In the five years since the publication of Team Topologies: Organizing Business and Technology Teams for Fast Flow by Matthew Skelton and Manuel Pais, the book’s principles and patterns have had a profound impact on how organizations structure and operate their software development teams. Through a series of case studies from diverse companies across multiple industries, we can see how Team Topologies has enabled organizations to accelerate software delivery, improve team autonomy and cognitive load management, and create more resilient and adaptable structures.

The core concepts of Team Topologies—including the four fundamental team types, team interaction modes, and a focus on cognitive load—have provided companies with a shared vocabulary and set of principles to guide their organizational transformations. Whether dealing with rapid growth, mergers and acquisitions, or the need to modernize legacy systems, Team Topologies has proven to be a flexible and powerful framework for shaping high-performing technology organizations.

In this article, we will look back at five years of Team Topologies through several case studies that have been shared publicly on the Team Topologies community page. Through these case studies, we can see how far we have come and how far we have yet to go.

Stream-Aligned Teams as the Foundation

A consistent theme across the case studies is the adoption of stream-aligned teams as the primary team type. These cross-functional, product-focused teams align closely with specific business domains or customer value streams. 

At Footasylum, a UK-based fashion retailer, the transition to stream-aligned teams addressed issues of siloed knowledge and slow delivery that had emerged as the company grew rapidly. By organizing teams around clear business domains like e-commerce, retail, and warehousing, Footasylum was able to give teams clearer purpose and autonomy.

Similarly, PureGym moved from short-lived project teams to long-lived, stream-aligned product teams organized around core business capabilities like member acquisition, retention, and gym operations. This shift led to greater ownership, faster delivery, and improved team morale.

Uswitch, the UK price comparison site, has long been organized around stream-aligned teams focused on different consumer services. Their then CTO, Paul Ingles, noted that this approach, combined with supporting platform teams, allowed them to “focus on broader outcomes, continual iteration and improvement, and a strong amount of accountability.”

The insurance company Gjensidige restructured its Digital Division to create stream-aligned product teams responsible for core business processes like pricing, digital sales, and claims handling. These multi-disciplinary teams now have end-to-end ownership of specific business domains.

By aligning team structures more closely with business domains and customer value streams, these organizations have reduced team dependencies, clarified ownership, and accelerated value delivery to customers.

Platforms and Cognitive Load Management

Another key impact of Team Topologies has been a more intentional approach to managing cognitive load through platform teams and enabling teams. Many organizations have found that as their systems grew in complexity, it became impossible for individual teams to maintain expertise across all aspects of the technology stack.

Docker provides an instructive example of this evolution. As they transitioned to cloud-native development, they realized their existing teams couldn’t keep up with the expanding complexity. Inspired by Team Topologies, they introduced a dedicated platform team to manage the underlying container orchestration layer and related tooling. This allowed their stream-aligned teams to focus more on delivering customer value without getting bogged down in infrastructure concerns.

Footasylum took a similar approach, creating platform teams for e-commerce APIs, cloud infrastructure, and data. These teams provide services that reduce cognitive load for the stream-aligned product teams.

At Improbable, adopting Team Topologies principles helped them successfully integrate an acquired company by clarifying team responsibilities and interaction modes. They created platform teams to provide infrastructure, tooling, and shared services, allowing their game development teams to focus on building compelling virtual worlds.

Visma, a large European software company, has invested heavily in platform teams and services to support its many stream-aligned Service Delivery Teams. Centralized platform services for monitoring, developer tools, and application security testing help reduce cognitive load and allow teams to focus on their core responsibilities.

The Norwegian insurance company Gjensidige has created several platform teams to accelerate delivery by their stream-aligned teams. These include platforms for design, analytics, web applications, CRM, and DevOps tooling. 

Across these examples, we see how the intentional use of platform teams has allowed organizations to provide robust, scalable infrastructure and tooling while letting stream-aligned teams focus on delivering customer-facing functionality. This division of responsibilities has proven key to managing complexity as organizations and systems scale.

Evolving Team Structures

The Team Topologies approach emphasizes that team structures should evolve over time as circumstances change. Several case studies illustrate how organizations have used Team Topologies concepts to guide this evolution.

Flo Health, a popular women’s health app, has gone through multiple iterations of its team structure as they’ve grown. Flo started with domain-focused teams, then added “mode teams” focused on personalization across domains. Most recently, Flo has introduced the concept of “channels” and “widgets” to create cleaner abstractions between teams. Throughout this evolution, Team Topologies interaction modes have helped Flo manage dependencies and team collaboration.

CROZ, a professional services company, used Team Topologies patterns to guide the introduction of a new platform team. This helped them manage the increasing complexity of cloud-native development while maintaining team autonomy. They’ve found the concepts of team interaction modes particularly helpful in clarifying how the platform team should work with other teams in the organization.

