63% Faster Delivery and Up to 3x Higher Throughput Across Product Teams
Context
Merlin Network is a global digital rights agency representing the world’s leading independent music labels and distributors. Their platform powers complex workflows across rights management, reporting, and partner integrations, supporting a large and diverse ecosystem of stakeholders.
As the platform evolved and product complexity increased, delivery performance became critical to supporting both internal operations and external partners.
The Challenge
Delivery was inconsistent, often slower than expected, and difficult to rely on.
Communication between business and engineering teams wasn’t strong enough, leading to misalignment on priorities, unclear expectations, and frequent delays. Commitments were difficult to meet, and delivery timelines were not always reliable.
Teams also relied heavily on a small number of key individuals. Ownership was uneven, accountability wasn’t clearly distributed, and progress often depended on specific people rather than the system working effectively.
While some teams had already adopted AI-assisted development practices, the impact on delivery speed and productivity remained limited, typically in the range of 10–20%, as underlying workflow inefficiencies and coordination issues were still present.
As a result, collaboration suffered, trust between teams weakened, and delivery became harder to manage as complexity increased.
How We Approached It
We started by analysing how work actually moved through the system, from idea to delivery, identifying where delays, dependencies, and misalignment were slowing teams down.
We worked closely with both business and engineering stakeholders to create a shared understanding of priorities, expectations, and how work should flow across teams.
At the team level, we focused on improving day-to-day execution by clarifying ownership, reducing dependencies, and introducing ways of working that allowed teams to operate more independently while staying aligned.
We also focused on strengthening engineering and quality practices to reduce rework and improve overall delivery stability. This created the conditions for existing AI-assisted development practices to deliver significantly more value, as improvements in flow, ownership, and coordination removed the constraints that previously limited their impact.
Changes were implemented incrementally, with continuous feedback and adjustment to ensure improvements were both practical and sustainable.
Results
Business Impact
Delivery became faster, more reliable, and easier to manage across teams.
The organization was able to execute product initiatives with greater confidence, improve alignment between business and engineering, and reduce the operational friction that previously slowed progress down.
Teams operated with clearer ownership and stronger accountability, enabling Merlin to scale product development without increasing complexity or relying on individual contributors to carry delivery.
How Does This Compare to Your Company?
If you’re facing similar challenges or your delivery isn’t as fast and predictable as it should be, we can have a short call to understand your setup and see if we can help.