On Making Great Decisions

imagesHere is a brief excerpt from a conversation involving Stanford’s Chip Heath and McKinsey’s Olivier Sibony, featured in the McKinsey Quarterly, published by McKinsey & Company. They discuss new research, fresh frameworks, and practical tools for decision makers. To read the complete article, check out other resources, learn more about the firm, obtain subscription information, and register to receive email alerts, please click here.

To learn more about the McKinsey Quarterly, please click here.

* * *

Every few years, Stanford University professor Chip Heath and his brother, Dan, a senior fellow at Duke University’s Center for the Advancement of Social Entrepreneurship (CASE), distill decades of academic research into a tool kit for practitioners. The bicoastal brothers offered advice on effective communications in Made to Stick, on change management in Switch, and now, in their new book, Decisive, on making good decisions. It’s a topic that McKinsey’s Olivier Sibony has been exploring for years in his work with senior leaders of global companies and in a number of influential publications.

Chip and Olivier recently sat down to compare notes on what matters most for senior leaders who are trying to boost their decision-making effectiveness. Topics included Heath’s latest book, research Sibony and University of Sydney professor Dan Lovallo have under way on the styles of different decision makers, and practical tips that they’ve found make a big difference. The discussion, moderated by McKinsey’s Allen Webb, represents a state-of-the-art tour for senior executives hoping to help their organizations, and themselves, become more effective by benefiting from the core insight of behavioral economics: systematic tendencies to deviate from rationality influence all of our decision making.

What’s the current state of play in real-world efforts to improve decision processes through behavioral economics?

Sibony: The point we haven’t conveyed effectively enough is that however aware you are of biases, you won’t necessarily be immune. You should see yourself as the architect of the decision-making process, not as a great decision maker enhanced by the knowledge of your biases.

The analogy I like is how we handle problems with memory. The solution isn’t to focus harder on remembering; it’s to use a system like a grocery-store list. We’re now in a position to think about the decision-making equivalent of the grocery-store list.

Sibony: We’re doing ourselves a disservice by calling it a decision-making process, because the word “process,” as you point out in your book—

Heath: —It’s boring.

Sibony: It immediately conjures up images of bureaucracy and slowness and decisions by committee—all things associated with bad management.

Heath: Early in the history of decision making, people were optimistic about a better process called decision analysis. But nobody ever used it, because very few people have the math chops to fold back probabilities in a three-layer decision tree. The process that we’re advocating runs away from decision analysis and bureaucracy. We wanted some tools that someone could use in five or ten minutes that may not make the decision perfect but will improve it substantially.

Sibony: There are individual solutions and organizational solutions. Perhaps because we’re a consulting firm, we tend to look for organizational solutions. In an article you wrote long ago, Chip, you quote somebody who asks something like, “If people are so bad at making decisions, how did we make it to the moon?” Your answer was that individuals didn’t make it to the moon; NASA did. That insight has been translated into all sorts of operational decision-making. It is the fundamental insight behind work in continuous improvement—for instance, when people are trained to go beyond the superficial, proximate cause of a problem by asking “five whys.”

But we don’t apply that insight when we move from shop floors to boardrooms. Partly, that’s because of a lack of awareness. Partly, it’s because the further up the hierarchy you go, the harder it becomes to say, “My judgment is fallible.” Corporate cultures and incentives reward the kind of decision-making where you take risks and show confidence and decisiveness, even if sometimes it’s really overconfidence. Recognizing uncertainty and doubt—it’s not the style many executives have when they get to the top.

Heath: Yes, but we’re never really sure when we’re being overconfident and when we’re being appropriately confident. That’s where we go back to processes.

Sibony: It’s a lot easier to say, “Let’s build a good process so your direct reports have better recommendations for you” than “Let’s come up with a process for you to be challenged by other people.”

Heath: I love that emphasis: “We’re going to help others get you the right recommendations.” We all tend to believe “I’m not subject to biases.” But we can easily believe that others are. I’m curious about your batting average, Olivier. Suppose you walk into an executive group and start talking about the behavioral research and how they could change their processes to overcome biases. Are a third of the people interested? Five percent?

Sibony: If we tell the story like that, it’s zero. But exactly as you just suggested, a lot of executives are open to discussing how their teams could help them make better decisions. So we will say, for example, “Let’s talk about what works and what doesn’t work in your strategic-planning process.” We don’t talk about biases, because no one wants to be told they’re biased; it’s a word with horrible, negative connotations. Instead, we observe that people typically make predictable mistakes in their planning process—for instance, getting anchored on last year’s numbers. That’s OK because we are identifying best practices. We end up embedding this thinking into processes that generate better strategic plans, R&D choices, or M&A decisions.

* * *

Here is a direct link to the complete article.

This discussion was moderated by Allen Webb, editor in chief of McKinsey Quarterly, who is based in McKinsey’s Seattle office.

Posted in

Leave a Comment

This site uses Akismet to reduce spam. Learn how your comment data is processed.