Part 1: The Science of Change

How culture, networks, and behavior shape the success of change initiatives.

At a Glance: This is the first in a three-part series exploring how ideas and behaviors spread, and how that invisible process shapes an organization’s ability to evolve successfully and at speed. The series examines why 70 percent of change efforts fail, not because leaders choose the wrong strategy, but because they underestimate the social systems that determine whether people actually adopt it. In this opening piece, we explore the science of spread: how adoption happens, why some ideas take root while others fade, and how an organization’s social structure ultimately decides the outcome.

Most change efforts fail not in concept, but in execution. You can explain the strategy, fund the roadmap, update the policies, and even reorganize the chart. People will nod. They may even understand it. And then… nothing happens.

Executives often interpret that silence as resistance, when it’s more often uncertainty. People are waiting to see what happens next. They’re observing how their peers respond, scanning for cues about whether the new behavior is safe, credible, and shared. In other words, they’re looking for social confirmation.

Change rarely fails on paper. It fails in the hearts and minds of employees -- the individuals who, collectively, decide whether to adopt it. While strategy may set the course, the culture determines whether anyone follows.

The 30 percent of transformations that succeed understand this. They know change is less a logical exercise than an emotional one. Research from Northwestern shows that even when people understand a change is in their best interest, they may still decline to act. Adoption depends less on comprehension and more on conviction -- seeing trusted peers model the new behavior until it feels both safe and shared.

Understanding that difference changes the course of strategic change programs. It’s the reason some organizations stay stuck in rollout purgatory while others accelerate change by a factor of four, a dynamic we’ll explore in the next piece of this series. For now, let’s understand the mechanism of adoption and the structure of change.

How Behavior Actually Spreads

Every transformation plan rational and well-thought out. It identifies the gap, maps the dependencies, and defines success. Yet logic alone rarely changes behavior.

Damon Centola’s research on complex contagions helps explain why. Unlike biological contagions, where a single exposure can transmit a virus, social behaviors such as organizational change, innovation, or even rumors require multiple points of confirmation. People don’t adopt after one exposure; they need reinforcement from several trusted peers before they feel convinced enough to act.

Centola calls this the threshold effect. Each of us has a different point at which the evidence feels convincing. Those thresholds are shaped by four forces: how credible the messenger is, how legitimate the behavior feels within the existing culture, how emotionally resonant it is, and how much benefit it appears to create. In short, people are looking for fit, both cognitive and social.

That’s what traditional rollouts often overlook, and what John Kotter found as the principal reason that nearly three out of four strategies fail to take shape. They speak to the mind but not the gut. Information can clarify what is changing, but only social confirmation -- seeing trusted peers practice the behavior -- can provide the confidence to follow.

Successful change leaders understand that both dimensions are essential. Logic builds clarity; emotion restores control. When people have both, adoption accelerates.

The Social Architecture of Change

Every organization has two structures. The first is the formal hierarchy of titles, reporting lines, and decision rights we all recognize. The second is the informal network that lives in hallways and Slack channels, where people turn for clarity, reassurance, or approval.

That second structure is the invisible social architecture of the organization. It’s separate from the org chart but visible in behavior. It’s how information moves, how norms spread, and how culture either accelerates or resists change.

Mark Granovetter’s research on social connections helps explain why. His study of how ideas spread showed that influence (and therefore change) rarely travels along formal lines. It crosses boundaries through informal, cross-functional relationships he called weak ties. These looser connections carry ideas from one pocket of the organization to another. They’re the reason a concept born in a single team can surface in conversations three levels away sparking comments like “how’d you hear about that?”.

This is where change begins to take shape. Not in planning meetings or cascading announcements, but in the informal, often emotional exchanges that give employees permission to believe or to hesitate. Every successful transformation I’ve seen, regardless of industry, found a way to activate that social architecture.

Understanding these dynamics reframes how we think about change. Culture is not a mystery or a mood; it’s a network phenomenon. And even social networks have structure. When we understand how those networks are built we can tap into the organic channels where people look for social confirmation.

In Centola’s terms, these connections help people cross their adoption thresholds. Each interaction and trusted proof point reduces uncertainty and builds the clarity and control individuals need to try something new.

