Evaluating Key Barriers and Drivers in Manufacturing Data Analytics: A Fuzzy DEMATEL-Based Strategic Map Approach

Özet

Purpose – This study aims to explore the strategic and operational challenges affecting the adoption of Manufacturing Data Analytics (MDA), defined as the systematic use of manufacturing data to support decision-making and performance improvement in industrial environments. Focusing on expert insights from manufacturing sectors in Türkiye, the study examines key technology management decisions such as resource allocation, technology selection, and organizational transformation and identifies the primary drivers and barriers influencing successful MDA implementation.
Design/methodology/approach – The study applies the Fuzzy DEMATEL (Decision-Making Trial and Evaluation Laboratory) method based on evaluations from 14 industry experts in Türkiye to identify and analyze the cause-and-effect relationships among critical drivers and barriers to MDA integration. This approach enables a systematic evaluation of how technological, managerial, and organizational factors interact during the adoption process.
Findings – The results reveal that high investment costs for data analysis and simulation (B4), lack of technical infrastructure in operational processes (B6), and insufficient top management support (B10) are the most significant barriers. Conversely, the primary drivers belong to the cause group and include problem identification (D1), operational efficiency improvement (D2), transparency (D3), observability (D4), coordination (D5), data management (D6), readiness of Industry 4.0 infrastructure (D9), prediction (D10), and agility (D13).
Discussion – The findings demonstrate that addressing cost, infrastructure, and leadership barriers particularly in the context of expert insights from Türkiye’s manufacturing sectors while strengthening analytical and organizational capabilities is essential for effective MDA adoption. The study contributes to technology and innovation management literature by providing practical insights for engineering managers to enhance digital transformation, improve operational performance, and achieve a sustainable competitive advantage.