Organizations increasingly rely on experimentation to drive data-informed decision-making and innovation. While models like the Flywheel offer guidance on scaling, they often assume a fixed operational context without addressing its impact on experimentation practices. This study examines how experimentation team structures interact with an organization’s operating model. Based on semi-structured interviews with 19 industry experts, we identified recurring organizational patterns and developed a multi-dimensional taxonomy. Our findings reveal four quadrants defined by team structures (centralized, decentralized, Center of Excellence) and operational models (Product vs. Feature-Management Operating Models). Each quadrant presents distinct challenges and trade-offs. By clarifying these interactions, our results support organizations in evaluating their experimentation maturity and applying targeted changes—such as introducing a Center of Excellence or adjusting operating models—to enhance scalability and alignment.