Challenges in Data Driven Decision Making in the Early Stages of a Startup

Abstract

Abstract Entrepreneurship is usually considered as a chaotic process paved with uncertainties. Without a method to the madness, entrepreneurship can become detrimental to the well-being of the entrepreneur. Early stage of a start-up refers to all important activities that help identify a potential business from an idea. This discovery process is characterised by stress and uncertainty which makes data driven decision making particularly challenging. Unlike mature phases (post launch and product-market fit phase) where data is available in plenty, early phase decision making depends on either limited data or generating one’s own data. Uncertainty gives rise to biases in the decision making. The two most negatively impacting biases are confirmation bias and self-serving bias. In a combination, they affect the way an entrepreneur in the early phase interprets both data and the consequences of his/her decision. Through a qualitative interview-based study involving 30 entrepreneurs in the early phase and 10 entrepreneurs in the mature stage, this study focuses on recognising the presence of these biases and proposes a habit-based process for grooming early-stage entrepreneurs. The scientific principles underlying the proposed framework have been detailed out and pragmatic solutions for improving early phase decision making have been derived.