Revolutionizing Manufacturing Decision-Making with Data-Driven Insights: A Case Study Approach
Sulartopo, Miftahurrohman, Agus Wibowo
Volume 12, Issue 5 2024
Abstract:
Information is pivotal in decision-making across various sectors, including the manufacturing
industry. A robust framework is required to amalgamate information from diverse sources, conduct thorough
analyses, and provide actionable insights to support an effective decision process. This study proposes a
comprehensive information-driven decision process (DD-DM) framework tailored for the manufacturing industry
within the context of Industry 4.0. Employing a case study methodology focused on a small and medium-sized
enterprise (SME) within the electronics manufacturing sector, we identify and address the multifaceted challenges
associated with implementing DD-DM. The study integrates qualitative and quantitative information collection
methods, including interviews, observations, and information analysis from various manufacturing processes. The
findings reveal that implementing the DD-DM framework significantly enhances decision process efficiency,
improves product quality, and increases responsiveness to market changes. Four critical factors essential for the
successful adoption of DD-DM are ensuring information quality, integrating advanced technologies, optimizing
operational processes, and addressing human factors. This research contributes valuable insights for managers,
engineers, and employees in the manufacturing industry by offering a practical and theoretical framework for
transitioning to an information-driven decision process. By facilitating the integration of Industry 4.0 technologies,
the proposed framework enables manufacturing companies to achieve higher levels of operational efficiency and
competitive advantage in a rapidly evolving market environment.
