Published on: April 2026
DATA-DRIVEN DECISION CULTURE AND ORGANIZATIONAL PERFORMANCE IN INFORMATION TECHNOLOGY ORGANIZATIONS: AN EMPIRICAL STUDY USING BUSINESS ANALYTICS
Prathamesh Ganesh Bartakke
Pro. Kanifnath S. Satav
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Abstract
In the business environment organizations are using data and analytical insights to guide their decisions. This is called data-driven decision-making. It means using data, analytics tools and evidence-based information to make decisions than just relying on intuition or experience. With the growth of digital technologies organizations now have a lot of data that can be analyzed to improve efficiency, productivity and competitiveness. The Information Technology industry plays a role in this transformation.
Many organizations are investing in business analytics tools and technologies. However they struggle to integrate data-driven practices into their decision-making processes. This study looks at the relationship between data-driven decision culture and organizational performance in IT organizations. We collected data from 50 respondents, including employees, team leaders, managers and HR professionals across IT organizations. We used a questionnaire with a 5-point scale to collect the data.
How to Cite this Paper
Bartakke, P. G. (2026). Data-Driven Decision Culture and Organizational Performance in Information Technology Organizations: An Empirical Study using Business Analytics. International Journal of Creative and Open Research in Engineering and Management, <i>02</i>(04). https://doi.org/10.55041/ijcope.v2i4.671
Bartakke, Prathamesh. "Data-Driven Decision Culture and Organizational Performance in Information Technology Organizations: An Empirical Study using Business Analytics." International Journal of Creative and Open Research in Engineering and Management, vol. 02, no. 04, 2026, pp. . doi:https://doi.org/10.55041/ijcope.v2i4.671.
Bartakke, Prathamesh. "Data-Driven Decision Culture and Organizational Performance in Information Technology Organizations: An Empirical Study using Business Analytics." International Journal of Creative and Open Research in Engineering and Management 02, no. 04 (2026). https://doi.org/https://doi.org/10.55041/ijcope.v2i4.671.
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- •Peer Review Type: Double-Blind Peer Review
- •Published on: Apr 24 2026
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