The logic seems irrefutable: provide people with better data, and they'll make better decisions. This, however, is a dangerous assumption.
It's a common scenario: brilliant data teams pour countless hours into building sophisticated analytics tools, dashboards, and recommendation engines. They are certain: Once people see the data, change will follow. After all, isn't that the foundation of data-driven culture? Most of the time, unfortunately, these teams will end up disappointed.
Success with data isn't just about algorithms or accuracy—it's just as much about human nature. Our brains have not evolved at the pace of technology. Rather, over millions of years, they have evolved to do something quite fascinating: resist any information that challenges existing beliefs.
This means that whenever we present data that confronts someone's assumptions and gut feelings, we're not simply sharing information. We're asking their brain to override an ancient protection mechanism. Which, ironically, means that the very data that could change someone's mind—and thus, elevate their decision-making—is also precisely the data they are neurologically most wired to ignore or dismiss.
So we need to rethink data-driven change. It's not about merely closing an information gap, but overcoming deeply-rooted belief-protecting mechanisms within individuals, teams, and organizations. Simply making data available within an organization is about as effective for change as putting calorie counts on menu items and expecting everyone to suddenly ignore the burger in favor of the salad.
Annoyingly, getting all the right data together and making it available can already be quite hard. But to drive change, this is merely the first step. The real challenge comes afterwards: navigating the delicate process of reconciling what the data says with what humans believe. This requires strong support—and, at times, strong nudges—to allow people to successfully challenge their assumptions and create an environment where questioning beliefs feels safer than defending them. Such an environment doesn't emerge naturally, yet it's essential for data-driven success—no matter how strong the data itself might be.
Data-driven transformation has to acknowledge how humans actually behave, not how we wish them to behave. This includes the natural inclination to ignore data that drives changes. Illogical as that may be: the only alternative to addressing this part of human nature is building solutions that look logical on paper but fail in practice.