Pivoting in Software Startups

Context: Software startups are able to produce cutting-edge products significantly contributing to the world economy. However, lack of resources, high reactiveness, and uncertain conditions are some of the road blocks on their path to success making startup a challenging endeavor. In order to handle intense time pressure and survive in dynamic markets, software startups have to make crucial decisions constantly on whether to change directions or stay on chosen courses, or in the terms of Lean Startup, to pivot or to persevere. Pivot is considered as an essential activity for software startups to survive, grow and eventually obtains a sustainable business model. Most of the successful software startups (e.g. Twitter, Instagram etc.) pivoted during their entrepreneurial journey. However, there is a lack of empirical evidences on why and how software startups make pivots. Due to the nascent nature of the topic, the existing research and knowledge on the pivots of software startups are very limited. A better understanding is needed on different types of pivots, factors that trigger pivots, and the pivoting decision making process. Objective: The research activities undertaken during this PhD study have the aim to explore and better understand pivoting in software startups. Method: The key research methods are case study and case survey. Case study method is employed to identify the challenges that software startups face during their entrepreneurial journey contributing towards the importance of pivots for startups. The case survey method based on the secondary data is used to identify the different types of pivots and factors triggering pivots. Furthermore, the case study method is conducted to have a deeper contextual understanding of how software startups pivot, and is used to examine the pivoting decision-making processes in software startups. Results: The findings of this PhD study show that thriving in technology uncertainty, acquiring first paying customers, and building entrepreneurial team are among the identified challenges. Moreover, customer need, customer segment, product zoom-in and technology pivots are the major types of pivots software startups have made. In addition to this, several new pivot types are identified, including market zoom-in, market zoom-out, complete and side project pivots. Negative customer reaction and flawed business model are the prominent factors triggering pivots. During the pivoting decision-making process, software startups loosely follow the strategic decision-making process by implementing its phases implicitly. Moreover mainly the founders of startups make the pivot decisions. Conclusions: A pivoting framework integrating the aforementioned results for better understanding of pivot in software startups is a key contribution of the thesis. The framework incorporates several key aspects of startups primarily related to pivot including challenges startups face, the types of pivots and the triggering factors, and decision-making process on pivoting. The findings can be used as a theoretical lenses for longitudinal research in this area, and to assist and better understand the pivot decision-making process for startups. It can also be used as a foundation to develop a conceptual framework to further explore pivots in software startups. Meanwhile it provides practical knowledge to software startups, which they can utilize to guide their effective decisions on pivoting.