Spotify's Organizational Evolution: From Hierarchy to Distributed Leadership

This post is part of the “Leadership Evolution” series, exploring how organizations navigate the messy, non-linear paths of transformation from conventional approaches to ecosystem-inspired models. Each post examines not just what these organizations became, but how they got there—offering insights for leaders navigating their own organizational evolution.

Introduction: The Before Picture

In 2006, when Daniel Ek and Martin Lorentzon founded Spotify, they didn’t set out to create a revolutionary organizational model. They were building a music streaming service in a landscape dominated by piracy and struggling music sales. Their early organizational structure

resembled most tech startups—a small, tight-knit team with informal coordination and direct communication. In other words, the kind of place where “organizational design” meant deciding who brought snacks to the all-hands meeting.

As they grew beyond their first dozen employees, they began facing the classic scaling challenges. Traditional management hierarchies seemed at odds with the need for rapid innovation and autonomy that engineering teams craved. The path from this conventional beginning to what became known as “the Spotify Model” wasn’t straightforward or planned. It emerged through experimentation, failure, and adaptation—much like the savanna ecosystems that continually reshape themselves through collective intelligence.

Crisis Points & Catalysts for Change

Spotify’s evolution was driven by pain points that emerged as they scaled. Around 2011, with over 100 employees, they hit coordination barriers. Teams were stepping on each other’s work, decision-making slowed, and their ability to respond quickly to market opportunities diminished.

Henrik Kniberg, who joined as an Agile coach during this period, describes the catalyst: “It wasn’t working. Teams were becoming bottlenecked by dependencies, and people were frustrated with the growing bureaucracy. We needed to find a way to maintain startup speed at scale.”

Another crisis point came as they expanded internationally, opening offices in multiple countries. The traditional approach—identical processes across locations—created friction with local needs and cultures.

These pressure points forced fundamental questions about how to organize for both autonomy and alignment—questions that would shape their experimental approach to organizational design.

We didn’t set out to create a model. We were just trying to solve real problems that were slowing us down. – Henrik Kniberg

Evolution of Structure: From Hierarchical Plains to Savanna Ecosystems

The now-famous “Spotify model” with its squads, tribes, chapters, and guilds didn’t emerge fully formed. It evolved through multiple iterations, with significant differences between the publicized model and the lived reality.

Initial experiments: Their first structural innovation was simply breaking the engineering department into cross-functional teams (later called “squads”) with end-to-end responsibility for specific features. This initial change revealed both benefits (faster delivery) and new challenges (consistency and knowledge sharing across teams).

Structural iterations: To address cross-team challenges, they experimented with various coordination approaches:

Matrix-like structures with functional reporting lines alongside team membership
Communities of practice for shared knowledge
Product owner circles for alignment

These eventually evolved into the more refined concepts of chapters (functional skill alignment) and guilds (communities of interest), but not without false starts.

Failed experiments: Not all structural experiments succeeded. Early attempts at completely flat structures without any reporting relationships created accountability gaps. Similarly, their first approach to “tribes” (collections of squads) set the size too large, reducing their effectiveness as coordination units. As one engineer put it, “We learned that when your tribe is too big to fit in a pizza place, you’ve probably gone too far.”

Evolutionary pressures: Interestingly, their approach evolved differently across functions. While engineering embraced the squad model early, other departments like marketing and finance adapted it later and differently. This wasn’t planned but emerged as different functions experienced different evolutionary pressures.

The key insight: their structure wasn’t designed comprehensively but evolved incrementally to solve specific pain points while preserving autonomy and alignment.

Leadership Transitions: From Alpha Leaders to Sentinel Roles

Spotify’s leadership approach evolved dramatically from conventional management to what resembles the distributed vigilance seen in savanna species.

Initial leadership model: Early Spotify had traditional managers responsible for direction and team performance. As autonomy increased, this created tension between manager authority and team self-direction.

Sentinel role evolution: Gradually, leadership roles transformed from directing to sensing and contextualizing. Like meerkats taking turns watching for danger while others work, they developed rotating roles focused on environmental awareness and information sharing rather than control.

