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Comparative analysis of outsourcing and in house warehouse management system to improve productivity and stock accuracy

Untung Alamsah (1), Anang Muftiadi (2), ⁠Ria Arifianti (3),
(1) Universitas Padjadjaran  Indonesia
(2) Universitas Padjadjaran  Indonesia
(3) Universitas Padjadjaran  Indonesia

Corresponding Author


DOI : https://doi.org/10.29210/020244964

Full Text:    Language : en

Abstract


This study compares the impact of outsourced and in-house Warehouse Management Systems (WMS) on productivity and stock accuracy in the fast-moving consumer goods (FMCG) sector. Data was collected from a logistics services company in Palembang using quantitative methods, including measurements of productivity per person per hour and stock accuracy per SKU. Productivity was assessed based on items processed per unit time, while stock accuracy compared physical stock with system records. Additional data was gathered through a Google Form survey targeting operational staff and warehouse managers to understand the implementation of both WMS models. The survey covered critical processes such as putaway, picking, and inventory, providing insights into operational efficiency and challenges associated with each model. Dummy variable multiple regression was applied to evaluate the performance impact of each WMS model, supplemented by qualitative insights from structured interviews. Findings reveal that WMS in-house is better than outsourcing WMS. While 12.5% of respondents rated the outsourced WMS as inefficient, none reported inefficiencies in the in-house system. Additionally, 62.5% of respondents found the in-house WMS highly effective, citing smoother implementation and higher reliability. The in-house WMS also demonstrated superior operational efficiency, storage accuracy, and responsiveness. It provided better storage location guidance (33.3%) and faster, more accurate operator navigation (26.5%) compared to the outsourced system. Moreover, only 33.3% of respondents noted delays in resolving technical issues with the in-house system, versus 68.8% for the outsourced system. Statistical analysis further supported these findings, showing significant advantages for the in-house WMS in productivity (p=0.068) and stock accuracy (p=0.000). These results highlight the strategic advantages of adopting an in-house WMS, underscoring its role in enhancing operational efficiency and maintaining competitiveness in the dynamic FMCG market.

Keywords


Warehouse, Management System, Stok Akurasi

References


Abdul Rahman, N. S. F., Karim, N. H., Md Hanafiah, R., Abdul Hamid, S., & Mohammed, A. (2023). Decision analysis of warehouse productivity performance indicators to enhance logistics operational efficiency. International Journal of Productivity and Performance Management, 72(4), 962–985.

Ali Syed, D., & Siddiqui, D. A. (2019). Impact of outsourcing and other factors on logistics performance in FMCG sector of Pakistan. Danish Ali Syed and Dr. Danish Ahmed Siddiqui, 9386–9390.

Amini, M., & Jahanbakhsh Javid, N. (2023). A multi-perspective framework established on diffusion of innovation (DOI) theory and technology, organization and environment (TOE) framework toward supply chain management system based on cloud computing technology for small and medium enterprises. Organization and Environment (TOE) Framework Toward Supply Chain Management System Based on Cloud Computing Technology for Small and Medium Enterprises (January 2023). International Journal of Information Technology and Innovation Adoption, 11, 1217–1234.

Andiyappillai, N. (2020). Digital transformation in warehouse management systems (WMS) implementations. International Journal of Computer Applications, 177(45), 34–37.

Attaran, M. (2020). Digital technology enablers and their implications for supply chain management. Supply Chain Forum: An International Journal, 21(3), 158–172.

Avci, Ö. (2019). A study to examine the importance of forecast accuracy to supply chain performance: A case study at a company from the FMCG industry. University of Twente.

Baruffaldi, G., Accorsi, R., & Manzini, R. (2019). Warehouse management system customization and information availability in 3pl companies: A decision-support tool. Industrial Management & Data Systems, 119(2), 251–273.

Buzu, A. (2021). The effect of Warehousing management on Warehouse performance. Available at SSRN 3951785.

Changarampat, P. P. (2022). The importance of warehouse management systems in the success of supply chain systems.

Chauhan, P. (2023). Analysis and management of logistics distribution performance in the FMCG sector. College of Management and Economic Studies, UPES, Dehradun.

Custodio, L., & Machado, R. (2020). Flexible automated warehouse: a literature review and an innovative framework. The International Journal of Advanced Manufacturing Technology, 106, 533–558.

Deepali, C., Monika, P., & Dharmendra, S. (2024). Integrating barcode technology into warehouse management systems for enhanced efficiency and inventory accuracy. Journal of Computer Science and Research (JoCoSiR), 2(1), 8–14.

