphone itself. Just as you have individual apps for banking, social networking, watching TV or reading the news, generative AI has distinct applications in its own right – from drug discovery to content generation to large-scale data analysis. Organizations that recognize this, and build specific generative AI use cases into their medical affairs strategies, will join the earliest adopters of third-generation insights management.
In our collaboration with MAPS, we’ve been privileged to record the evolution of insights management, and to witness the successes of those who have traced the curve of insights implementation. Our latest white paper, ‘Three Generations of Insights Implementation’, is a deeper dive into the topics discussed in this blog post, and contains the full results of the MAPS polls and roundtables. You can access the full white paper – along with previous collaborations between MAPS and Within3 – here.
And if you’re ready to experience the third generation of insights implementation for yourself, you can book a demo of the Within3 Insights Management Platform today.