Efficient markets? Not so fast.

Tariffs everywhere. Prices rising. Markets falling. Pressure building on supply chains. And now, turmoil in the labor market, with waves of layoffs across the federal government and continued job losses in the private sector, especially in tech, driven by relentless cost-cutting and AI-related restructuring (yes, still hashtag#OpenToWork).

Good times, right? Surprising? Not really.

When I saw the announcement of China's retaliatory 34% tariff on U.S. goods this morning, I found myself wondering: why were so many caught off guard? The warning signs have been flashing for months, including escalating trade rhetoric, early policy signals from Project 2025, and an increasingly brittle global economy. This isn’t a Black Swan. It’s a Gray Swan. The signals were obvious. The real failure was in not acting on what foresight revealed.

The Efficient Market Hypothesis (EMH) suggests that all available information is already reflected in asset prices and that markets, in effect, see clearly and respond rationally. In theory, events like this shouldn’t catch anyone off guard. But clearly, they did. Others have pointed out the gap between theory and reality. Nassim Taleb has written extensively about this: how markets are prone to overconfidence, blind to “fat tail” risks, and more vulnerable to narrative traps than we like to admit. In that view, market efficiency is a useful idea, but one that often collapses under pressure when uncertainty and complexity surge. 

Strategic foresight isn’t about predicting the future. It’s about asking better questions, stress-testing assumptions, and planning for multiple plausible outcomes. When I studied foresight formally, one of the core principles that stuck with me was this: don’t get trapped by the most convenient narrative, however compelling it might be. Plan for volatility before it arrives. I’ve learned, sometimes the hard way, how difficult that can be, in organizations and in life.

We see this pattern again and again. Teams optimize for efficiency, not adaptability. They build for what they hope will happen, not for what could. When disruption hits, it’s rarely because the signals weren’t there. It’s because we chose not to see them.

So why weren’t these shifts priced in? Why did so few organizations model the second- and third-order effects of rising trade barriers? And what would it take to design systems, whether financial, organizational, or otherwise, that are actually prepared for (or hashtag#antifragile to) volatility? Markets are reacting now, but the conditions that created this moment have been building for some time. The signals were visible. 

Of course, hindsight is always easier than foresight. But that’s the point, right?

Photo Credit: Copyright © 2007, 2025 Sean Daken.