Main Article Content
Abstract
Purpose: This study evaluates the adequacy of public data for applying Economic Order Quantity (EOQ), Safety Stock (SS), and Reorder Point (ROP) to PT Mayora Indah Tbk’s inventory for the 2024–2025 period.
Research Method: This study employs a descriptive quantitative approach with a documentary design. The data were drawn from consolidated financial statements and sustainability reports, and were then evaluated based on physical data requirements, relevant costs, demand, and lead time.
Results and Discussion: The public report provides only aggregate inventory values and does not disclose quantities, ordering costs, storage costs, or lead times for each material. The insurance coverage amount is not the annual premium, and data do not support the ordering frequency and previous SS parameters. Therefore, the estimates for EOQ, ROP, cost savings, and margin improvement cannot be validated.
Implications: Applying the model requires transaction data at the homogeneous material level, including physical usage, incremental costs, order history, lead times, and service targets. The research findings serve as the basis for improving inventory data management and for subsequent implementation studies.
Originality: This study highlights the methodological limitations of using consolidated financial statements to make operational EOQ decisions at large-scale FMCG companies.
Keywords
Article Details

This work is licensed under a Creative Commons Attribution 4.0 International License.
References
- Afiah, N. (2025). Analisis Pengelolaan Persediaan Bahan Baku Dengan Menggunakan Metode EOQ Pada Lewa Bakery. Bongaya Journal of Research in Accounting (BJRA), 8(2), 103–111. https://doi.org/10.37888/bjra.v8i2.714
- Ahakonye, L. A. C., Zainudin, A., Shanto, M. J. A., Lee, J.-M., Kim, D.-S., & Jun, T. (2024). A multi-MLP prediction for inventory management in manufacturing execution system. Internet of Things, 26, 101156. https://doi.org/https://doi.org/10.1016/j.iot.2024.101156
- Alam, M. K., Thakur, O. A., & Islam, F. T. (2023). Inventory management systems of small and medium enterprises in Bangladesh. Rajagiri Management Journal, 18(1), 8–19. https://doi.org/10.1108/RAMJ-09-2022-0145
- Arief, M., & Adi, T. W. (2024). Optimalisasi pengendalian persediaan pertamax pada fuel terminal X menggunakan metode Economic Order Quantity. Prosiding Seminar Nasional Teknologi Energi Dan Mineral, 4(1), 481–491. https://doi.org/10.53026/prosidingsntem.v4i1.180
- Arifani, A. (2023). Relationship between Working Capital Elements and Company Profitability. Advances: Jurnal Ekonomi & Bisnis, 1(2), 124–130. https://doi.org/10.60079/ajeb.v1i2.73
- Balkhi, B., Alshahrani, A., & Khan, A. (2022). Just-in-time approach in healthcare inventory management: Does it really work? Saudi Pharmaceutical Journal, 30(12), 1830–1835. https://doi.org/https://doi.org/10.1016/j.jsps.2022.10.013
- Berling, P., & Sonntag, D. R. (2022). Inventory control in production–inventory systems with random yield and rework: The unit‐tracking approach. Production and Operations Management, 31(6), 2628–2645. https://doi.org/10.1111/poms.13706
- Bucarey, V., Calderón, S., Muñoz, G., & Semet, F. (2024). Decision-Focused Predictions via Pessimistic Bilevel Optimization: A Computational Study BT - Integration of Constraint Programming, Artificial Intelligence, and Operations Research (B. Dilkina (ed.); pp. 127–135). Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-60597-0_9
- Chakir, A., Andry, J. F., Ullah, A., Bansal, R., & Ghazouani, M. (2024). Engineering applications of artificial intelligence. Springer Nature.
