Analysis of Efficiency and Productivity Using Data Envelopment Analysis Method to Improve Operational Performance in Local Manufacturing Industry

Abstract

The local manufacturing industry plays a crucial role in Indonesia’s economic development, yet faces increasing pressure from globalization, supply chain disruptions, and technological transformation. Amid these challenges, improving operational efficiency and productivity has become imperative. This study aims to analyze the efficiency and productivity levels of manufacturing firms using the Data Envelopment Analysis (DEA) method. DEA is a non-parametric technique that assesses the relative efficiency of decision-making units (DMUs) by comparing inputs (e.g., labor, capital, energy) and outputs (e.g., production, revenue). Using a qualitative approach based on a systematic literature review (SLR), this research synthesizes data from ten academic studies published between 2019 and 2025. Thematic content analysis revealed that DEA is highly effective in identifying efficiency gaps among manufacturing firms, especially small and medium enterprises (SMEs). Studies also emphasized the usefulness of the Malmquist Productivity Index in tracking productivity changes over time. Key findings show that firms integrating digital tools, adopting automation, and investing in workforce development achieve higher efficiency scores. Conversely, those with limited innovation and poor resource management often perform below optimal levels. Additionally, benchmarking through DEA allows underperforming firms to model strategies from more efficient peers. This study concludes that DEA provides actionable insights for enhancing operational performance in local manufacturing. It supports data-driven decision-making, promotes continuous improvement, and helps firms align resource utilization with productivity goals in the digital era.