Analysing the role of business analytics adoption on effective entrepreneurship

Abstract

Business Analytics has emerged as an important area of study for researchers. It is mainly concerned with the extensive use of data, statistical and quantitative analysis, explanatory and predictive models, and fact-based management to stimulate decisions and actions. Business Analytics is believed to provide an edge to organizations since it helps offer opportune insights over the competition, helps optimize business processes, and helps drive growth and generate avenues for innovation. Traction related to big data and Business Analytics has increased tremendously in the last decade and a salient challenge for organizations is in understanding how to anchor them to create business value. As organizations launch into Business Analytics initiatives, many tactical questions, such as how to implement Business Analytics in order to generate the most value, come to light. The introduction of big data machine learning into analytics eventually unfolds opportunities for businesses to develop an approach for better decision making thereby resulting in effective entrepreneurship. The use of big data analytics enables the analysis of key influences of business, market dynamics and customer impact. However, very little scrutiny has been applied to understanding the theoretical and practical success factors concomitant to the operationalization of Business Analytics by entrepreneurs in their organizational setup. The objective of this research study is to fill that gap by empirically studying Business Analytics success factors and exploring the impact of Business Analytics on entrepreneurs and their organizations. Following a qualitative study, we attempt to obtain unplumbed insights into the consequences of Business Analytics and possibly shape theoretical and hands-on implementation of Business Analytics for entrepreneurs. Further, we offer a research model framework that captures major elements that not only traverse across industries, but also links these elements to what is most important to organizations: actionable insights that lead to increased performance, amplified competitive advantage, and preferable ethical and legal use of the data.