- Essila, J. C. (2022). Strategies for reducing healthcare supply chain inventory costs. Benchmarking: An International Journal, 30(8), 2655–2669. https://doi.org/10.1108/BIJ-11-2021-0680
- Feng, Y., Abdus, S., Tuo, G., & Chen, S. (2022). Raw materials and production control with random supply and demand, an outside market and production capacity. Operations Research Letters, 50(6), 679–684. https://doi.org/https://doi.org/10.1016/j.orl.2022.10.008
- Guo, Y., Liu, F., Song, J.-S., & Wang, S. (2025). Supply chain resilience: A review from the inventory management perspective. Fundamental Research, 5(2), 450–463. https://doi.org/https://doi.org/10.1016/j.fmre.2024.08.002
- Hammler, P., Riesterer, N., Mu, G., & Braun, T. (2023). Multi-Echelon Inventory Optimization Using Deep Reinforcement Learning BT - Quantitative Models in Life Science Business: From Value Creation to Business Processes (J. K. Canci, P. Mekler, & G. Mu (eds.); pp. 73–93). Springer International Publishing. https://doi.org/10.1007/978-3-031-11814-2_5
- Huo, B., Li, D., & Gu, M. (2024). The impact of supply chain resilience on customer satisfaction and financial performance: A combination of contingency and configuration approaches. Journal of Management Science and Engineering, 9(1), 38–52. https://doi.org/https://doi.org/10.1016/j.jmse.2023.10.002
- Huynh, N., & Le, Q. N. (2025). From chain to capital: Supply chain risks and working capital management. Economics Letters, 247, 112100. https://doi.org/https://doi.org/10.1016/j.econlet.2024.112100
- Jaber, M. Y., & Peltokorpi, J. (2024). Economic order/production quantity (EOQ/EPQ) models with product recovery: A review of mathematical modeling (1967–2022). Applied Mathematical Modelling, 129, 655–672. https://doi.org/https://doi.org/10.1016/j.apm.2024.02.022
- Jadidi, O., Firouzi, F., & Sorooshian, S. (2025). A closed-form solution approach for optimal reorder point in economic order quantity models with uncertain demands. Decision Analytics Journal, 16, 100622. https://doi.org/https://doi.org/10.1016/j.dajour.2025.100622
- Khakbaz, A., Alfares, H. K., Amirteimoori, A., & Tirkolaee, E. B. (2024). A novel cross-docking EOQ-based model to optimize a multi-item multi-supplier multi-retailer inventory management system. Annals of Operations Research. https://doi.org/10.1007/s10479-023-05790-9
- Mallick, R. K., Patra, K., & Mondal, S. K. (2023). A new economic order quantity model for deteriorated items under the joint effects of stock dependent demand and inflation. Decision Analytics Journal, 8, 100288. https://doi.org/https://doi.org/10.1016/j.dajour.2023.100288
- Milewski, D., & Wiśniewski, T. (2022). Regression analysis as an alternative method of determining the Economic Order Quantity and Reorder Point. Heliyon, 8(9). https://doi.org/10.1016/j.heliyon.2022.e10643
- Öztürk, H., & Konstantaras, I. (2025). EOQ model with defective products, batch shipment and partial backorders. Annals of Operations Research, 351(3), 1941–1988. https://doi.org/10.1007/s10479-025-06669-7
- Palanivel, M., Venkadesh, M., Vetriselvi, S., & Suganya, M. (2025). An analytics-driven economic order quantity model integrating fuzzy learning for deteriorating imperfect items in sustainable supply chains. Supply Chain Analytics, 10, 100120. https://doi.org/https://doi.org/10.1016/j.sca.2025.100120
