Quantitative assessment of customer segment, value proposition and appropriateness of minimum viable product features for technology commercialization in the environmental sciences

Transitioning fundamental and applied science to evidence-based real-world applications is challenging yet necessary, especially in environmental sciences. In this paper, a quantitative data analysis method is presented to support decision-making by augmenting qualitative customer discover methods used for new technology adoption. This method can be used to assess: i) customer segment (CS) and value proposition (VP) validity and ii) the ability of a new technology to address the VP. Two different environmental technologies were evaluated to demonstrate this quantitative approach. CS and VP(s) that were previously qualitatively identified were statistically (in)validated using binomial testing. In each of the presented cases, the CS was statistically validated but only one of the three VPs for each case was validated. The validated performance parameters for each technologywere tested against cost and performance data using linear optimization. This testing allowed for the identification of conditions under which the technology met minimum customer performance requirements and where further data or technology modifications were still needed. These identified conditions establish the features necessary to transition the technologies to the minimum viable product (MVP) phase of commercialization. One technology was found to be ready for MVP development while the other technology needed additional data and modification. Both findings demonstrate the effectiveness of this quantitative data analysis method and guide decision-making in the early stages of technology commercialization.