Exploring Hypothesis Generation Practices: Comparison of the Assumptions Mapping and HyMap Techniques
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Perustieteiden korkeakoulu |
Master's thesis
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Authors
Date
2023-12-11
Department
Major/Subject
Software and Service Engineering
Mcode
SCI3043
Degree programme
Master’s Programme in Computer, Communication and Information Sciences
Language
en
Pages
62+11
Series
Abstract
Entrepreneurs are key drivers of economic growth, yet face high failure rates due to overlooking customer needs research. To address this issue, continuous experimentation, which involves testing hypotheses to constantly refine understanding of customer needs, has gained prominence as an essential concept in both entrepreneurship and software engineering. However, the adoption of continuous experimentation principles remains limited among entrepreneurs due to a lack of clearly defined practices, particularly in the initial phase of hypothesis generation. Addressing this gap, the study focuses on comparing two hypothesis generation practices, the Assumptions Mapping method and the HyMap approach. This research adopts a task-based study approach, complemented by elements of case study, aiming to examine the efficiency and feasibility of the two techniques in the specific context of early-stage software startups. These startups are characterized by their age (1-3 years), size (around 20 employees), and domain (software products). The findings reveal that Assumptions Mapping emerges as a more efficient practice than the HyMap approach, placing emphasis on prioritizing crucial assumptions and promoting the creation of experiment-ready hypotheses. While the study did not conclusively determine a more feasible method between Assumptions Mapping and HyMap, the findings indicate that both practices typically require session durations exceeding 1.5 hours, hinting at the necessity for longer engagement times. Additionally, each method presents distinct challenges, which can potentially be addressed by more detailed guidelines or adapted modifications. Another key observation is the role of facilitators in both techniques; however, Assumptions Mapping inherently promotes collaborative dynamics within teams, in contrast to HyMap, which currently seems better suited for individual application. The research also sheds light on the significance of knowledge sharing and highlights the intricate challenges involved in experiment design within the startup context.Description
Supervisor
Fagerholm, FabianThesis advisor
Lehtela, BettinaKeywords
continuous software engineering, continuous experimentation, experimentation, hypothesis generation, hypothesis elicitation, ideas testing