November–December 2025

Does Your C-Suite Really Operate as a Team?

New research from Gartner finds that in many companies, the C-suite team isn’t acting like one. Surveys show that just 31% of C-suite executives consider the C-suite to be their primary team. When senior leaders are asked about their team, they’re more likely to think about their functional units—marketing, finance, technology—and the people below them on the org chart. This alignment contributes to behaviors and dynamics that create dysfunction and underperformance. The study’s author recommends that chief human resources officers (CHROs) should take the lead to solve this problem and identifies three ways to improve how the top team works together. A Q&A with the CHRO of Barracuda Networks explores the steps the company is taking to ensure its leadership team collaborates well.

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The CEO of Advocate Health on Fostering Innovation Through Partnerships

Advocate Health, formed by the merger of two major health systems, aims to redefine patient care by leveraging its scale of 69 hospitals and 1,000 other sites to partner with academic institutions and leading businesses.

Key initiatives include the use of AI tools such as Microsoft’s DAX Copilot to make it easier for doctors and nurses to do their jobs; the creation of The Pearl, an innovation district in Charlotte, North Carolina, that brings together medtech pioneers including IRCAD, Siemens, and others; and the launch of the National Center for Clinical Trials (NCCT) to streamline research and access to cutting-edge treatments.

To accomplish all this, Advocate starts with a strong foundation, including its inspiring purpose, open culture, and solid infrastructure. The organization also encourages a mindset of curiosity and optimism. It co-creates with external experts and strategic partners—but only those that have aligned values and a shared vision for healthcare’s future, including serving the most vulnerable. Finally, it leverages its size not just operationally but strategically to create platforms for rapid experimentation and decision-making.

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Become an Octopus Organization

As companies pour trillions into transformation efforts, few see lasting results. That’s because most organizations approach change like machines—rigidly, predictably, and from the top down, argue Amazon Web Services enterprise strategists Jana Werner and Phil Le-Brun. In this article, adapted from their forthcoming book The Octopus Organization (Harvard Business Review Press, 2025), the authors offer a radically different paradigm: the Octopus Org. Modeled after one of nature’s most adaptive and intelligent creatures, the Octopus Org distributes decision-making, senses change in real time, and continually adapts. Unlike “Tin Man” organizations that view business as complicated but controllable, Octopus Orgs recognize the truly complex nature of today’s world, which is nonlinear, uncertain, and constantly evolving. The key to thriving in it is to change antipatterns—deep-seated habits that compromise clarity, ownership, and curiosity. The shift to this model doesn’t unfold in predictable, scalable phases. It happens organically, as local teams solve meaningful problems and share what works. The prize? Greater adaptability, deeper engagement, stronger innovation, and, ultimately, lasting advantage.

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Is This a Moment for Strategic Hibernation?

Political and regulatory whiplash is forcing companies to rethink how they weather hostile environments. Beyond the familiar strategy of speaking out against policy or exiting business lines, strategic hibernation offers a way to preserve core capabilities while minimizing exposure, enabling rapid reentry when political winds change. Historical examples—from Prohibition-era brewers, to biotech firms navigating U.S. stem cell restrictions, to Indian banks under financial repression, to Chinese tech companies under state crackdowns—show how maintaining essential assets, investing in political risk intelligence, and calibrating public visibility can safeguard long-term objectives. Done well, this approach allows organizations to sustain critical capacities, avoid mission drift, and reemerge stronger when sentiment and regulations change.

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The Surprising Success of Hands-On Leaders

Leadership theory suggests CEOs should focus on high-level issues such as strategy and resource allocation. These authors challenge this conventional wisdom by spotlighting CEOs who dive deep into day-to-day execution rather than hovering at the strategic level. By exploring best practices at Amazon, Danaher, RELX, and Toyota, they argue that top-performing companies thrive because of leaders who actively shape how work gets done.

These CEOs—Jeff Bezos, Larry Culp, Erik Engstrom, and Eiji Toyoda—have rejected the hands-off model in favor of modeling behaviors and teaching frontline teams. Their approach isn’t micromanagement; it’s a disciplined, system-building style that fosters autonomy, clarity, and continuous improvement. The authors distill five principles that define this leadership: obsessing over customer-value metrics, designing work processes, making decisions through experimentation, teaching tool kits, and embedding a culture of relentless improvement.

This article illustrates how the CEO role can be redefined in a way that makes depth, presence, and operational fluency become sources of enduring competitive advantage.

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What Every Company Can Learn from Private Equity

Private-equity-backed companies consistently deliver faster, more substantial gains than their public or family-owned peers, often transforming their performance within just a few years. Their playbook consists of six practices: conducting full-potential due diligence on a recurring basis, building management teams that are precisely matched to their value-creation goals, “clean-sheeting” labor to streamline operations and boost productivity, eliminating unprofitable revenue that has a negative impact on cash flow, executing transformation plans with granular accountability, and treating leadership time as a scarce, high-value asset. Applied together, these methods foster sharper strategic focus, quicker decision-making, and stronger alignment between resources and results. Leaders in any sector can adopt then to accelerate growth, improve efficiency, and strengthen long-term performance.

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Stop Running So Many AI Pilots

Companies eager to adopt generative AI often launch numerous pilots across departments, chasing quick wins and marginal efficiencies. But a scattershot approach won’t deliver transformative impact. The global consumer packaged goods company Reckitt took a different approach. It chose to go deep in one domain—marketing—where gen AI could be applied across interconnected tasks like insight generation, content creation, and product development.

