The recent uptick in conversations about the future of applied research has driven many in the industry to pause and reflect. What role will AI play in our practice? How have organizational priorities shifted post-COVID? What counts as ‘actionable insight’ in world where smaller teams can scale rapidly in ‘founder mode’? Which practices and processes can be streamlined? Which ones shouldn’t?

These are all valid questions; and while I think it’s important to address them, I’d like to free up some of our collective mind share to get us past the hand-wringing to focus on our foundations. To that end, this post is the first of four that will consider our enduring value in light of relatively recent shifts in the industry.

I thought I’d kick it off with a few personal reflections.

Timing

First, I’ve grown to realize that timing is critical in our industry. Perhaps that’s true in most professions, but it seems particularly pronounced in the world of insights provision. More specifically, the ‘in-the-moment’ value of insights work is indispensable, and I’ve seen it repeatedly accelerate our impact if we take the time to read the signs. It might be tempting to dismiss this as opportunistic. It’s not. It’s about knowing your audience, and tailoring your insights to sync with their momentum, reward structures, and priorities.

This shouldn’t be confused with blanket appeasement, which erodes our credibility. Instead, it’s about optimizing our value. I’ve written much more about this recently, but the point I want to make here is that adjusting our deliverables to the context in which our work is received doesn’t mean compromising rigor, which should always be at the foundation of what we do anyway.

In fact, this approach allows us to maintain that foundation, while simultaneously freeing us. More specifically it frees us from taking on the weight of thinking we need to solve EVERYTHING, and instead positions our work as more valuable because it is both insightful and contextually-aware — it’s work that’s critically instrumental in lifting everyone up, not just researchers.

Facilitation

Beyond insights, this also applies critically to the interpretation of data. As research practitioners, we are often trained to think that our interpretations of data are predominant. The same might be said of design thinking, and the inherent ‘it-can-solve-everything’ presumptions it advanced during its heyday. While both are often more informed by theory, years of practice, etc., I’ve got news for you: our interpretive value isn’t always top of mind among our collaborators.

If we open our lens a bit, we can see that a huge part of our interpretive value may actually lie in facilitating, guiding, and setting the boundaries for a wide range of interpretations to flourish. If you’re willing to accept this, it too can be remarkably freeing — and powerful. We don’t need to feel responsible for solving “everything, everywhere, all at once.” In fact, it’s often more powerful, and useful, to define the playing field itself.

Resilience

Finally, a deeper dive into context. Nothing in our training as ethnographers, designers, writers, strategists, or insights practitioners of other breeds, can prepare us for some of the friction we face in the workplace. Your professors weren’t a good gauge for dealing with this; and maybe your coach isn’t either. Interacting (and maybe sometimes ‘wrestling’) with cross-functional peers, over and over again, and being consciously and sincerely empathic about where they’re coming from, gives you two things: a broader lens and thicker skin. We all face a mix of headwinds and tailwinds. It’s up to us to know when to ignore the cynics and when to pause and consider the critical concerns of others; when to build incrementally on institutional orthodoxies and when to advocate for entirely new perspectives.

Enduring Value: Intro to the Mini-Series

Once we’ve freed ourselves from the burden of solving for everything, and established solid groundwork for facilitating well-timed and thoughtfully-contextualized insights, we’re in a position to work relationally, rather than directionally. That seemingly small shift opens the door to a broader surface for our work; and it is the context in which I want to consider three attributes that serve as what I consider critical foundations for our practice: curiosity, adaptation, and storytelling. In each of the next three posts, I’ll dig deeper into the layers of value that each of these attributes provides, and try to position them in the context of the capabilities of AI. I hope you’ll join me.

In the meantime…