Thinkers & Ideas

In Global by Design: How to Create Innovations That Scale, Travel, and Transform, Vijay Govindarajan argues that the most powerful innovations are designed from the ground up for emerging markets like rural China or India, and then travel back to disrupt wealthy ones.
Govindarajan is the Coxe Distinguished Professor at Dartmouth College’s Tuck School of Business and one of the world’s foremost experts on strategy and innovation, most known for the New York Times and Wall Street Journal bestseller Reverse Innovation. In his new book, co-authored with MIT engineer Amos Winter, he fuses business strategy with engineering science to show how high-value, low-cost products built for poorer countries can win there first and then upend established markets abroad, offering a roadmap for innovators across engineering, business, NGOs, and government.
In his conversation with Nikolaus Lang, global leader of the BCG Henderson Institute, he discusses how GE built a $15,000 ultrasound machine for rural China; why most multinationals chase only the thin top slice of emerging markets; the three phases of his innovation framework; the difference between serial and parallel reverse innovation; and why globalization behaves like gravity even in a fragmented, multipolar world.
Key topics discussed:
03:29 | How reverse innovation works: GE’s ultrasound machine for rural China
06:39 | Why most multinationals aren’t global by design
08:01 | The mistake of serving only the thin top slice of emerging markets
10:00 | Phase 1, elucidating requirements: P&G’s 3,000 hours redesigning a razor
13:00 | Phase 2, closing the innovation gap: GE’s low-cost CAT scanner
16:48 | Phase 3, serial vs. parallel reverse innovation
20:20 | Value-driven innovation, the Segway cautionary tale, and where the biggest opportunities lie
24:14 | Global by design in a geopolitically fragmented world
Additional inspirations from Vijay Govindarajan:
Reverse Innovation: Create Far From Home, Win Everywhere (Harvard Business Review Press, 2012)
LinkedIn: Three Box Solution Weekly Column

In Blue Ocean Strategy: How to Create Uncontested Market Space and Make the Competition Irrelevant, Renée Mauborgne argues that lasting growth does not come from winning market share in crowded existing industries, but from creating entirely new market space that no one is competing in yet.
Mauborgne is a professor of strategy at INSEAD and co-director of the INSEAD Blue Ocean Strategy Institute. Blue Ocean Strategy, co-written with W. Chan Kim has sold more than 4 million copies and is recognized as one of the most iconic and impactful strategy books ever written. The new 20th anniversary edition tests the original theory against today’s market realities and is enhanced with fresh cases, including NVIDIA’s three successive market-creating moves, a new preface that highlights the book’s ongoing global impact, and a curated list of over fifty blue ocean cases across diverse industries that expand far beyond those in the original version.
In her conversation with Adam Job, senior director at the BCG Institute, Mauborgne discusses when a company should stop competing and start creating, why the search for new demand begins with non-customers rather than customers, how NVIDIA chases “zero-billion-dollar markets,” why differentiation and low cost need not be a trade-off, whether AI’s commoditizing effect makes advantage harder to defend, and how to reconcile bold commitment with the case for keeping options open.
Key topics discussed:
01:12 | Why beating the competition is the wrong goal
02:34 | How to know when it’s time to shift from competing to creating
05:26 | Finding a blue ocean: value innovation and the role of non-customers
07:02 | Where the process starts inside an organization
09:25 | NVIDIA and the pursuit of zero-billion-dollar markets
12:46 | Breaking the trade-off between differentiation and low cost
16:21 | What prompted the new edition
18:33 | Will blue oceans stay defensible as AI commoditizes capabilities?
24:17 | Why using AI only for speed and efficiency is a trap
25:36 | Reconciling bold commitment with the need for optionality
Additional inspirations from Renée Mauborgne:
Blue Ocean Shift: Beyond Competing—Proven Steps to Inspire Confidence and Seize New Growth (Grand Central Publishing, 2017)

As uncertainty continues to define the business landscape, we’re revisiting our conversation with economist and complexity scientist Doyne Farmer on why conventional forecasting often falls short in a world shaped by interconnected, dynamic systems. Drawing on decades of research, he explains how complexity science offers a more realistic way to think about prediction, risk, and decision-making—and how leaders can navigate uncertainty with greater confidence.
Whether you’re hearing this conversation for the first time or revisiting it with fresh perspective, Doyne’s insights remain as relevant today as ever.

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 crisis
05:28 | Sensemaking: the invisible force driving decisions under pressure
10:38 | The 2013 healthcare.gov collapse: arriving on the crisis scene
14:05 | Why physical co-location is essential in a crisis
17:18 | Using a crisis to remap how the organization actually works
20:17 | Bracketing: deliberately defining the beginning and end of a crisis
25:33 | Why organizations struggle to define an exit condition
27:34 | Capturing crisis learning before returning to normal operations
30:22 | How AI is changing (and likely multiplying) crisis situations
35:51 | Advice for business leaders on building crisis readiness before a crisis hits

In The Irrational Decision: How We Gave Computers the Power to Choose for Us, Benjamin Recht argues that the optimization and mathematical rationality we apply to every corner of modern life—from dieting to hiring to strategy—often fails when encountering the messy realities of life.
Recht is a professor of electrical engineering and computer science at UC Berkeley. In his new book, he traces how a narrow conception of rationality, born from 1940s wartime computing, came to dominate decision-making across society—and shows that this approach works brilliantly in closed, controlled systems like microchip design but breaks down in the complex, unpredictable domains where most real decisions are made.
In his conversation with Adam Job, senior director at the BCG Henderson Institute, he discusses the origins of mathematical rationality, why optimization works for microchips but not for diets, why game theory fails to describe how humans actually behave, and how leaders should think about the boundary between human and machine intelligence in the age of AI.
Key topics discussed:
01:02 | What is mathematical rationality and where do we encounter it?
02:49 | The origins of rational thinking in the 1940s
07:18 | Where optimization works: microchips, logistics, controlled systems
09:13 | Where it fails: Chernobyl, Waymo, and the limits of control
13:17 | When human “qualitative irrationality” is the right answer
14:59 | A framework for assigning decisions to machines vs. humans
17:45 | How the boundary between human and machine decision-making will evolve
19:14 | Why game theory fails to describe how humans actually behave
22:07 | Kahneman vs. Klein: two views on human decision-making
24:30 | What we risk losing as we outsource more decisions to AI