The lesson? To unlock gen AI’s full potential, organizations should resist the urge to experiment broadly and instead go deep and narrow—concentrating efforts where scale and synergy can drive meaningful change. They should begin by selecting a single strategic domain where gen AI can be applied across interconnected tasks. They should then build on existing strengths—such as data assets or technical capabilities—to scale AI adoption meaningfully. By rethinking core processes within that domain and aligning teams around transformation rather than experimentation, companies can unlock deeper insights, accelerate innovation, and achieve measurable impact.

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How to Monetize Your Data

Many organizations are sitting on valuable proprietary data but lack a clear plan for commercializing it. As interest in selling data grows—driven by advances in AI, pressure to find new sources of revenue, and the success of firms like Amazon, Mastercard, and Instacart—leaders need a structured approach. The most effective strategies start close to home: with core businesses, existing partners, and a focus on data that supports the company’s primary mission.

To succeed, companies must first clarify who their data customers are and what problems the data will solve. They also need to choose between direct monetization, such as subscriptions or licensing, and indirect approaches that embed data into existing offerings. And regardless of the method, data privacy, regulatory compliance, and reputational risk must be addressed from day one.

Finally, how the data is packaged matters. Firms can sell raw data, bundle insights, or deliver commercially ready products. The more complete the offering, the greater the potential for strategic differentiation—and sustainable returns.

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A Smarter Way to Disagree

To foster constructive disagreements, organizations should encourage individuals to modify their observable behaviors during conflicts. More specifically, the authors’ research has shown that employees should be more attentive to their linguistic behavior—to carefully choose the words they speak—because unlike a person’s thoughts and feelings, language is observable by counterparts, trainers, and mentors.

Individuals can use several approaches in conversations where there are different points of view. They can signal a desire to learn by saying they’re curious about their counterpart’s position. They can acknowledge a colleague’s position by restating the core of that person’s statement. They can find common ground and make the similarities they share explicit. They can hedge their claims, leaving open the possibility of being wrong. And they can build trust by sharing their personal stories.

For their part, organizations can train people to improve their verbal skills. They can use technology to monitor those skills and give employees direct feedback on their conversational behavior immediately after an interaction. They can hire and promote employees who disagree constructively. And finally, leaders can model the right behaviors.

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The Gen AI Playbook for Organizations

Leaders can’t afford to take a “wait and see” approach to adopting generative AI. They need a plan for applying it differently than others in the value chain, say the authors. In this article they introduce a framework for thinking about gen AI strategically and offer practical advice on how to apply gen AI to the tasks composing jobs.

The framework focuses on two factors: the cost of errors and the type of knowledge required. If an error in carrying out a task would lead to serious harm, financial loss, or reputational damage, firms must be cautious about employing gen AI to perform it without human oversight. Tasks that rely on explicit data (information that can be captured and processed) are well suited for gen AI. But other tasks are fundamentally harder for it to perform because they involve not just retrieving information but also applying tacit knowledge: empathy, ethical reasoning, intuition, and contextual judgment. Placing the tasks in the appropriate quadrant makes it clear which ones gen AI can handle faster, cheaper, or better.

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The Hidden Beliefs That Hold Leaders Back

High-performing leaders often face internal limiting beliefs that hinder their effectiveness and career growth. Identifying and reframing these hidden blockers can unlock greater leadership potential and improve team and organizational outcomes.

Common limiting beliefs include the need to be involved in every detail, an urgency for immediate results, a belief in always being right, a fear of making mistakes, expectations that others should perform like oneself, an inability to say no, and feelings of not belonging.

Overcoming these blockers involves recognizing and naming the limiting belief, understanding its origins and impact, and reframing it into a more productive belief.

Leaders can then support their teams in identifying and overcoming their own limiting beliefs, fostering a culture of growth and improved performance.

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Case Study: Should a CHRO Abandon Performance Improvement Plans?

At Barton Creek Technologies, Anna Chen, the chief human resources officer, faces a dilemma over the company’s performance improvement plan (PIP). Introduced as a supportive tool to rehabilitate struggling employees, the PIP has widely become perceived as a punitive mechanism. An internal audit revealed that only 15% of employees placed on PIPs complete them, while 60% are terminated and 25% go on stress-­related medical leave, often not returning. Managers admit they lack the training to implement PIPs effectively, and employees describe the plans as stigmatizing and demoralizing. Chen is torn between reforming the program into a mentorship-based system—requiring significant investment and cultural change—or leaving it untouched to avoid straining resources and leadership goodwill, especially amid looming acquisitions and tight budgets.

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Lessons from Market Crashes Past

In the book 1929, the New York Times journalist and CNBC coanchor Andrew Ross Sorkin explores the events leading up to the historic stock market crash that set off the Great Depression. The parallels between them and those chronicled in Sorkin’s earlier book on the 2008 financial crisis, Too Big to Fail, are striking—and more than a little unsettling.

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Life’s Work: An Interview with Esther Duflo

The Nobel laureate talks about why she became an economist, how she and her colleagues popularized the use of randomized controlled trials in their field, which tools and interventions have shown success in reducing poverty, and the role of public-private collaboration in solving seemingly intractable problems.

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