DIP: 18.02.031/20251003 
DOI: 10.25215/2455/1003031 
Abstract
In an era defined by rapid digitization and expanding data ecosystems, Data-Driven Decision Making (DDDM) has emerged as a critical competency across organizational hierarchies. While extensive research has explored the strategic impact of data at executive levels, the role of middle management—often the linchpin between strategy and execution—remains underexamined. This study investigates the adoption, application, and effectiveness of DDDM among middle managers across four key industries: healthcare, manufacturing, finance, and education. Utilizing a mixed-methods approach, the research combines survey data from 210 middle managers with in-depth interviews of 24 participants to evaluate data literacy, tool usage, cultural readiness, and organizational enablers/barriers to DDDM. The study introduces a DDDM Maturity Index to measure individual and institutional preparedness and effectiveness in applying data to operational and tactical decision-making.
Findings reveal significant industry-specific variations: while finance and manufacturing exhibit high tool adoption and confidence in analytics, healthcare and education face challenges related to data silos, regulatory constraints, and skill gaps. Across sectors, cultural resistance and lack of training emerge as common impediments to data-informed choices at the middle management level. Notably, organizations that embed data practices into day-to-day workflows and provide decentralized access to analytics tools see stronger alignment between managerial decisions and organizational goals.
The paper concludes with a framework for building DDDM capacity in middle management, emphasizing targeted upskilling, cross-functional collaboration, and leadership support. By illuminating the operational realities of middle-tier data use, this research contributes to both academic understanding and practical strategies for enhancing evidence-based decision-making across industries.
Keywords
- Data-Driven Decision Making (DDDM)
- Middle Management
- Cross-Industry Analysis
- Organizational Decision-Making
- Business Intelligence
- Data Literacy
- Analytics Adoption
- Evidence-Based Management
- Digital Transformation
- Operational Efficiency
- Managerial Effectiveness
- Data Culture
- Strategic Alignment
- Data Utilization
- Decision Support Systems
The author(s) appreciates all those who participated in the study and helped to facilitate the research process. 
The author(s) declared no conflict of interest. 
ISSN 2455-670X