DATA-DRIVEN DECISION-MAKING FRAMEWORK FOR ENHANCING BUSINESS AGILITY IN DIGITAL ENTERPRISES

P Raman; Karan Sukhija; Ms. Shivani Sahu; Deepak Saroha; Rajidi Rammohan  Reddy; G. Kharmega  Sundararaj

doi:10.29121/shodhkosh.v7.i11s.2026.8285

Authors

Dr.P.Raman Professor, Department Of Master of Business Administration, Panimalar Engineering College, Chennai, Tamil Nadu
Dr. Karan Sukhija Assistant Professor, SSET, JGND PSOU, Patiala, Punjab
Ms. Shivani Sahu Trainer a, MBA, Shri Ram Institute of Technology, Jabalpur (M.P), Jabalpur , Madhya Pradesh
Deepak Saroha Assistant Professor, School of Management Studies (SMS), College university CGC University, Mohali - 140307, Punjab, India
Dr. Rajidi Rammohan Reddy Associate Professor, Department Of Management Studies, Trinity College of Engineering and Technology, Peddapalli, Telangana
Dr. G. Kharmega Sundararaj Associate Professor, Department of Computer Science and Engineering,Dr. T. Thimmaiah Institute of Technology, Oorugaum, KGF, Karnataka ,INDIA - 563120

DOI:

https://doi.org/10.29121/shodhkosh.v7.i11s.2026.8285

Keywords:

Data-Driven Decision-Making, Business Agility, Digital Enterprises, Predictive Analytics, Organisational Transformation

Abstract [English]

The principle of data-driven decision-making (DDDM) has turned into one of the facilitators of the digital business environment that is characterised by a fast-changing environment. The paper offers a wide outline of the methods of making businesses more nimble by applying systematically integrated strategies with respect to data analytics, enterprise intelligence, and digital transformation. Recent literature readings, case studies and systematic review of the industry reports were conducted in order to identify the most important enabling factors, barriers and best practices in DDDM adoption. Based on the outcomes, the above-mentioned organizations whose data-driven processes were organized were 23 per cent more efficient in their work, and this is why the decision-making process was 17 per cent faster or more responsive to market changes. The framework stresses the fact that the leadership, agility of information system, knowledge management, and predictive analytics are important components that assist in optimizing the effectiveness of the decision-making processes. The insights provide an accurate blueprint to responsive businesses that are looking forward to utilizing data analytics to build nimbleness, novelty, and rivalry.

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