An Analysis of Data Driven, Decision-Making Capabilities of Managers in Banks

TL;DR

This paper examines how bank managers in Sri Lanka utilize data analytics and BI tools for decision making, highlighting challenges like trust, knowledge, and visualization quality that affect data-driven decisions.

Contribution

It provides insights into the current state of data-driven decision making among bank managers and offers recommendations to improve adoption and effectiveness of BI tools.

Findings

Managers often rely on intuition over data due to uncertainty.

Visualization quality influences the reliance on data insights.

Trust and knowledge gaps hinder effective data-driven decisions.

Abstract

Organizations are adopting data analytics and Business Intelligence (BI) tools to gain insights from the past data, forecast future events, and to get timely and reliable information for decision making. While the tools are becoming mature, affordable, and more comfortable to use, it is also essential to understand whether the contemporary managers and leaders are ready for Data-Driven Decision Making (DDDM). We explore the extent the Decision Makers (DMs) utilize data and tools, as well as their ability to interpret various forms of outputs from tools and to apply those insights to gain competitive advantage. Our methodology was based on a qualitative survey, where we interviewed 12 DMs of six commercial banks in Sri Lanka at the branch, regional, and CTO, CIO, and Head of IT levels. We identified that on many occasions, DMs' intuition overrules the DDDM due to uncertainty, lack of trust, knowledge, and risk-taking. Moreover, it was identified that the quality of visualizations has a significant impact on the use of intuition by overruling DDDM. We further provide a set of recommendations on the adoption of BI tools and how to overcome the struggles faced while performing DDDM.