Solution-System Fit: The missing ingredient for lean innovation within complex systems

Omar Dabash and Kit Huckvale

No euy8z_v1, OSF Preprints from Center for Open Science

Abstract: We propose a novel, practical, and actionable framework to address the persistent challenges faced by startups operating in complex industries such as healthcare, energy, and security. These settings are characterised by intricate stakeholder dynamics, regulatory hurdles, and systemic constraints that traditional entrepreneurial frameworks often fail to address. We argue that, while Lean Startup Approaches (LSAs) emphasise Problem-Solution Fit (PSF) and Product-Market Fit (PMF), a missing complementary, yet critical, dimension is aligning innovations with the broader systems in which they operate. To bridge this gap, we introduce the concept of Solution-System Fit (SSF), which we define as the active identification and optimisation of alignments between an innovation and its complex system context. SSF emphasises early understanding of system behaviours, structures, actors, and constraints to mitigate risks of misalignment that limit solution adoption. SSF is operationalised through two phases: Systems-Flavoured Customer Discovery, and Systems-Flavoured Agile Development. The latter focuses on developing a System Viable Product (SVP) that accounts for technical, workflow, and systemic adoption requirements. By integrating systems thinking into LSAs, SSF seeks to increase the likelihood of sustainable innovation in complex environments. We propose that this approach offers both a practical framework for entrepreneurs and a lens for educators and investors to evaluate startup viability within complex systems contexts.

Date: 2025-02-09
New Economics Papers: this item is included in nep-ent
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Persistent link: https://EconPapers.repec.org/RePEc:osf:osfxxx:euy8z_v1

DOI: 10.31219/osf.io/euy8z_v1

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