Unlocking Digital Archive Efficiency: ERP Implementation in the Wooden Furniture Industry - Pratiwi, Mona Inayah; Rizqiana, Titi; Sulistiyani, Endang; Ramadhanti, Naya Yasinta; Chairunnisa, Dheanda Maurizta (RSF Conference Series: Business, Management and Social Sciences, 2025)
The rapid growth of digital technology has driven businesses to transition from manual processes to automated systems to improve efficiency and reduce human error. Archive management is one of the crucial administrative functions that require transformation, particularly in manufacturing and export companies. The Wooden furniture manufacturer and exporter in Jepara, still relied on physical archives, causing inefficiencies in document retrieval, lack of systematic classification, and absence of integrated backup systems. This study aims to analyze the company’s document management process and design a digital archiving system using the "Document" module in Odoo ERP to improve efficiency, accelerate information access, and minimize the risk of data loss. The research employed a qualitative descriptive method with a case study approach, involving interviews, direct observations, and document analysis to identify problems, design solutions, and test the system. To further ensure system efficiency and relevance, a GAP analysis using the NPF method was conducted to evaluate the alignment of the Odoo ERP "Document" module with the company’s current manufacturing and administrative processes. The developed digital archiving system features structured document classification, unique coding, keyword-based search, hierarchical access rights, encryption, and automated backups. Implementation results show a significant reduction in document retrieval time, improved storage accuracy, enhanced data security, and reduced physical storage needs. The system also facilitates audits, supports compliance, and provides a practical model for medium-sized companies managing large volumes of operational documents. Future research should explore cross-module integration and assess user acceptance to optimize the system’s potential.