Product ownership adaptation: The product owner role evolved from a decision-maker to an alignment creator—someone who ensured teams had the context to make good autonomous decisions.

Leadership capacity building: Rather than concentrating leadership in management roles, they worked to distribute leadership capacity throughout the organization. Informal leaders emerged based on situation and expertise rather than position.

Management identity crisis: This transition wasn’t without challenges. Many managers struggled with their changing identity. As one former Spotify manager noted: “I had to unlearn success metrics I’d used my entire career. My value wasn’t in having answers but in fostering environments where others found better answers than I could.” Turns out “Chief Answering Officer” isn’t actually a sustainable leadership position.

The evolution of leadership at Spotify shows how traditional directing functions can transform into sensing, contextualizing, and boundary-setting functions that enable rather than control the system.

Cultural Evolution: Developing Collective Intelligence

Spotify’s culture evolved alongside its structure, with increasing emphasis on collective sensing and response capabilities.

Trust development: Early attempts at autonomy revealed that trust doesn’t automatically emerge from structural change. They developed specific practices to build trust:

Transparent sharing of mistakes and learnings
Regular retrospectives without management presence
Celebration of teams solving problems their own way, even if imperfectly

Squad health checks: Their now-famous health check model didn’t exist initially. It evolved as they recognized that teams needed consistent ways to assess their own functioning. The first versions were much simpler, focusing on basic team satisfaction. Later iterations added dimensions like technical quality and learning.

Communication pattern shifts: Communication evolved from centralized cascading to networked sharing. They invested in information radiators (visible displays of key metrics and activities) and internal sharing platforms to ensure everyone had context for decisions.

Collective rhythm finding: They discovered that completely independent team timing created coordination problems. They gradually developed synchronized increments—not to control what teams did but to create natural points for alignment.

The cultural evolution at Spotify parallels how savanna species develop collective intelligence through distributed awareness and shared signals, allowing coordinated movement without centralized control.

Resistance & Adaptation Cycles: Controlled Burns and Migration

Spotify’s evolutionary path included significant resistance and adaptation cycles that refined their approach.

Internal resistance: Not everyone embraced the autonomous model. Some engineers preferred clearer direction, and some managers struggled with their changing role. Rather than forcing conformity, they created space for different working styles while maintaining non-negotiable principles.

Controlled disruption: Like savanna ecosystems that benefit from periodic fires, Spotify instituted regular reorganizations to prevent calcification of team boundaries that no longer served their purpose. These controlled disruptions prevented larger, more chaotic reorganizations later. Think of it as organizational Marie Kondo—regularly asking of each team structure, “Does this still spark joy… or at least functional software delivery?”

Migration patterns: As priorities shifted, resources needed to flow to new opportunities. They developed lightweight processes for teams to “migrate” to new problems, preserving team cohesion while allowing organizational focus to shift.

External skepticism: As their model gained fame, external criticism mounted, claiming it couldn’t work at scale or in other contexts. This external pressure actually helped refine their approach, forcing clearer articulation of underlying principles versus context-specific practices.

Adaptation during hypergrowth: Perhaps their biggest challenge came during periods of hypergrowth when hundreds of new employees joined quarterly. Their response was cultural immersion rather than process training—ensuring new employees absorbed principles through experience rather than documentation.

These cycles of resistance and adaptation demonstrate how organizational evolution, like ecosystem evolution, isn’t linear but cyclical—with each challenge refining the model.

Scaling Migration Intelligence: Growing the Herd

As Spotify grew from hundreds to thousands of employees across multiple continents, maintaining their model required solving new coordination challenges.

Knowledge transfer mechanisms: Simple osmosis worked for knowledge sharing when small, but scale required more intentional approaches. They developed patterns for sharing without standardizing:

Regular demos where teams shared their work and learnings
Internal conferences and unconferences
Rotation programs between teams and offices

Decision-making evolution: As scale increased, decision rights needed clarification. They developed the “DIBBs” framework (Data, Insights, Beliefs, Bets) to make decision rationales transparent without centralizing decisions themselves. This wasn’t just another four-letter acronym for the corporate jargon bingo card—it actually changed how teams justified their choices beyond “because we’re agile” or “the VP said so.”