- Pham, C. M., Lokuge, S., Nguyen, T.-T., & Adamopoulos, A. (2023). Exploring knowledge management enablers for blockchain-enabled food supply chain implementations. Journal of Knowledge Management, 28(1), 210–231. https://doi.org/10.1108/JKM-07-2022-0586
- Qin, H., Simchi‐Levi, D., Ferer, R., Mays, J., Merriam, K., Forrester, M., & Hamrick, A. (2022). Trading safety stock for service response time in inventory positioning. Production and Operations Management, 31(12), 4462–4474. https://doi.org/10.1111/poms.13869
- Reyaldi, F., Arianto, B., Moektiwibowo, H., & Mandagie, K. L. (2023). Analisis Pengendalian Persediaan Bahan Baku Dengan Pendekatan Metode Economic Order Quantity (Eoq). Jurnal Teknik Industri Universitas Dirgantara Marsekal Suryadarma (Unsurya), 12(1), 80–89. https://journal.universitassuryadarma.ac.id/index.php/jtin/article/view/1055
- Saldanha, J. P. (2022). Estimating the reorder point for a fill-rate target under a continuous review policy in the presence of non-standard lead-time demand distributions. Transportation Research Part E: Logistics and Transportation Review, 164, 102766. https://doi.org/https://doi.org/10.1016/j.tre.2022.102766
- Saldanha, J. P., Price, B. S., & Thomas, D. J. (2023). A nonparametric approach for setting safety stock levels. Production and Operations Management, 32(4), 1150–1168. https://doi.org/10.1111/poms.13918
- San-José, L. A., Sicilia, J., González-de-la-Rosa, M., & Febles-Acosta, J. (2022). Profit maximization in an inventory system with time-varying demand, partial backordering and discrete inventory cycle. Annals of Operations Research, 316(2), 763–783. https://doi.org/10.1007/s10479-021-04161-6
- Seyedan, M., Mafakheri, F., & Wang, C. (2023). Order-up-to-level inventory optimization model using time-series demand forecasting with ensemble deep learning. Supply Chain Analytics, 3, 100024. https://doi.org/https://doi.org/10.1016/j.sca.2023.100024
- Subur, S., & Andriani, M. (2025). Analisis Persediaan Bahan Baku Kelapa Sawit Dengan Menggunakan Metode Economic Order Quantity (EOQ). Jurnal Industri Samudra, 6(1), 32–37. https://doi.org/10.55377/jis.v6i1.11367
- Sukmana, S. D., & Wijaya, H. (2026). Evaluate the Effectiveness of the Inventory Accounting Information System in Supporting Internal Control. Advances: Jurnal Ekonomi & Bisnis, 4(3 SE-Articles), 542–557. https://doi.org/10.60079/ajeb.v4i3.811
- Teerasoponpong, S., & Sopadang, A. (2022). Decision support system for adaptive sourcing and inventory management in small- and medium-sized enterprises. Robotics and Computer-Integrated Manufacturing, 73, 102226. https://doi.org/https://doi.org/10.1016/j.rcim.2021.102226
- Utama, D. M., Santoso, I., Hendrawan, Y., & Dania, W. A. P. (2022). Integrated procurement-production inventory model in supply chain: A systematic review. Operations Research Perspectives, 9, 100221. https://doi.org/https://doi.org/10.1016/j.orp.2022.100221
- Vázquez-Serrano, J. I., Cárdenas-Barrón, L. E., Vicencio-Ortiz, J. C., Smith, N. R., Bourguet-Díaz, R. E., Céspedes-Mota, A., & Peimbert-García, R. E. (2025). An integrated analytical framework for inventory and pricing of perishable products in multi-echelon supply chains. Supply Chain Analytics, 12, 100157. https://doi.org/https://doi.org/10.1016/j.sca.2025.100157
