Aligning Experimentation with Product Operations: A Taxonomy for Structuring Experimentation Teams
Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-review
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Software Engineering and Advanced Applications - 51st Euromicro Conference, SEAA 2025, Proceedings: 51st Euromicro Conference, SEAA 2025 Salerno, Italy, September 10–12, 2025 Proceedings, Part III. ed. / Davide Taibi; Darja Smite. Vol. 3 Cham: Springer Nature Switzerland AG, 2026. p. 23-38 (Lecture Notes in Computer Science; Vol. 16083).
Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-review
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RIS
TY - CHAP
T1 - Aligning Experimentation with Product Operations
T2 - 51st Euromicro Conference on Software Engineering and Advanced Applications - SEAA 2025
AU - Stotz, Nils
AU - Labay, Ben
AU - Vermeer, Lukas
AU - Drews, Paul
N1 - Conference code: 51
PY - 2026
Y1 - 2026
N2 - 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.
AB - 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.
KW - Business informatics
KW - Center of Excellence
KW - Continuous Experimentation
KW - Experimentation Program
KW - Product Operating Model
UR - http://www.scopus.com/inward/record.url?scp=105016557008&partnerID=8YFLogxK
U2 - 10.1007/978-3-032-04207-1_3
DO - 10.1007/978-3-032-04207-1_3
M3 - Article in conference proceedings
SN - 978-3-032-04206-4
SN - 978-3-032-04208-8
VL - 3
T3 - Lecture Notes in Computer Science
SP - 23
EP - 38
BT - Software Engineering and Advanced Applications - 51st Euromicro Conference, SEAA 2025, Proceedings
A2 - Taibi, Davide
A2 - Smite, Darja
PB - Springer Nature Switzerland AG
CY - Cham
Y2 - 10 September 2025 through 12 September 2025
ER -