An Analysis of data-driven decision-making capabilities of managers in banks

Abstract

The vast volume of data generated by modern organizations could be used to gain a competitive advantage through the application of data analytics techniques. As such, many organizations are adopting data analytics and business intelligence tools with the aim of obtaining information more easily, gaining important insights, forecasting future events, and getting timely and reliable information to aid them in their decision making. While these tools are becoming mature, affordable, and easier to use, it is also important to understand whether the contemporary managers in these organizations are ready for Data-Driven Decision Making (DDDM). Therefore, it is imperative to understand to what extent the Decision Makers (DMs) are utilizing these data and tools, whether they can interpret the various forms of outputs from these tools, and gauge their ability to apply those insights to gain a competitive advantage. This study aims to answer these questions through a qualitative survey and a detailed analysis of several cases where such data analytics tools were used. This research uses Straussian’s grounded theory as the tool to analyze and build the theory for this investigation. The analysis focused on commercial banks in Sri Lanka and interviewed DMs at branch and regional levels, and the CTO, CIO, and Head of IT of six banks. It was identified that in many occasions, the DMs’ intuition overrules the DDDM due to uncertainty, lack of trust, knowledge, and the unwillingness towards risk-taking. It was also found that while experienced DMs prefer intuition-based decision-making, novice DMs are more adept at DDDM. Moreover, it was identified that quality of visualizations and presentations had a significant impact on the use of intuition by overruling DDDM. Subsequently, a set of recommendations are provided on the adoption of BI tools and on overcoming the struggles faced while performing DDDM.