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Managing Data-Driven Decision-Making: Managerial Practices : A Qualitative Multiple Case Study about Managerial Practices when Utilizing Data-Driven Decisions

Background: The rapid digitalization of business operations has transformed the decision-making process, with companies increasingly relying on Data-Driven Decision-Making (DDDM) to navigate complex business environments. However, the utilization of DDDM is not without challenges, as organizations face obstacles such as data integration issues and a lack of technical skills among managers. This study explores the integration of DDDM into organizational strategies, focusing on the experience of managers as they navigate the transition toward data-driven approaches. Problem: While the benefits of DDDM, such as enhanced operational efficiency and competitive advantage are well-documented, there is a notable gap in understanding how managers' practices and the decision-making process are integrated. Research Purpose: The purpose of the research is to examine how DDDM influences managerial practices in the decision-making process and identify the key challenges and opportunities. By examining experiences, the study aims to uncover insights that can guide organizations in refining their decision-making process and fostering data-driven approaches. Research Question: How does DDDM influence managerial practices and the decision-making process within an organization? Method: This study employs a qualitative research methodology, utilizing semi-structured interviews to gather insights from managers across various industries. It adopts a relativistic ontological stance and epistemological constructionism through a multiple case study to examine managerial practices when utilizing DDDM. Conclusion: The findings show that DDDM can significantly impact organizational efficiency, productivity, and strategic planning. However, successful DDDM requires a balance between data-driven insights and intuitive decision-making. While data can inform decisions, managers must also rely on intuition and experience, especially in complex scenarios with incomplete data.

Identiferoai:union.ndltd.org:UPSALLA1/oai:DiVA.org:hj-64371
Date January 2024
CreatorsÖstlund, Maja, Gustafsson, Ellen
PublisherJönköping University, Internationella Handelshögskolan
Source SetsDiVA Archive at Upsalla University
LanguageEnglish
Detected LanguageEnglish
TypeStudent thesis, info:eu-repo/semantics/bachelorThesis, text
Formatapplication/pdf
Rightsinfo:eu-repo/semantics/openAccess

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