Data-Driven Decision Making: How Much Data Does a CEO Need?

It’s decision time at the Harvard Business Review, which has dedicated a lot of real estate in its November issue to the subject of making better decisions. There’s a lot of excellent commentary on the topic at HBR‘s blogs as well—so much, you might say, that my choice to blog about it was an easy one.

But take a look at the wealth of material there and there’s one aspect of the topic that, surprisingly, has gone AWOL. One article discusses the importance of gaining credibility  (opens in a new tab); another cautions against silver bullets  (opens in a new tab). One article reminds readers of the emotional aspect of decision making  (opens in a new tab); another advises not to worry so much about it  (opens in a new tab). One article reveals the latest research on echo chambers  (opens in a new tab); another categorizes the types of decisions a leader can make  (opens in a new tab), so she can decide which decision process to use.

Emotions, feelings, stressors. Hey, wasn’t data going to make all this stuff easy, or at least easier?

Is Big Data a Big Deal?

In the past few years the term “data-driven decision making” has become so common I imagine many CEOs have a keyboard shortcut to produce the phrase in their memos and speeches. But it would appear that we’re back to that old business of trusting one’s gut—and figuring out how much to trust it.

That’s not a criticism of HBR‘s own editorial decisions. Indeed, it’s good to have a reminder that data-gathering is at best a supporting player in larger decision-making process. For instance, the Wall Street Journal recently reported on research that suggests being “data-driven” can help with routine operational decisions, but gets trickier with larger strategic processes  (opens in a new tab). “One of the biggest challenges in leveraging data science to help make complex strategic decisions is to mistakenly assume that an unordered, unpredictable, complex context is in fact an ordered, predicable complicated one,” Iriving Wladawsky-Berger writes.

So, decision-making is always going to be messy, emotional work. It’s why the business shelves of bookstores are stuffed with titles suggesting that leaders just need to lock into a particular mindset to become smart when it really counts—your status as a brilliant leader is just a blink  (opens in a new tab) or nudge  (opens in a new tab) or switch  (opens in a new tab) away. This would be so much easier if we didn’t have to think.

Data, People; People, Data

If anything, the gig has become harder. As CEO adviser Ram Charan told HBR: “Getting to the right answer is tougher these days. It’s not just the greater number of variables to consider; executives also need to make subjective judgments about highly ambiguous factors that are moving targets. The usual competitive analysis doesn’t work well when technology keeps erasing industry boundaries and the pace of change is so fast that you can’t wait for things to stabilize.”

So today, a leader’s best skill at a moment that calls for a tough strategic decision may be the ability to speak candidly with stakeholders about those variables. Earlier this year, Building Owners and Managers Association executive director Gabriel Eckert, CAE, spoke with Associations Now about the importance of blending data, intuition, and board members who reflect a diversity of mindsets and competencies. “I think that with a lot of organizations it’s caused an over-reliance on data, and in some cases it’s caused organizations to be paralyzed by data,” he said. “With some boards there’s never going to be enough data to satisfy the curiosity for discovering what the facts may be. So I think that the same thing could be said on the other side of the equation, that you don’t want to have a board that’s just relying on intuition alone all the time.”

When it comes to high-stakes decisions, where do you stand? How much and what kind of hard data do you need to feel confident about your choices? And what “soft” factors do you keep in mind? Let us know in the comments.