In our last article we discussed the importance of having entrepreneurial traits and self-efficacy in order to successfully commercialise your research results. Having made a self-assessment of one’s deficiencies and strengths in this respect, it is then important to start the search process, that is the process of identifying a viable and scalable business model. 

While it is important to identify a direction and make a decision with regard to the business model to be taken when commercialising research results, it is equally important to remain flexible and adaptable to the highest degree possible. A component of this flexibility is to hold off on making decisions in the absence of sufficient information, and not jump the gun by investing substantial amounts of money and time early on into resources or aspects of the business that may prove not to be useful as time goes by. In undertaking the search process it is therefore important to structure one’s thoughts and to create a framework in which these decisions can be made, a framework that takes into account the differences between more standard approaches to problem solving as well as those that may work better for a start-up. 

If you were to take an infrastructure project as an example of a problem solving exercise you might reach certain conclusions about the best approach. A rational analysis of the situation might be called for which would set out a static and linear development to how the project would proceed, laying out multiple options which can be predicted. The natural focus would be on predicting the future rather than controlling it. This would be reflected in elements such as predicting the use and load of the infrastructure in question, predicting the short and long term impact of choosing certain materials over others and taking an approach to risk that is centred on the expected returns for the project by predicting revenue streams. 

When thinking about the principles of running a startup, the thought process can be diametrically opposed. Given that startups typically have limited resources and tools, a business model or plan must not only be commercially viable and scalable but must also take a realistic point of departure for that startup in question. Therefore weight must be given to the resources and tools available as well as the entrepreneur’s traits. The development of the start-up cannot be static and linear. given the inherent uncertainty of the exercise and the fact that the start-up may be operating in an emergent market, and must therefore be dynamic and non-linear. Furthermore, given this uncertainty, it will be impossible to predict the future and the entrepreneur must therefore focus on controlling the future instead. This means that you will need to identify the manner in which you can retain control of the company’s situation regardless of shifting developments and find ways in which to manufacture the ideal circumstances to benefit your start-up’s success. Part of this calculation is to focus on affordable losses, a concept which goes hand in hand with the aforementioned need to minimise the time and money invested into areas of the business that may not bear fruit. It is needless to say that taking this approach to charting the course for your start-up requires a tolerance for ambiguity. This tolerance for ambiguity can be defined as the tendency to perceive ambiguous situations as desirable rather than threatening, and is strongly linked to the “risk-taking” personal trait as discussed in our last article. 

A good place to start with the search process is the value proposition, a concept we considered in detail in an earlier article on this topic. Using a value proposition canvas can help entrepreneurs determine the user’s top priority and structure the business around this point. Taking the user’s top priority as paramount, one can then work on providing evidence to justify the product or service, determine the main feature of the technology and what customers value in the product as well as how enthusiastic they are. Having taken this approach, the business must focus on producing its minimum viable product (MVP). The MVP should include just enough features to allow useful feedback from early adopters which in turn will increase the speed to market with customer-driven product versions, reduce the likelihood of wasting time on useless features and maximise the learning per euro spend. Through a series of MVPs a startup can validate a specific and comprehensive set of hypotheses which will be the foundation of the product’s viability.