Pharma brand teams practicing patient-centric decision-making require broad access to data as well as the tools to analyse and action it. But as we know, the skills and experience to make effective use of data are the product of considerable training and development. While some businesses employ sizable analytics teams, their ability to service multiple brand teams can still be limited. And given the workload of successfully managing a brand, it’s a stretch to expect brand managers to have the same depth and breadth of analytics expertise as their business intelligence peers.
For those following Prospection in recent times (and even for those who follow tech generally), it’ll come as no surprise to see large language models (LLMs)—notably “GPT—appear in this discussion. 2023 will probably be remembered as the year of GPT, and it’s almost impossible to overstate its potential when it comes to improving the way non-analytics professionals interact with data. Of course interaction is just the first benefit it brings – there’s more to come. But it’s a very good start.
GPT in Pharma: A Game Changer
Understanding and interpreting patient-level data to improve brand performance and patient outcomes is a complex task that demands precision, speed, and – if it’s to become a brand team superpower – scalability. Analytics teams can be the linchpin in bringing patient-centric intelligence to life for brand teams. However, access to analytics teams can be constrained for numerous reasons, including by their limited resources and the large demand for their expertise.
Choosing how to allocate this specialized and valuable resource is challenging. Customers want their analytics teams involved in more challenging, high value analysis, rather than routine reporting and insight generation. It can also be difficult to give them the space to just explore possibilities that might be gleaned from the data. That means that brand teams can be left planning with fewer insights at hand, with less potential to identify opportunities to really grow their brand’s success and impact.
A GPT-enabled patient-centric intelligence platform offers solutions to these challenges in a few ways:
- Enhancing Data Accessibility – Manipulating and creating reports from patient-centric intelligence that lead to brand-enhancing insights around patient behaviors and market dynamics requires considerable expertise. GPT can give brand teams independence when it comes to generating insights from data, helping them configure and generate reports that can answer their key business questions almost instantly.
- Accelerating Decision-Making – The best decisions are the timely ones. GPT helps by getting brand teams to insights and answers in a fraction of the time that a traditional back-and-forth with the analytics teams takes.
- Augmenting Domain Expertise – Brand teams possess nuanced, contextual knowledge about their markets and patients. GPT assists these teams by complementing their expertise, and guiding them to insights that an analytics team might not initially envision. As they explore patient-centric data themselves, their deep understanding and domain-specific intuition are integrated into the exploration process, leading to more targeted and relevant insights.
Working with GPT – Limits, Opportunities, Considerations
With almost every new technology, while the positives are exciting and often groundbreaking, it’s critical to consider the limitations – and work out how to make sure the technology is applied appropriately to get the most from it without causing downstream risks.
- GPT is not Infallible – We expect mistakes from people, and we accommodate that risk with second opinions and cross-checking. The risk with artificial intelligence (AI) systems like GPT is that we just assume it will be right, 100% of the time. For businesses with analytics teams, brand-team use of GPT-powered solutions can be liberating, giving analytics teams more capacity to work on challenging data problems, while brand teams are able to self-serve their routine queries. To offset risk though, brand teams can explore and come up with hypotheses and then seek validation and support from analytics experts. It’s a more empowering, efficient and sustainable approach to maximizing use of patient-centric data to improve outcomes.
- Transparency Rules – Remember school days and solving a mathematical equation? Where a wrong answer can be offset by clear accounting of the method that led to the answer? Just as you would hope with human analysis, trust can be built when the “workings out” are clear. Your GPT-powered solution needs to be “explainable”—able to show how it arrived at its answer. Alongside trust, this also enables a smoother checking process with analytics teams, and it can also upskill brand teams, helping them understand how to create and interpret patient-centric data reports.
- The Drafting Tool – When GPT provides an answer, it should be treated as a starting point, not a final solution. GPT’s responses are flexible, and they encourage curiosity. It’s elastic in nature, offering possibilities that human analysis might overlook. Brand teams should use it to explore and refine, working towards insights that can be expanded upon and validated.
GPT Quick Tip
GPT is a tool that empowers, but it’s human expertise that guides it effectively. Put a commonsense guardrail into action with GPT with the 80/20 rule. GPT often provides 80% of the answer, but the final 20% may require human expertise. The sweet spot is in combining GPT’s capabilities with human expertise.
Prospection AI: Patient-centric Intelligence and Award-winning ProGPT
Prospection has long been recognized for the quality of insights that can be generated with its products and people. With Prospection AI, we’ve brought the power of our proprietary Patient-centric Intelligence Core to a new streamlined platform that incorporates ProGPT to assist brand teams looking to maximize use of patient-centric insights in championing their brands.
Here’s three things that make Prospection AI a compelling business tool for pharma brand teams.
- Truly easy to use – With the Critical Insights hub and ProGPT, Prospection AI empowers pharma brand teams to navigate and utilize patient-level data efficiently. Through its user-friendly interface, users can quickly find answers, ask questions and generate clear visualizations with ease.
- The Power of Iteration – Prospection AI with ProGPT serves as a dynamic starting point. If a brand manager doesn’t get the answer they’re looking for, they can iterate. It’s real-time collaboration with a responsive AI that encourages curiosity and exploration. And because ProGPT can describe exactly how it arrived at its answers, transparency and trust are implicit.
- Unlocking Time and Resources – Traditional data analysis consumes time and resources. Prospection AI streamlines the process, reducing the reliance and drain on analytics teams and making insights more accessible to brand teams.
Brand Teams and Prospection AI
The use of AI is about progress and improvement. It’s about making data more accessible and providing a starting point for brand teams to explore and improve how they manage their brands. While the bar might be high for AI, a deeper understanding of its limitations as well as its possibilities allows brand teams to capitalize on its potential.
With Prospection AI, we’ve built a brand-team partner to accelerate data-driven success. It’s already making a difference for customers, and it has already won AI-focused awards. That said, we talked about using ProGPT for iteration of ideas, but for us, ProGPT itself is an iterative tool. At the moment it works as a handy helper to create reports that can lead to insights, yet the use of AI is continually expanding within Prospection AI. In the not-so-distant future we’ll be rolling out additional functionality that not only broadens access to insights, but also describes what is happening with the market or patients, and why it’s happening. We look forward to sharing more about our AI journey in the months ahead.
Contact us today for a demo to learn more about how Prospection AI can help brand teams be more patient-centric, data-driven and effective.