A Progression Model of Software Engineering Goals, Challenges, and Practices in Start-Ups

Abstract

Context: Software start-ups are emerging as suppliers of innovation and software-intensive products. However, traditional software engineering practices are not evaluated in the context, nor adopted to goals and challenges of start-ups. As a result, there is insufficient support for software engineering in the start-up context. Objective: We aim to collect data related to engineering goals, challenges, and practices in start-up companies to ascertain trends and patterns characterizing engineering work in start-ups. Such data allows researchers to understand better how goals and challenges are related to practices. This understanding can then inform future studies aimed at designing solutions addressing those goals and challenges. Besides, these trends and patterns can be useful for practitioners to make more informed decisions in their engineering practice. Method: We use a case survey method to gather first-hand, in-depth experiences from a large sample of software start-ups. We use open coding and cross-case analysis to describe and identify patterns, and corroborate the findings with statistical analysis. Results: We analyze 84 start-up cases and identify 16 goals, 9 challenges, and 16 engineering practices that are common among startups. We have mapped these goals, challenges, and practices to start-up life-cycle stages (inception, stabilization, growth, and maturity). Thus, creating the progression model guiding software engineering efforts in start-ups. Conclusions: We conclude that start-ups to a large extent face the same challenges and use the same practices as established companies. However, the primary software engineering challenge in start-ups is to evolve multiple process areas at once, with a little margin for serious errors.

Service design as an innovation approach in technology startups: a longitudinal multiple case study

“…This indicates that the potential integration of service design as an innovation approach in technology startups may be realized differently with varying potential. Finally, the startup life cycle stage framework (Klotins et al, 2019) is used to categorize the “principles” and “toolbox” levels within startups' life cycle stages. This section is structured according to these three main findings.…”

“…The organizational context, operational challenges, development practices, and strategic vision were the focus in the pre‐project phase. Data analysis in this phase also enabled the categorization of startups according to the startup life cycle framework, since we did not use the framework for case selection purposes (Klotins et al, 2019). In the other two phases (during and post‐project), the focus was on activities, practices, and material evidence experienced and created during the project, and their assessment for innovation outcomes after the project finished.…”

“…Although all startups share similar innovation challenges at a broader level, research suggests that the stage of the startup's life cycle should not be disregarded where innovation is concerned. According to Klotins et al (2019), startups face specific challenges depending on the stage of their life cycle. The life cycle is divided into four stages; inception, where the aim is to build the initial version of the product; stabilization, with the aim of ensuring further development and preparing to scale; growth, with the aim of growing through the planned market share acquisition; and maturity, with the aim of starting a transition toward an established company.…”

“…Based on a rich set of data collected before, during, and after the service design projects, the study examines how service design facilitated the development of innovative value propositions, as well as how it was embedded in the innovation processes of the technology startups. The results reveal how value propositions are developed by following service design principles, point to two levels of service design embeddedness, and go on to contextualize these levels within the startups' life cycle stage framework (Klotins et al, 2019).…”

“…Startups also face specific challenges relative to their life cycle stage. Klotins et al (2019) define four life cycle stages for startups, which include inception, stabilization, growth, and maturity. Even though startups across different life cycle stages are managing their innovation activities under limited operational capability, varying actor involvement, and a restricted value focus, the technology they are developing does not always get the best customer response (Giardino, Wang, & Abrahamsson, 2014).…”