Data-Driven Agile Leadership: The Impact of Business Intelligence Solutions on Transformation Outcomes

Authors

  • Vasudev Pendyala Southern Illinois University, USA Author
  • Shishir Biyyala University of Nebraska - Lincoln, USA Author
  • Sudheer Chennuri Texas A&M University, USA Author

DOI:

https://doi.org/10.32628/CSEIT241051086

Keywords:

Agile Transformation, Business Intelligence, Leadership Empowerment, Data-Driven Decision Making, Organizational Change

Abstract

This article examines the integration of Business Intelligence (BI) solutions in empowering leadership teams during Agile transformations within organizations. As businesses increasingly adopt Agile methodologies to enhance adaptability and efficiency, leaders face unique challenges in monitoring and steering these complex transformations. Through a multi-case study approach, we investigate how BI tools provide real-time insights into key performance indicators such as sprint velocity and team capacity, significantly enhancing leadership's ability to make informed decisions and identify bottlenecks in the Agile process. Our findings reveal that the implementation of BI solutions fosters a culture of transparency and accountability, enabling leaders to navigate the intricacies of Agile transformation more effectively. The article contributes to the growing body of literature on Agile leadership by highlighting the symbiotic relationship between data-driven decision-making and successful organizational change. We conclude that the strategic use of BI in Agile environments not only improves visibility into transformation progress but also enhances overall organizational performance in response to dynamic market demands.

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References

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Published

05-11-2024

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Section

Research Articles

How to Cite

[1]
Vasudev Pendyala, Shishir Biyyala, and Sudheer Chennuri, “Data-Driven Agile Leadership: The Impact of Business Intelligence Solutions on Transformation Outcomes”, Int. J. Sci. Res. Comput. Sci. Eng. Inf. Technol, vol. 10, no. 6, pp. 111–121, Nov. 2024, doi: 10.32628/CSEIT241051086.

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