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

Q2 Environmental Science Environmental Challenges Pub Date : 2024-04-01 DOI:10.1016/j.envc.2024.100939
Madeleine Meyer , Lacy Barnette , Azadeh Mehrani , Louisa Schandera , Sarah Stone , Bo Cai , Paul Vecchiarelli , Jamie R. Lead
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Abstract

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.

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对客户群、价值主张以及环境科学技术商业化最低可行产品功能的适当性进行定量评估
将基础科学和应用科学转化为以证据为基础的实际应用具有挑战性,但也是必要的,尤其是在环境科学领域。本文介绍了一种定量数据分析方法,通过增强用于新技术采用的定性客户发现方法来支持决策。该方法可用于评估:i) 客户群(CS)和价值主张(VP)的有效性;ii) 新技术解决价值主张问题的能力。我们对两种不同的环境技术进行了评估,以展示这种定量方法。之前定性确定的 CS 和 VP 通过二项检验进行了统计(不)验证。在介绍的每个案例中,CS 都得到了统计验证,但每个案例的三个 VP 中只有一个得到了验证。通过线性优化,根据成本和性能数据对每种技术的验证性能参数进行了测试。通过测试,可以确定在哪些条件下该技术能满足客户的最低性能要求,在哪些条件下仍需要进一步的数据或技术改造。这些确定的条件确立了将技术过渡到商业化最低可行产品(MVP)阶段所需的功能。其中一项技术已准备好进行 MVP 开发,而另一项技术则需要更多数据和修改。这两项发现都证明了这种定量数据分析方法的有效性,并为技术商业化早期阶段的决策提供了指导。
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来源期刊
Environmental Challenges
Environmental Challenges Environmental Science-Environmental Engineering
CiteScore
8.00
自引率
0.00%
发文量
249
审稿时长
8 weeks
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