- Vazquez Hernandez, J., & Elizondo Rojas, M. D. (2023). Improving spare parts (MRO) inventory management policies after COVID-19 pandemic: a Lean Six Sigma 4.0 project. The TQM Journal, 36(6), 1627–1650. https://doi.org/10.1108/TQM-08-2023-0245
- Yassine, N. (2022). Inventory planning under supplier uncertainty in a two-level supply chain. The International Journal of Logistics Management, 34(2), 497–516. https://doi.org/10.1108/IJLM-02-2021-0104
- Yeboah, S., Kjærland, F., & Kustec, I. (2025). Resilience in Cyclicality: Impact of Inventory Management Efficiency on Operational Profitability. Managerial and Decision Economics, 46(2), 832–842. https://doi.org/10.1002/mde.4406
- Zamani Dadaneh, D., Moradi, S., & Alizadeh, B. (2023). Simultaneous planning of purchase orders, production, and inventory management under demand uncertainty. International Journal of Production Economics, 265, 109012. https://doi.org/https://doi.org/10.1016/j.ijpe.2023.109012
- Zhou, Y., Shen, X., & Yu, Y. (2023). Inventory control strategy: based on demand forecast error. Modern Supply Chain Research and Applications, 5(2), 74–101. https://doi.org/10.1108/MSCRA-02-2023-0009
References
Afiah, N. (2025). Analisis Pengelolaan Persediaan Bahan Baku Dengan Menggunakan Metode EOQ Pada Lewa Bakery. Bongaya Journal of Research in Accounting (BJRA), 8(2), 103–111. https://doi.org/10.37888/bjra.v8i2.714
Ahakonye, L. A. C., Zainudin, A., Shanto, M. J. A., Lee, J.-M., Kim, D.-S., & Jun, T. (2024). A multi-MLP prediction for inventory management in manufacturing execution system. Internet of Things, 26, 101156. https://doi.org/https://doi.org/10.1016/j.iot.2024.101156
Alam, M. K., Thakur, O. A., & Islam, F. T. (2023). Inventory management systems of small and medium enterprises in Bangladesh. Rajagiri Management Journal, 18(1), 8–19. https://doi.org/10.1108/RAMJ-09-2022-0145
Arief, M., & Adi, T. W. (2024). Optimalisasi pengendalian persediaan pertamax pada fuel terminal X menggunakan metode Economic Order Quantity. Prosiding Seminar Nasional Teknologi Energi Dan Mineral, 4(1), 481–491. https://doi.org/10.53026/prosidingsntem.v4i1.180
Arifani, A. (2023). Relationship between Working Capital Elements and Company Profitability. Advances: Jurnal Ekonomi & Bisnis, 1(2), 124–130. https://doi.org/10.60079/ajeb.v1i2.73
Balkhi, B., Alshahrani, A., & Khan, A. (2022). Just-in-time approach in healthcare inventory management: Does it really work? Saudi Pharmaceutical Journal, 30(12), 1830–1835. https://doi.org/https://doi.org/10.1016/j.jsps.2022.10.013
Berling, P., & Sonntag, D. R. (2022). Inventory control in production–inventory systems with random yield and rework: The unit‐tracking approach. Production and Operations Management, 31(6), 2628–2645. https://doi.org/10.1111/poms.13706
Bucarey, V., Calderón, S., Muñoz, G., & Semet, F. (2024). Decision-Focused Predictions via Pessimistic Bilevel Optimization: A Computational Study BT - Integration of Constraint Programming, Artificial Intelligence, and Operations Research (B. Dilkina (ed.); pp. 127–135). Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-60597-0_9
Chakir, A., Andry, J. F., Ullah, A., Bansal, R., & Ghazouani, M. (2024). Engineering applications of artificial intelligence. Springer Nature.
