Key Insights from IA Ignite: Healthcare

Yesterday I had the chance to attend IA Ignite: Healthcare put on by the Insights Association in Philadelphia, and it was a great reminder of the value of getting the pharma insights community together in person.

It was a strong one-day event, and the timing felt right. The day had the right mix of practical case studies, brand-side perspective, and bigger-picture discussion about how insights teams are being asked to work differently.

One theme that naturally surfaced throughout the day was AI, But what I appreciated was that AI did not overwhelm the agenda. It was present and relevant but it wasn’t treated as the only story. That balance felt refreshing, more so than in many recent conferences. The conversation seems to be moving into a healthier place: less hype, more pragmatism, and more focus on where AI can genuinely improve the work.

That being said, two sessions in particular stood out to me that I wanted to dive in deeper on.

The first was “When JTBD Meets Reality: Translating Behavioral Insight into Quantifiable Clinical Decision Frameworks,” presented by Jacqueline Alexander of C Space and Michael Hunt of Merck.

The session focused on applying Jobs-to-Be-Done thinking in an oncology setting, and it raised an important challenge that many insights teams face: what do you do when you have incredibly rich qualitative understanding, but need to scale it into something measurable, comparable, and actionable?

One of the key takeaways for me was the importance of translating behavioral and emotional insight into language that HCPs can quickly recognize and react to. The team had to preserve nuance while also making the work practical for quantitative validation.

I also appreciated the reminder that good research has to move beyond the obvious. In oncology, it is not enough to hear that overall survival data is meaningful. Of course it is, and it always will be the most meaningful data point. The more valuable work is understanding what sits beneath that answer: how different stakeholders interpret evidence, navigate uncertainty, weigh trade-offs, and make decisions in a multidisciplinary environment.

That is where frameworks like JTBD can be powerful, not as rigid templates, but as adaptable ways to push beyond surface-level answers and design research around the realities of clinical decision-making.

The second highlight was The Brand-Side Perspective panel, moderated by Lisa Courtade of Organon, with Emily Scheitlin of Lilly, Tomoko Shimizu of Boston Scientific, and Indrajit Mitra of Merck.

The panel captured a lot of what insights teams are experiencing right now. Jit said that “agility is becoming the cost of entry,” which felt like a succinct way to describe the pressure many organizations are under. Speed is no longer a nice-to-have; it is increasingly expected.

Emily Scheitlin built on that idea by noting that “speed is taking on a new form, and there is no excuse for not moving quickly anymore.” But what stood out even more was her reminder that the first step should be asking, “What do we already know on this topic?”

That is such a simple but important discipline. In a world where teams are being asked to move faster, the answer is not always to launch something new immediately. Sometimes agility starts with making better use of existing knowledge, connecting dots faster, and being clearer about what truly needs to be learned next.

Overall, this event was a valuable forum for reconnecting with the pharma insights community and reflecting on where the work is headed. The strongest theme for me was not just speed, AI, or methodology. It was the need for insights teams to be more intentional about what we already know, where we go deeper, and how we translate complexity into decisions that can actually move the business forward.

It was great to see so many thoughtful conversations happening across the industry, and that we were able to gather in-person to share them.