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Entrepreneurial software engineering: towards a hybrid development method for early-stage startups
(2021)
A considerable share of innovative software-intensive products is developed by startups. However, product development in an early-stage startup is not a sequential process. A business idea is usually based on a number of assumptions. The riskiest assumptions need to be tested. Depending on the test results, a product strategy may change several times. This raises the question of how to create sufficiently stable software using engineering principles despite a dynamic product strategy that is subject to many uncertainties. Hybrid development methods that combine agile aspects with classical engineering methods seem to be a good choice in such a start-up context. This paper proposes a lightweight hybrid development method that provides early-stage startups with a framework to support the development of single-feature minimum viable products. The method was derived from a start-up company's founding case and evaluated in expert interviews. The proposed method is intended to provide a basis for discussion between practitioners and scientists with the aim of better understanding the application of software engineering principles in software start-ups.
Selecting a suitable development method for a specific project context is one of the most challenging activities in process design. To extend the so far statistical construction of hybrid development methods, we analyze 829 data points to investigate which context factors influence the choice of methods or practices. Using exploratory factor analysis, we derive five base clusters consisting of up to 10 methods. Logistic regression analysis then reveals which context factors have an influence on the integration of methods from these clusters in the development process. Our results indicate that only a few context factors including project/product size and target application domain significantly influence the choice. This summary refers to the paper “Determining Context Factors for Hybrid Development Methods with Trained Models”. This paper was published in the proceedings of the International Conference on Software and System Process in 2020.
Context: Agile practices as well as UX methods are nowadays well-known and often adopted to develop complex software and products more efficiently and effectively. However, in the so called VUCA environment, which many companies are confronted with, the sole use of UX research is not sufficient to find the best solutions for customers. The implementation of Design Thinking can support this process. But many companies and their product owners don’t know how much resources they should spend for conducting Design Thinking.
Objective: This paper aims at suggesting a supportive tool, the “Discovery Effort Worthiness (DEW) Index”, for product owners and agile teams to determine a suitable amount of effort that should be spent for Design Thinking activities.
Method: A case study was conducted for the development of the DEW index. Design Thinking was introduced into the regular development cycle of an industry Scrum team. With the support of UX and Design Thinking experts, a formula was developed to determine the appropriate effort for Design Thinking.
Results: The developed “Discovery Effort Worthiness Index” provides an easy-to-use tool for companies and their product owners to determine how much effort they should spend on Design Thinking methods to discover and validate requirements. A company can map the corresponding Design Thinking methods to the results of the DEW Index calculation, and product owners can select the appropriate measures from this mapping. Therefore, they can optimize the effort spent for discovery and validation.