Reconciling global and local: International expansion created tension between global consistency and local adaptation. Rather than enforcing uniformity, they distinguished between principles (universal) and practices (locally adapted), allowing their model to take different forms in different locations.

Multiple layers of alignment: Simple alignment mechanisms broke at scale. They developed a “nested alignment” approach where alignment happened at multiple levels—squad, tribe, and organization—with appropriate mechanisms at each level.

The scaling story demonstrates that maintaining distributed coordination requires deliberate attention to the mechanisms that enable collective intelligence as an organization grows.

Today’s Reality and Continuing Evolution

Today’s Spotify doesn’t perfectly match either the widely-publicized “Spotify Model” or any static organizational ideal. Their reality includes both the benefits of their evolutionary approach and ongoing challenges.

Model vs. reality: The “Spotify Model” as described in widely-shared articles represents a snapshot of their thinking at a particular moment, not today’s reality. Their actual organization continues to evolve beyond those early articles.

Ongoing challenges: They still struggle with:

Balancing autonomy and alignment as they’ve grown to thousands of employees
Maintaining innovation speed with increasing technical complexity
Finding the right balance of formal and informal coordination mechanisms

Leadership lessons: Their experience has reinforced that organizational evolution never ends—what works at one stage or in one context requires adaptation for the next. This ongoing evolution isn’t a bug but a feature of their approach.

If you’re copying the Spotify Model, you’re doing it wrong. The most important part isn’t the structure but the principles and the evolutionary approach. – Henrik Kniberg

Or as one Spotify developer more colorfully put it: “Copying our model is like buying someone else’s gym membership and expecting to get fit. The value is in the workout, not the paperwork.”

The honest assessment of their current state serves as an important reminder that no organizational model represents an endpoint—only a stage in ongoing evolution.

Takeaways for Leaders

For leaders inspired by Spotify’s journey, the path isn’t about implementing their specific model but understanding how to foster similar evolutionary capabilities in your context:

Solve real problems, not theoretical ones: Start with concrete pain points rather than abstract organizational ideals. Every significant change at Spotify addressed a specific problem hindering their effectiveness.

Clarify principles before practices: Define the principles you want to uphold (like team autonomy or customer focus), then allow practices to emerge that honor those principles in your context.

Create safe-to-fail experiments: Design smaller, reversible organizational experiments rather than comprehensive reorganizations. Spotify’s approach evolved through dozens of small experiments, not one grand design.

Invest in alignment mechanisms: As you distribute authority, increase investment in alignment tools like clear company direction, transparent metrics, and frequent communication forums.

Develop sensor networks: Create mechanisms that help the organization sense changes and opportunities through distributed awareness rather than centralized monitoring.

Build leadership capacity, not just leadership roles: Develop the capabilities of informal leadership throughout the organization rather than concentrating them in management positions.

Expect evolution, not stability: Recognize that your organizational model should continue evolving as the environment, scale, and challenges change.

Reflection Questions for Your Organization

Consider these questions to apply Spotify’s evolutionary lessons to your context:

What concrete problems would be addressed by moving toward more distributed authority in your organization?
Where might you create safe-to-fail experiments with team autonomy without risking core business performance?
What information and context do teams need to make good autonomous decisions in your environment?
How might you develop “sentinel roles” that focus on environmental awareness and context-sharing rather than directing work?
What mechanisms could help your organization develop greater collective intelligence, where patterns and opportunities are sensed throughout the system rather than just at the top?

The most valuable lesson from Spotify’s journey isn’t their specific squad model but their approach to organizational evolution: patient development of distributed intelligence that allows the organization to sense and respond to opportunities without centralized control. Like a savanna ecosystem, they demonstrate that remarkable coordination can emerge when we create the conditions for collective awareness and autonomous action aligned toward shared purpose.

Spotify’s Organizational Evolution: From Hierarchy to Distributed Leadership