Start-up entrepreneur human virtual intelligence decision-making transformation model

Abstract

Start-up entrepreneurs (SE) have to make fast and quality business decisions in multiple contexts, despite resource limitations and a chaotic environment. Many start-up ventures fail at an early stage due to poor entrepreneurial decision-making that lacked practical business knowledge, skills, and experience. Unlike Chief Operating Officers of large and mature organizations, who make important decisions collectively, a SE has to make decisions on his own. However, his decision-making could be improved significantly if he is able to consult a virtual network of advisors, mentors, business partners, crowd and relevant parties through social network media supported by Information and Communication Technology that is termed as Human Virtual Intelligence (HVI). The main issue is how can an ad-hoc decision-making SE be transformed into a consultative decision-maker who can make effective business decisions in multiple contexts? To find out, an in-depth study on SE decision-making practices was conducted to determine their decision-making lifestyle. The study employed mixed methods including crowdsourcing, psychometric profiling and a lifestyle field study. All the results were summed up as a SE decision-making lifestyle mind map. Using Checkland’s Soft System Methodology and Snowden’s Cynefin Framework, a transformation model was developed. The Mind Map was converted into a Rich Picture consists of the relationship among the participating stakeholders. A Root Definition was formulated and it then assisted the CATWOE analysis to finally derive the activity model. To validate this model, Action Research was conducted on members of the Indonesian Young Entrepreneurs Association. In the validation, a pre-test comprising of questions on business decisions was used to determine the SE decision-making competency. From the test, the worst performers were selected as candidate for transformation. An HVI awareness program consisted of focus group workshop, coaching clinic and group assignment was developed and then provided to the candidates for them to quickly learn how to utilize HVI to make effective business decisions. After finishing the program, a post-test was conducted to determine if the candidate’s business decision-making has improved. A control test on unintervened sample was also conducted to confirm the improvement made by the model. From the study, it was found that more than 80% SE made effective decisions in multiple contexts, confirming that the HVI decision-making transformation model can improve SE business decision-making practices. The findings contribute to the field of Knowledge Management by assisting SE to make better business decisions through consulting knowledge agents in a HVI network.