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The current craze for unicorns and other hyper growth companies brings a novel interest in what makes the exceptional performance of a firm. Literature about technological innovation explains the bond between the performance level reached by a company and its ability to promote radical innovations. But if the theory of disruption enables to validate various levels of innovation, it faces difficulties to define more accurately the drivers of hyper growth. This thesis comprises five main moments to better understand what drives fast growing young technological companies. To survey this question we have defined one single scientific field, namely microfluidics, focusing on active clusters and spinoffs from the same parent in this sector. The first phase aims at highlighting evolutionary prospects about scientific enhancements in microfluidics leading to successful innovations. It shows that there is no innovation “due to succeed” and that technical innovations do not make progress as linearly as usual technological trees found in academic literature could suggest. That leads to a kind of rewriting in the evolution of inkjet technology. The second phase intends to explore performance among groups of spinoffs from the same parent. We consider the 2 European clusters in microfluidics. It appears that all these firms are developing, but they do not reach the same degree of performance. From far, yet, the differences in performance do not clearly appear. To explain variations, we study each spinoff’s growth during the 5 first years after launching before comparing with the growth during the 5 first years of the mother company. We have to look in details to the European clusters, to see also technology variants. A fractal approach is thus enabling to understand that performance of firms is like hidden in technology layers. The third moment elaborates on the relationship between a superior technology and an outstanding performance level. In the case of spin off performance we are not at a stage where we could put the phenomenon under equation! That is why it was appropriate to survey the scientific and technological clusters in Europe from a case study perspective. It appears then that seemingly similarly disrupting technologies do not end up capturing similar value. In fact, slight differences in the technologies used are leading to massive differences in performance. We discover in the end that one single variable is rooting Outstanding Performance. In a fourth phase we restate the initial question to better understand what makes Outliers and Outstanding Performance. Where we show that exceptional value capture is coming from exceptionally fitting of the technology considered to a very specific application. Outstanding Performance is thus attached to an extraordinary EBITDA. The last moment of the dissertation is devoted to ultimately check findings. The whole checking process eventually led to the conclusion that outliers and outstanding performance are permanently referring to a kind of “uniqueness” embedded in the various cases of exceptional value capture. Such a unique feature, qualifying outliers among technological startups, makes by itself a research topic. As more and more attention is given to specific statistical populations, not only could this research contribute to improve the knowledge about hyper growth companies but it could also impact methods in statistics; and beyond methods: statistics themselves as a discipline.