Problems with the Center of Excellence Model

The DevOps Research and Assessment (DORA) has conducted comprehensive multi-year studies on high-performing technology organisations. Their 2019 State of DevOps report highlights that companies using high demand Centers of Excellence (CoEs) significantly underperform compared to those with decentralised approaches. Given this evidence, we need to understand why this model falls short and explore better alternatives.

Not All CoEs Are the Same though. To analyse the challenges of CoEs effectively, we need to differentiate between the two primary types:

1. Continuous Collaboration CoEs – These support functions that teams need to engage with on an ongoing basis, such as Research, Design, and DevOps.

2. Transactional CoEs – These handle specialised expertise that teams occasionally require, including Legal, Finance, and Machine Learning.

While both types have inefficiencies, Continuous Collaboration CoEs pose the most significant challenges due to their ongoing interaction with product teams.

The Challenges with Continuous Collaboration CoEs

Process: The Dependency Problem

CoEs are often created under the assumption that pooling expertise reduces costs. In reality, they introduce bottlenecks that slow teams down. A Continuous Collaboration CoE inherently creates a dependency on a specialised group of experts. When successful, demand for their services increases, often exceeding capacity. This leads to longer wait times and frustration among product teams that need timely input to maintain their delivery cadence.

For functions like research and design, where quick iteration and deep team involvement are crucial, these issues make CoEs particularly ineffective. Teams need embedded expertise rather than an external service that slows them down.

Siloed Knowledge: Losing Nuance and Context

When functions like research are conducted outside of product teams, valuable tacit knowledge is lost. For example:

• A researcher may collect insights but fail to capture nuances that a product manager or engineer would notice.

• Insights lose context when transferred from one team to another, reducing their impact.

• Teams that were not involved in the research process may be less likely to trust or act on the findings.

This disconnect between research and execution slows decision-making and weakens innovation.

Hoarding of Skills: Reinforcing Dependency

By centralising expertise, CoEs create a fragile system which can suffer when key people leave or when demand spikes beyond capacity. Instead of knowledge flowing across teams, it remains locked in silos, increasing risk and slowing decision-making.

A CoE consolidates specialised knowledge within a small group, preventing product teams from developing expertise in key areas. This leads to:

• Reliance on the CoE – Teams become dependent on external specialists rather than improving their own skills.

• Lack of Continuous Learning – Knowledge remains concentrated within a centralised function instead of being distributed across teams.

• A Single Point of Failure – If key CoE members leave, critical knowledge is lost.

Monopoly: Lack of Incentive to Improve

Without competition, internal CoEs can become complacent monopolies, leading to misaligned incentives:

• They become service-driven rather than outcome-driven. CoEs optimise for their own efficiency rather than business impact.

• They resist change. Without competitive pressure, there’s little incentive to experiment or adopt better ways of working.

• They can impose rigid standards that don’t fit teams. CoEs often create one-size-fits-all processes that hinder agility.

Without external competition or accountability, CoEs risk becoming inward-focused and ineffective.

The Way Forward: Improving the CoE Model

Improving Continuous Collaboration CoEs: Decentralisation and Enablement

For functions that require continuous engagement, such as research and design, decentralisation is the best approach. This involves:

• Embedding experts within product teams instead of isolating them in a CoE.

• Training teams in core skills, enabling them to perform basic tasks independently.

• Shifting CoEs from execution to enablement, focusing on training, coaching, and providing reusable frameworks instead of doing the work themselves.

This fosters self-sufficiency and faster decision-making, reducing dependency on a centralised function.

Improving Transactional CoEs: Breaking the Monopoly

While transactional CoE’s suffer from all of the same problems as continuous collaboration CoE’s, the frequency of interaction means full decentralisation isn’t practical. Instead, organisations should focus on improving performance through competition.

Allowing product teams to seek external solutions forces CoEs to improve their offerings, which often leads to a "productisation" of their services.

Examples of Internal Teams Becoming Competitive Services:

• Amazon Web Services (AWS) – Originally an internal operations team, AWS emerged because Amazon productised its infrastructure services to improve internal efficiency. It became so effective that they launched it as a standalone business.

• Haier Finance – Haier allowed internal teams to use third-party finance providers, forcing its internal finance function to improve service. This led to the finance department to change how they worked and interacted with the teams around the organisation. Their new processes were so valuable they started selling them externally and become a competitive, profit-generating business.

• Fulfillment by Amazon (FBA) – Amazon’s logistics team optimised internal fulfillment services so successfully that external sellers wanted to use them too, leading to the creation of FBA.

This approach ensures internal teams remain customer-focused, competitive, and continuously improving.

Conclusion: Moving Beyond the CoE Model

While Centers of Excellence were designed to provide specialised expertise and consistency, they often introduce inefficiencies, dependencies, and silos that slow down innovation. By shifting towards decentralisation, self-service capabilities, and a competitive service model, companies can create more agile, empowered, and effective product teams.

For continuous collaboration capabilities like research and design, embedding expertise within teams is the best way forward. For transactional capabilities, a CoE can still be effective—but only if it is structured to enable teams rather than control them.

By rethinking the CoE model, organisations can move towards a more adaptive, decentralised, and efficient way of managing expertise.