Deptova, D. (2024). Outsourcing of Warehouse Operations.

Dinçer, K. F., & Turgay, S. (2023). Balancing Demand and Supply: Inventory Allocation in FMCG. Industrial Engineering and Innovation Management, 6(10), 41–49.

Halawa, F., Dauod, H., Lee, I. G., Li, Y., Yoon, S. W., & Chung, S. H. (2020). Introduction of a real time location system to enhance the warehouse safety and operational efficiency. International Journal of Production Economics, 224, 107541.

Istiqomah, N. A., Sansabilla, P. F., Himawan, D., & Rifni, M. (2020). The implementation of barcode on warehouse management system for warehouse efficiency. Journal of Physics: Conference Series, 1573(1), 12038.

Kmiecik, M. (2024). Stock management in e-commerce by 3PL – case study. Scientific Papers of Silesian University of Technology Organization and Management Series, 192(2024). https://doi.org/10.29119/1641-3466.2024.192.34

Koponen, R. (2023). The warehouse outsourcing review and analysis at Actiw Oy.

Liang, K., Zhou, L., Yang, J., Liu, H., Li, Y., Jing, F., Shan, M., & Yang, J. (2023). Research on a dynamic task update assignment strategy based on a “parts to picker” picking system. Mathematics, 11(7), 1684.

Madamidola, O. A., Daramola, O. A., Akintola, K. G., & Adeboje, O. T. (2024). A review of existing inventory management systems. International Journal of Research in Engineering and Science (IJRES), 12(9), 40–50.

Maheshwari, P., Kamble, S., Kumar, S., Belhadi, A., & Gupta, S. (2023). Digital twin-based warehouse management system: a theoretical toolbox for future research and applications. The International Journal of Logistics Management, ahead-of-print.

Malema, M. B. (2019). Factors Impacting the Efficiency of the Distribution of Finished Goods to Multiple Customers at a Fast-moving Consumer Goods Company. University of the Witwatersrand, Faculty of Engineering and the Built ….

Marzouk, E., Abdelhady, N., & Kaoud, M. (2022). The Effect of DRP Automation on Supply Chain Management in the Egyptian FMCG Industry. https://www.researchgate.net/profile/Menatalla-Kaoud/publication/371018087_The_Effect_of_DRP_Automation_on_Supply_Chain_Management_in_the_Egyptian_FMCG_Industry/links/6479b876b3dfd73b775da35c/The-Effect-of-DRP-Automation-on-Supply-Chain-Management-in-the-Egyptian-FMCG-Industry.pdf

Minashkina, D., & Happonen, A. (2020). Systematic literature review and research gap issues on third party logistics operators selecting WMS for efficient operations for customers. International Journal of Supply Chain and Inventory Management, 3(2), 142–166.

Muller, M. (2019). Essentials of inventory management. HarperCollins Leadership.

Odeyinka, O. F., & Omoegun, O. G. (2023). Warehouse Operations: An Examination of Traditional and Automated Approaches in Supply Chain Management.

Ogbeyemi, A., Ogbeyemi, A., & Zhang, W. (2024). Integrating human factors into the distribution model of goods and fast-moving consumer goods for effective inventory control. International Journal of Engineering Business Management, 16, 18479790241266350.

Ozden, S. G., Smith, A. E., & Gue, K. R. (2021). A computational software system to design order picking warehouses. Computers & Operations Research, 132, 105311.

Richards, G. (2021). Warehouse management: The definitive guide to improving efficiency and minimizing costs in the modern warehouse. Kogan Page Publishers.

Ruthramathi, R., & Sivakumar, V. (2023). Digital Technology Advancement And Innovations In Warehouse Operations.

Shanmugamani, K., & Mohamad, F. (2023). The implementation of warehouse management system (wms) to improve warehouse performance in business to business (B2B). International Journal of Industrial Management, 17(4), 231–239.

Shetty, N., Sah, B., & Chung, S. H. (2020). Route optimization for warehouse order picking operations via vehicle routing and simulation. SN Applied Sciences, 2, 1–18.

Shivam, & Gupta, M. (2024). Inventory and warehouse management in industry 4.0: a BPR perspective. Journal of Information Technology Case and Application Research, 1–36.

Tien, N. H., Anh, D. B. H., & Thuc, T. D. (2019). Global supply chain and logistics management. Academic Publications, Dehli.

Vatumalae, V., Rajagopal, P., & Sundram, V. P. K. (2020). Warehouse management system of a third party logistics provider in Malaysia. International Journal of Economics and Finance, 12(9), 73.


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