Wealth Wizards went through multiple iterations of their team structure guided by Team Topologies principles. They started by breaking a large team into smaller stream-aligned teams, then refined ownership boundaries, and finally introduced an enabling team to support capability development across teams. This iterative approach allowed them to continuously improve team cognitive load and ownership.

PureGym‘s journey shows a similar pattern of evolution. They started with short-term project teams, then moved to longer-lived but still temporary teams, before finally adopting stable stream-aligned product teams supported by platform and enabling teams. Each step brought improvements, but the final Team Topologies-inspired structure delivered the greatest benefits in terms of ownership, speed, and quality.

These examples highlight how Team Topologies provides a flexible framework that organizations can use to guide their team structures as they grow and as their needs change over time.

Interaction Modes and Team APIs

The Team Topologies concepts of team interaction modes and team APIs have given organizations new tools for managing coordination between teams. 

Footasylum found the interaction modes particularly helpful for their product managers. They allowed them to have more directed conversations about upcoming work and dependencies, helping teams plan their collaboration needs in advance rather than relying on ad hoc coordination.

At Improbable, clearly defined interaction modes helped them manage the integration of an acquired company. By intentionally using collaboration and facilitation modes, they could build necessary capabilities while maintaining clear ownership boundaries.

NAV, the Norwegian welfare administration, has adopted interaction modes to guide how its platform teams work with stream-aligned teams. Nav aims for X-as-a-Service as the default mode but uses collaboration modes when developing new platform capabilities. 

Several organizations have implemented the concept of team APIs to make team responsibilities and interaction patterns more explicit. Visma uses team APIs to clarify how teams should interact with their centralized alerting service. Improbable created team APIs to document team responsibilities, communication channels, and interaction guidelines.

By providing clear patterns for team interactions, Team Topologies has helped organizations reduce coordination overhead and create cleaner interfaces between teams.

Challenges and Limitations

While the case studies overwhelmingly point to positive outcomes from applying Team Topologies, they also highlight some challenges.

Several organizations noted that the transition to new team structures can be disruptive and time-consuming. Footasylum‘s then CTO emphasized that reorganizing teams doesn’t immediately solve all problems—it takes time for new structures to settle and for teams to build necessary capabilities.

PureGym found that even after adopting stream-aligned teams, they sometimes had to compromise their structure to meet urgent business needs. In some cases, they had to borrow resources from other teams to hit aggressive targets.

Paul Ingles, formerly of Uswitch, noted that it can be challenging for platform teams to see the full impact of their work, as the benefits are often distributed across many stream-aligned teams. Finding ways to recognize and celebrate platform team contributions has been important.

Multiple case studies emphasized that Team Topologies is not a rigid blueprint, but rather a set of patterns that need to be adapted to each organization’s specific context. The Visma case study notes that “splitting the cognitive load relieved much of the pressure from stream-aligned teams and enabled them to focus better on delivering value to end users” but that they “still have lots to improve.”

These challenges highlight that while Team Topologies provides valuable patterns and principles, implementing them effectively requires ongoing effort, adaptation, and learning.

Measurable Impact

Across the case studies, organizations reported significant measurable improvements after adopting Team Topologies-inspired structures:

• Footasylum increased their software deployment frequency from 6 releases per year to over 1,250 deployments per week.
• PureGym saw improvements in key metrics like Trust with Peers (8.1 to 9.0), Engagement (7.6 to 8.4), and Mastery (6.8 to 7.9) after restructuring teams.
• Improbable achieved a 30x reduction in Mean Time to Recover (MTTR) and a 5x reduction in major incidents after adopting stream-aligned and platform teams.
• Gjensidige Insurance reported 40% annual growth in digital sales over 5 years, 100% growth in digital customer service, and up to 40% of claims now handled automatically.
• Docker‘s platform team approach enabled them to quadruple annual recurring revenue while maintaining development velocity.

While not every organization provided specific metrics, the case studies consistently point to improvements in delivery speed, reliability, team autonomy, and business outcomes after applying Team Topologies principles.

Conclusion

Five years after its publication, Team Topologies has proven to be a powerful and flexible framework for shaping effective technology organizations. By providing clear team types, interaction modes, and a focus on cognitive load, it has given leaders a shared language and set of principles for evolving their organizational structures.

The case studies show how diverse organizations—from startups to large enterprises, across industries from retail to insurance to gaming—have successfully applied the concepts of Team Topologies. Common patterns emerge around the value of stream-aligned teams, the importance of cognitive load management through platforms, and the benefits of clear team interaction modes.

At the same time, the studies highlight that Team Topologies is not a rigid prescription but rather a set of adaptable patterns. Organizations have evolved and refined their structures over time, learning and adjusting as they go.

Based on the evidence from these case studies, Team Topologies is well-positioned to continue providing value as a framework for shaping high-performing technology organizations in the years to come.

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