Design Documentation Canvas: A Lightweight Design Rationale Framework for Solo Designers
DOI:
https://doi.org/10.59261/bustechno.v7i4.773Keywords:
Design Rationale, Design Documentation, Solo Designer, Knowledge Management, Multi-Brand Design, FSE FrameworkAbstract
Background: Design systems have become standard infrastructure in digital product development, yet they often underdocument the rationale behind design decisions. This gap is amplified in resource-constrained startups, where solo designers manage multi-brand, multiplatform products, increasing the risk of knowledge loss during handoffs and onboarding.
Objective: This study designs, implements, and evaluates the Design Documentation Canvas (DDC), a lightweight design rationale and traceability framework for solo designers in multi-brand startup contexts.
Methods: A single-case study was conducted at an Indonesian insurtech startup. Data were collected through two focus group discussion (FGD) sessions involving nine participants, one individual interview, a six-point Likert-scale questionnaire (n = 10), and artifact analysis, with the researcher acting as a participant-observer.
Results: The framework achieved 100% completeness across 17 qualifying design tickets, defined by substantively completed Description Panels (FSE-structured fields: Summary, Question/Issue, Final Decision, Evidence, and References) and Before-After Panels. Questionnaire results showed a median and mode of 6 across all items and 100% agreement-side responses, although these results should be interpreted with caution because of potential ceiling effects and social desirability bias. Cronbach’s alpha was 0.853. AI-assisted drafting also emerged during implementation as a means of reducing the perceived documentation articulation burden.
Conclusion: The DDC demonstrates operational feasibility and positive stakeholder reception within a single case, providing an adoptable documentation artifact for solo designers in Southeast Asian startup environments. The findings remain bounded by the single-case design and small sample and should not be interpreted as generalizable outcomes.
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