Essila, J. C. (2022). Strategies for reducing healthcare supply chain inventory costs. Benchmarking: An International Journal, 30(8), 2655–2669. https://doi.org/10.1108/BIJ-11-2021-0680
Feng, Y., Abdus, S., Tuo, G., & Chen, S. (2022). Raw materials and production control with random supply and demand, an outside market and production capacity. Operations Research Letters, 50(6), 679–684. https://doi.org/https://doi.org/10.1016/j.orl.2022.10.008
Guo, Y., Liu, F., Song, J.-S., & Wang, S. (2025). Supply chain resilience: A review from the inventory management perspective. Fundamental Research, 5(2), 450–463. https://doi.org/https://doi.org/10.1016/j.fmre.2024.08.002
Hammler, P., Riesterer, N., Mu, G., & Braun, T. (2023). Multi-Echelon Inventory Optimization Using Deep Reinforcement Learning BT - Quantitative Models in Life Science Business: From Value Creation to Business Processes (J. K. Canci, P. Mekler, & G. Mu (eds.); pp. 73–93). Springer International Publishing. https://doi.org/10.1007/978-3-031-11814-2_5
Huo, B., Li, D., & Gu, M. (2024). The impact of supply chain resilience on customer satisfaction and financial performance: A combination of contingency and configuration approaches. Journal of Management Science and Engineering, 9(1), 38–52. https://doi.org/https://doi.org/10.1016/j.jmse.2023.10.002
Huynh, N., & Le, Q. N. (2025). From chain to capital: Supply chain risks and working capital management. Economics Letters, 247, 112100. https://doi.org/https://doi.org/10.1016/j.econlet.2024.112100
Jaber, M. Y., & Peltokorpi, J. (2024). Economic order/production quantity (EOQ/EPQ) models with product recovery: A review of mathematical modeling (1967–2022). Applied Mathematical Modelling, 129, 655–672. https://doi.org/https://doi.org/10.1016/j.apm.2024.02.022
Jadidi, O., Firouzi, F., & Sorooshian, S. (2025). A closed-form solution approach for optimal reorder point in economic order quantity models with uncertain demands. Decision Analytics Journal, 16, 100622. https://doi.org/https://doi.org/10.1016/j.dajour.2025.100622
Khakbaz, A., Alfares, H. K., Amirteimoori, A., & Tirkolaee, E. B. (2024). A novel cross-docking EOQ-based model to optimize a multi-item multi-supplier multi-retailer inventory management system. Annals of Operations Research. https://doi.org/10.1007/s10479-023-05790-9
Mallick, R. K., Patra, K., & Mondal, S. K. (2023). A new economic order quantity model for deteriorated items under the joint effects of stock dependent demand and inflation. Decision Analytics Journal, 8, 100288. https://doi.org/https://doi.org/10.1016/j.dajour.2023.100288
Milewski, D., & Wiśniewski, T. (2022). Regression analysis as an alternative method of determining the Economic Order Quantity and Reorder Point. Heliyon, 8(9). https://doi.org/10.1016/j.heliyon.2022.e10643
Öztürk, H., & Konstantaras, I. (2025). EOQ model with defective products, batch shipment and partial backorders. Annals of Operations Research, 351(3), 1941–1988. https://doi.org/10.1007/s10479-025-06669-7
Palanivel, M., Venkadesh, M., Vetriselvi, S., & Suganya, M. (2025). An analytics-driven economic order quantity model integrating fuzzy learning for deteriorating imperfect items in sustainable supply chains. Supply Chain Analytics, 10, 100120. https://doi.org/https://doi.org/10.1016/j.sca.2025.100120
Pham, C. M., Lokuge, S., Nguyen, T.-T., & Adamopoulos, A. (2023). Exploring knowledge management enablers for blockchain-enabled food supply chain implementations. Journal of Knowledge Management, 28(1), 210–231. https://doi.org/10.1108/JKM-07-2022-0586
Qin, H., Simchi‐Levi, D., Ferer, R., Mays, J., Merriam, K., Forrester, M., & Hamrick, A. (2022). Trading safety stock for service response time in inventory positioning. Production and Operations Management, 31(12), 4462–4474. https://doi.org/10.1111/poms.13869
