Enablers and Inhibitors of Leveraging Analytics for Digital Business Transformation

Digital Business Transformation is the process of improving corporate processes and business models by harnessing advanced technologies in order to become more efficient and competitive to meet the ever-changing needs of customers through innovative business models. The exponential rise of technologies such as cloud computing, the Internet of Things (IoT), 3D manufacturing, smart robots, robotic process automation, cloud computing, etc., is fundamentally changing the way organizations work, i.e. the business processes are becoming efficient, touchless, remote, data-driven and autonomous. All of the above mentioned technologies generate and utilize huge quantities of data. This data, when analyzed, can generate insights that can help organizations to become more competitive and develop innovative business models for delivering their products and services. The literature review reveals a need for additional research to understand the relationship between the enablers and inhibitors of leveraging analytics for 'digital business transformation'. To explore this topic further, fifteen enablers and ten inhibitors were shortlisted from the literature review. With the help of industry experts, Interpretive Structural Modeling (ISM) and Fuzzy Total Interpretive Structural Modeling (F-TISM) were used to establish the relationship and magnitude of impact between these enablers and inhibitors. It was seen that strategic enablers like 'C-suite/Board Involvement', 'Digital Strategy', 'Digital and analytical skills' have a higher driving power and consequently more influence on other factors as compared to technological enablers. Finally, a Confirmatory factor analysis (CFA) revealed the quantitative significance of each enabler and inhibitor. A case study was conducted to model and prioritize the transformation initiatives of a company using SAP-LAP Hills framework. Two more case studies were conducted to study the response of companies to enablers and inhibitors. The key contribution of this research is that it helps us to prioritize the key enablers that harness the power of analytics for 'digital business transformation' and makes us aware of the inhibitors. By doing this effectively, an organization can generate more insights, provide more inputs to senior management, and achieve its 'digital business transformation' goals more effectively. The study also provides recommendations for different stakeholders of the industry.