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

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dc.contributor.advisor Bandara, HMND Marikar, MS 2018 2018 2018
dc.description.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. en_US
dc.language.iso en en_US
dc.subject COMPUTER SCIENCE AND ENGINEERING – Dissertation en_US
dc.subject INFORMATION TECHNOLOGY – Dissertation en_US
dc.subject DECISION-MAKERS en_US
dc.subject DATA LITERACY en_US
dc.subject DATA ANALYTICS en_US
dc.subject COMMERCIAL BANK – Sri Lanka en_US
dc.title An Analysis of data-driven decision-making capabilities of managers in banks en_US
dc.type Thesis-Full-text en_US
dc.identifier.faculty Engineering en_US MBA in Information Technology en_US
dc.identifier.department Department of Computer Science & Engineering en_US 2018
dc.identifier.accno TH4321 en_US

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