That’s where tools like Organizational Network Analysis come in. They make the invisible visible. At scale, they identify the essential elements of social change: who people trust, where influence concentrates, and which connections hold the power to unlock momentum.

Once an organization can see that, culture stops being an article of faith and becomes an operating system it can understand.

Designing for Activation

Traditional transformation programs focus on alignment: clear vision, detailed milestones, consistent communication. Those are essential. But what actually drives adoption is the social process through which people decide, collectively, to participate. The difference is subtle but profound.

This is where behavioral science meets organizational design. Change accelerates when two conditions are met: clarity and control. People need to understand what’s changing and why, but they also need to feel ownership over how it unfolds. Clarity satisfies the logical side of adoption. Control satisfies the emotional side. When both exist, individuals no longer feel like subjects of change, but become its agents.

ONA gives leaders a way to design for both. By identifying individuals who already hold trust and influence, leaders can invite those people into the process early. Not to communicate the change, but to shape it. When those peers adjust the rollout, translate language, or adapt rituals to fit their teams, they begin the process of social confirmation. The behavior begins to spread naturally, reinforced by repetition and credibility through their networks.

This is what we mean by engineering culture. It isn’t about controlling people; it’s about creating the conditions that make adoption the natural outcome. Leaders don’t need to choose between logic and emotion. They need to design systems that give people both the clarity to understand the change and the control to make it their own.

Seeing the System Beneath the Surface

When we talk about transformation, we often talk about plans. Timelines. Governance. Dashboards. While change may start with process, it takes shape through people.

Culture is the sum of their choices: whether they adopt, hesitate, or wait to see what happens next. Each choice is influenced by countless small signals of who modeled the new behavior, who endorsed it, and who benefitted. When those signals accumulate through trusted relationships, change stops being an initiative and becomes part of how the organization thinks and acts.

That truth has never mattered more. Artificial intelligence is redefining the boundaries of strategy, operations, and work itself. Every firm is racing to integrate it, yet most are still treating adoption as a technical rollout rather than a social transformation. Studies from MIT and the RAND Corporation show that even where AI strategies are sound, execution falters because employees don’t understand how it changes their work or their role within it.

Across industries, we’re seeing the consequences. Firms like Target, Amazon, and Meta are restructuring workforces to prepare for automation. Others, like Klarna, are racing ahead but still grappling with how to keep culture aligned to new capabilities. Governments are even mulling whether to track layoffs relative to AI adoption, a sign of how disruptive this moment truly is.

These shifts make the human side of transformation the decisive factor. Technology may redefine what’s possible, but people determine what’s real. The organizations that thrive in this new era will be those that understand both sides of the equation: how to design execution for clarity and culture for activation.

About the Author: Jason is a behavioral economist and founder of 3Fold Collective, an organizational design firm helping leaders diagnose and reshape cultural dynamics. Visit 3FoldCollective.com to discover more.

References

Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179–211.

Centola, D. (2018). How behavior spreads: The science of complex contagions. Princeton University Press.

Christakis, N. A., & Fowler, J. H. (2009). Connected: The surprising power of our social networks and how they shape our lives. Little, Brown.

Dweck, C. S. (2006). Mindset: The new psychology of success. Random House.

Granovetter, M. S. (1973). The strength of weak ties. American Journal of Sociology, 78(6), 1360–1380.

Greiner, L. E. (1998, May–June). Evolution and revolution as organizations grow. Harvard Business Review.

Kahneman, D. (2011). Thinking, fast and slow. Farrar, Straus and Giroux.

Kotter, J. P. (1995, May–June). Leading change: Why transformation efforts fail. Harvard Business Review.

Massachusetts Institute of Technology (MIT) & MLQ. (2025). State of AI in business 2025 report (v0.1). MLQ.ai.

RAND Corporation. (2025). The state of AI adoption in U.S. organizations: Early lessons from implementation and workforce impact (Report No. RRA2680-1).

Rogers, E. M. (2003). Diffusion of innovations (5th ed.). Free Press.

Congratulations, you’ve reached the rare air of readers who make it to the very end. That alone suggests a high tolerance for complex contagions and probably a soft spot for behavioral science. Before you go, see what happens when that social architecture breaks down. Our story on Starbucks shows why even the best strategies fail when culture doesn’t feel seen. Pour yourself another cup and head over.