The SECURE framework for evaluating startup ventures is intended to provide potential investors with an actionable tool for assessing investment quality. The SECURE framework enables investors to evaluate startups on all functional domains and provides conclusive results that aid investment decision-making. The SECURE framework would also assist policymakers in assessing startup business models and be well-equipped to guide entrepreneurs based on the recommendations. Finally, entrepreneurs can self-assess their business plans or even their existing ventures and gain confidence and guidance on areas of improvement.

Educators can assess business ideas and business plans using the SECURE framework. Researchers and educators will have the chance to reflect on several value-creating ex-ante measures and their resultant impact on ex-post value-capturing ex-post performance measures, which are theoretically anchored and supported by empirical evidence. SECURE is also beneficial for entrepreneurial education in general as it enables educators to guide students and assist in assessing business plans and feasibility studies.

Although several evaluation criteria and measures were included in the SECURE framework, not all possible steps could be retained for clarity and simplicity. Therefore, the SECURE framework is primarily targeted toward beginners and new entrepreneurs. It is a basic assessment of business models by educators and an additional tool to aid decision-making for investors. Considering the merits of weighted averages and summation of scores, the SECURE framework aggregates the scores so that the scale can be conclusive and aid decision-making. Therefore, the values of weighted average scoring cannot be applied to the SECURE framework. In addition, the SECURE framework is unsuitable for comprehensively evaluating not-for-profit ventures, so social and environmental impacts are not measured. Finally, the SECURE framework remains a quantitative measure despite some qualitative assessments. Therefore, its ability to interpret responses in depth remains limited.