There Is No Single Winning Studio
The European study of venture studios asks a narrower question than “What makes a startup good?” It asks which combinations of studio conditions are associated with a high rate of successful exits. This chapter explains what that measure captures, how four different configurations reach it, and why the result should change how a founder or investor reads a studio claim. The useful judgment is not which single feature wins, but whether a studio’s experience, specialization, affiliations, international reach, and location fit together for the outcome being measured.
What the study calls success
Exit productivity, not every kind of value
The study defines venture-studio success as the number of successful exits achieved by a studio’s startups divided by the studio’s lifetime through 2023. The measure is intended to capture production efficiency: a studio that repeatedly creates, develops, and exits ventures is producing outputs over time. Dividing by lifetime also makes studios of different ages more comparable than simply counting their total exits.
That is a reasonable measure for a production-oriented organization, but it is not a complete definition of success. It does not tell us how much value an exit created, how many jobs a portfolio generated, how innovative its ventures were, whether the companies survived without a sale, or whether founders and customers benefited in ways the studio’s financial measure does not record. The measure is especially important to interpret before the study’s configurations are discussed. The four paths are associated with exit productivity, not with every outcome a reader might care about.
The method is fuzzy-set Qualitative Comparative Analysis, usually shortened to fsQCA. In plain language, fsQCA looks for combinations of conditions that appear together in cases with a particular outcome. It does not ask only whether more founder experience is associated with more exits on average. It can ask whether experience combined with institutional affiliation works, whether specialization can work with a less prominent location, or whether international orientation matters differently in a generalist studio.
This matters because venture studios are not identical organizations operating under identical constraints. A condition can be useful in one configuration and unnecessary in another. A prominent ecosystem may supply capital and talent to a generalist studio, while a specialized studio may create enough domain knowledge and network access to operate outside a leading hub. A method that assumed one average effect for each condition could hide those alternatives.
The study began with a publicly available database containing 407 venture studios and 1,844 associated startups. It then narrowed the cases in stages: to European studios, to studios old enough to provide a nine-year outcome horizon, to those founded between 2009 and 2014 so that the economic conditions were more comparable, and finally to 25 studios whose identity and exit information were verified through multiple sources. This filtering improves comparability, but it also defines the population to which the result most directly applies.
The five conditions in the analysis describe different levels of the studio. Founder experience represents accumulated entrepreneurial experience among the founders. Affiliation records a formal institutional relationship at founding. Specialization captures whether the studio began as a generalist, broad-vision, or highly focused organization. Born-global orientation captures the share of portfolio startups established internationally.