Thinkers & Ideas

Nitin Nohria, former Harvard Business School dean and longtime CEO educator, explores what leadership really demands. He examines why CEOs must build systems for better decisions rather than make them all, the struggle to move beyond the COO mindset, and what 70,000 hours of calendar data reveal. They also discuss isolation, AI, geopolitical uncertainty, and defining a lasting legacy.

George Newman, cognitive scientist and Rotman School professor, reframes creativity as an archaeological search rather than a lightning strike. He explores a four-stage method for uncovering ideas, why organizations retreat inward under pressure, and how breakthroughs emerge from cross-domain connections. He also examines AI’s creative role, the power of a small original twist, creative hot streaks, and why promising ideas can feel uncomfortable at first.

Paula Goldman, Salesforce’s EVP of Product and first Chief Ethical and Humane Use Officer, explores what happens when AI becomes a workplace partner. She discusses keeping humans at the helm, using customer emotion to guide automation, preventing skill decay, navigating AI’s uneven capabilities, measuring value beyond time saved, and scaling promising pilots into enterprise transformation.

Vijay Govindarajan, Coxe Distinguished Professor at Dartmouth and author of Reverse Innovation, champions products built for emerging markets that scale globally. He tells how a $15,000 portable ultrasound for rural China became a global hit. He explains why multinationals miss broad markets, the three-phase design framework, and serial versus parallel reverse innovation.

Renée Mauborgne, INSEAD strategy professor and co-author of Blue Ocean Strategy, explains creating uncontested market space through value innovation. She discusses when companies should stop competing, why non-customers spark new demand, NVIDIA’s market‑making moves, breaking the differentiation–cost trade-off, and how AI can enable rather than commoditize strategic advantage.

Doyne Farmer, complexity scientist and economist who directs the Complexity Economics Program and wrote Making Sense of Chaos, offers a compact tour of why traditional forecasting breaks down in interconnected systems. He discusses emergence and chaotic dynamics. He explains agent-based modeling with real-world pandemic and economic forecasting examples. He outlines practical uses for businesses and how to get these tools adopted.

In Crisis Engineering: Time-Tested Tools for Turning Chaos Into Clarity, Matthew Weaver and Mikey Dickerson argue that organizational crises are not problems to be survived but are rare windows in which rapid, directed transformation becomes possible within days rather than years.Weaver was a founding Site Reliability Engineer (SRE) at Google and later established the Defense Digital Service at the U.S. Department of Defense. Dickerson, also a founding SRE at Google, led the rescue of healthcare.gov, an effort that landed him on the cover of Time magazine. President Barack Obama subsequently appointed him deputy chief information officer of the United States, where he created the United States Digital Service. Together with their co-author Marina Nitze, the three are partners at the crisis engineering firm Layer Aleph. Drawing on decades of experience inside some of the most complex systems in government and industry—from the healthcare.gov rescue to wildfire response and pandemic logistics—the writers deliver a practical framework for identifying the five signals of a genuine crisis, and how to use that moment to drive lasting change across tech, government, healthcare, and beyond.In their conversation with Nikolaus Lang, global leader of the BCG Henderson Institute, they discuss why breakdowns in sensemaking cause well-trained operators to make situations worse, what the healthcare.gov rescue reveals about co-location and shared urgency, how crisis disrupts normal incentive structures to surface the organization’s real map, the concept of bracketing as a tool for directing team attention, and how AI integrations are creating the conditions for larger and harder-to-manage crises ahead.Key topics discussed: 01:24 | What “crisis engineering” means and what conditions define a true crisis05:28 | Sensemaking: the invisible force driving decisions under pressure10:38 | The 2013 healthcare.gov collapse: arriving on the crisis scene14:05 | Why physical co-location is essential in a crisis17:18 | Using a crisis to remap how the organization actually works20:17 | Bracketing: deliberately defining the beginning and end of a crisis25:33 | Why organizations struggle to define an exit condition27:34 | Capturing crisis learning before returning to normal operations30:22 | How AI is changing (and likely multiplying) crisis situations35:51 | Advice for business leaders on building crisis readiness before a crisis hits

Benjamin Recht, UC Berkeley professor and author of The Irrational Decision, explores how mathematical optimization came to govern choices. He traces its WWII origins, shows where optimization shines (microchips, logistics) and where it breaks down (self-driving cars, complex real-world dilemmas). He argues for keeping human judgment in the loop and offers a framework for which decisions to automate.

Verity Harding, former DeepMind policy lead and director of the AI & Geopolitics Project, argues nonexperts must shape AI governance. She challenges the nuclear analogy, points to the Outer Space Treaty and IVF regulation as cooperative models, explores how the internet shifted after 9/11, and urges business leaders to align AI with real-world purpose and societal trust.

Eric Ries, entrepreneur and author of The Lean Startup and Incorruptible, explores why mission-driven companies drift toward short-termism and systemic corruption. He discusses the rise of shareholder primacy, the idea of financial gravity pulling firms off course, and structural defenses like purpose, coherence, and legal charters to protect long-term integrity.