Reyaldi, F., Arianto, B., Moektiwibowo, H., & Mandagie, K. L. (2023). Analisis Pengendalian Persediaan Bahan Baku Dengan Pendekatan Metode Economic Order Quantity (Eoq). Jurnal Teknik Industri Universitas Dirgantara Marsekal Suryadarma (Unsurya), 12(1), 80–89. https://journal.universitassuryadarma.ac.id/index.php/jtin/article/view/1055
Saldanha, J. P. (2022). Estimating the reorder point for a fill-rate target under a continuous review policy in the presence of non-standard lead-time demand distributions. Transportation Research Part E: Logistics and Transportation Review, 164, 102766. https://doi.org/https://doi.org/10.1016/j.tre.2022.102766
Saldanha, J. P., Price, B. S., & Thomas, D. J. (2023). A nonparametric approach for setting safety stock levels. Production and Operations Management, 32(4), 1150–1168. https://doi.org/10.1111/poms.13918
San-José, L. A., Sicilia, J., González-de-la-Rosa, M., & Febles-Acosta, J. (2022). Profit maximization in an inventory system with time-varying demand, partial backordering and discrete inventory cycle. Annals of Operations Research, 316(2), 763–783. https://doi.org/10.1007/s10479-021-04161-6
Seyedan, M., Mafakheri, F., & Wang, C. (2023). Order-up-to-level inventory optimization model using time-series demand forecasting with ensemble deep learning. Supply Chain Analytics, 3, 100024. https://doi.org/https://doi.org/10.1016/j.sca.2023.100024
Subur, S., & Andriani, M. (2025). Analisis Persediaan Bahan Baku Kelapa Sawit Dengan Menggunakan Metode Economic Order Quantity (EOQ). Jurnal Industri Samudra, 6(1), 32–37. https://doi.org/10.55377/jis.v6i1.11367
Sukmana, S. D., & Wijaya, H. (2026). Evaluate the Effectiveness of the Inventory Accounting Information System in Supporting Internal Control. Advances: Jurnal Ekonomi & Bisnis, 4(3 SE-Articles), 542–557. https://doi.org/10.60079/ajeb.v4i3.811
Teerasoponpong, S., & Sopadang, A. (2022). Decision support system for adaptive sourcing and inventory management in small- and medium-sized enterprises. Robotics and Computer-Integrated Manufacturing, 73, 102226. https://doi.org/https://doi.org/10.1016/j.rcim.2021.102226
Utama, D. M., Santoso, I., Hendrawan, Y., & Dania, W. A. P. (2022). Integrated procurement-production inventory model in supply chain: A systematic review. Operations Research Perspectives, 9, 100221. https://doi.org/https://doi.org/10.1016/j.orp.2022.100221
Vázquez-Serrano, J. I., Cárdenas-Barrón, L. E., Vicencio-Ortiz, J. C., Smith, N. R., Bourguet-Díaz, R. E., Céspedes-Mota, A., & Peimbert-García, R. E. (2025). An integrated analytical framework for inventory and pricing of perishable products in multi-echelon supply chains. Supply Chain Analytics, 12, 100157. https://doi.org/https://doi.org/10.1016/j.sca.2025.100157
Vazquez Hernandez, J., & Elizondo Rojas, M. D. (2023). Improving spare parts (MRO) inventory management policies after COVID-19 pandemic: a Lean Six Sigma 4.0 project. The TQM Journal, 36(6), 1627–1650. https://doi.org/10.1108/TQM-08-2023-0245
Yassine, N. (2022). Inventory planning under supplier uncertainty in a two-level supply chain. The International Journal of Logistics Management, 34(2), 497–516. https://doi.org/10.1108/IJLM-02-2021-0104
Yeboah, S., Kjærland, F., & Kustec, I. (2025). Resilience in Cyclicality: Impact of Inventory Management Efficiency on Operational Profitability. Managerial and Decision Economics, 46(2), 832–842. https://doi.org/10.1002/mde.4406
Zamani Dadaneh, D., Moradi, S., & Alizadeh, B. (2023). Simultaneous planning of purchase orders, production, and inventory management under demand uncertainty. International Journal of Production Economics, 265, 109012. https://doi.org/https://doi.org/10.1016/j.ijpe.2023.109012
Zhou, Y., Shen, X., & Yu, Y. (2023). Inventory control strategy: based on demand forecast error. Modern Supply Chain Research and Applications, 5(2), 74–101. https://doi.org/10.1108/MSCRA-02-2023-0009