Design Of An Operations Strategy-Based Framework To Align Demand And Capacity In A Crsytal Ice Manufacturing SME Within The Cold-Chain Industry
DOI:
https://doi.org/10.24256/kharaj.v8i1.9163Keywords:
Operational Alignment, Operations Strategy, Performance Objectives, Speed, Dependability, Analytical Hierarchy Process (AHP), Cold Chain SME, Mixed Method.Abstract
This study examines the mismatch between production capacity, market demand, and distribution performance at a small and medium-sized enterprise (SME) producing ice crystals (Company A) in the cold chain industry. The company operates two machines with a total capacity of 10 tonnes per day, but actual sales volume only reaches 4-5 tonnes per day. This situation has resulted in low production utilisation, limited distribution coverage. Operational data for 2024-2025 shows that customer demand fluctuates on a daily, weekly, and hourly basis, while ordering behaviour is sudden, preventing the company from optimally planning production and distribution routes. The capacity of five motor couriers within a 12 km radius also becomes a bottleneck during peak hours, hindering delivery accuracy.Based on these conditions, this study formulates the problem of how to align production capacity, market demand, and distribution performance by determining the operational performance objectives; quality, speed, reliability, flexibility, and cost that need to be prioritised. The research design uses a mixed method case study with a quantitative dominance. Internal archive data analysis was conducted to calculate production utilisation, distribution utilisation, sales-to-output ratio, and demand-capacity gap stability. Next, six internal experts (the owner, administrative staff, two production operators, and two couriers) provided assessments through the Analytical Hierarchy Process (AHP), and the results were tested for consistency before being combined into group priority weights.The results of the study show that there is a consistent mismatch between installed capacity and actual demand. Average production utilisation is at 34-36%, while distribution loads accumulate during morning and afternoon peak hours. AHP analysis shows that cost, speed, and reliability are the top priorities for improving operational performance, in line with the patterns of inefficiency apparent in the operational data. This study in the discussion section highlights that distribution responsiveness, minimisation of inefficient costs of operations, and provision consistency in the fulfilment of services are essential in harmonising capacity and demand. The combination of operational results and AHP priorities provides the design of an alignment-based framework of an operational strategy. Suggestions on future research include creating a digital system that uses real-time data and increasing investigation into other cold chain SMEs in order to ensure that this strategic framework is more externally valid.
References
Ahmad, N. A., Aziz, A. A., & Arsat, A. (2024). Enhancing the resilience of micro food and beverage businesses in Malaysia: An evaluation critical success factors approach. Journal of Tourism, Hospitality and Culinary Arts, 16(1), 854–868.
Ajeigbe, K., & Peace, P. (2023). Evaluating the impact of transportation costs on supply chain forecasting.
Alahmari, K. H. (2023). The role of time-driven activity-based costing in integrated supply chain management: An empirical study of modelling operational costs at 4PLs (Doctoral dissertation, Victoria University).
Ambulkar, S., et al. (2023). Frequent supply chain disruptions and firm performance: The moderating role of exploitation, exploration and supply chain ambidexterity. International Journal of Physical Distribution & Logistics Management, 53(10), 1261–1285.
Anam, B. E., et al. (2024). Economic recovery and growth plan, economic sustainability plan and national development plan (2021–2025): The Nigerian experience under President Muhammadu Buhari. Cogent Social Sciences, 10(1), 2289600.
Bugingo, E., & Ndimubenshi, E. L. (2025). Application of AHP in decision-making: Case studies. In The Art of Decision Making: Applying AHP in Practice (p. 121).
Caramuta, C., et al. (2021). Integration of BPMN modeling and multi-actor AHP-aided evaluation to improve port rail operations. Transportation Research Procedia, 52, 139–146.
Crivellari, A., et al. (2022). Multi-target CNN-LSTM regressor for predicting urban distribution of short-term food delivery demand. Journal of Business Research, 144, 844–853.
Geminarqi, E. R., & Purnomo, H. (2023). Improving operational management efficiency in the food and beverage industry: A systematic literature review. Open Access Indonesia Journal of Social Sciences, 6(5), 1143–1149.
Gilpa, L., et al. (2024). Human resource scarcity as a predictor of employee workload and morale: A trajectory toward policy model development. SSRN. https://ssrn.com/abstract=4979921
Hassan, B. (2024). Demand-driven supply chain planning and responsive replenishment for SMEs. Kabul University. Available at ResearchGate.
Hidayat, D. W., & Mulyono, N. B. (2025). Optimizing fuel distribution costs through vehicle routing problem modeling in Jakarta–Tanjung Gerem terminals. JIMKES (Jurnal Ilmiah Manajemen Kesatuan), 13(5). https://doi.org/10.37641/jimkes.v13i5.3547
Jasiński, P. (2024). The demand planning renaissance: A data-driven approach. Journal of Supply Chain Management, Logistics and Procurement, 7(1), 6–24.
Jia, G., et al. (2022). Control of ice crystal nucleation and growth during the food freezing process. Comprehensive Reviews in Food Science and Food Safety, 21(3), 2433–2454.
Kandampully, J., & Solnet, D. (2024). Service management principles for hospitality & tourism in the age of digital technology. Springer.
Kazantsev, N., et al. (2022). Investigating barriers to demand-driven SME collaboration in low-volume high-variability manufacturing. Supply Chain Management: An International Journal, 27(2), 265–282.
Kumar, S., & Mallipeddi, R. R. (2022). Impact of cybersecurity on operations and supply chain management: Emerging trends and future research directions. Production and Operations Management, 31(12), 4488–4500.
Nikiforos, M. (2022). Demand, distribution, productivity, structural change, and (secular?) stagnation. In Handbook of Economic Stagnation (pp. 137–158). Academic Press.
Petropoulos, F., Akkermans, H., Aksin, O. Z., Ali, I., Babai, M. Z., & Barbosa-Povoa, A. (2025). Operations & supply chain management: Principles and practice. International Journal of Production Research, 63, 330–513. https://doi.org/10.1080/00207543.2025.2555531
Rakyta, M., et al. (2024). The change in maintenance strategy on the efficiency and quality of the production system. Electronics, 13(17), 3449.
Slack, N., & Lewis, M. (2017). Operations strategy (5th ed.). Pearson.
Slack, N., Brandon-Jones, A., & Burgess, N. (2022). Operations management (10th ed.). Pearson.
Tang, Y. M., et al. (2024). IoT-based information system on cold-chain logistics service quality (ICCLSQ) management in logistics 4.0. Information Systems Frontiers, 26(2), 689–708.
Utami, D. M., et al. (2024). The role of the 30% threshold for Islamic parties: A fast-growing middle class and religion-based political preferences in Indonesia. Heliyon, 10(4).
Vetrivel, S. C., Saravanan, T. P., & Maheswari, R. (2025). Smart factories and energy efficiency in Industry 4.0. In T. Choudhury, R. K. Singh, R. Tomar, S. Balamurugan, & J. C. Patni (Eds.), Distributed time-sensitive systems. Wiley. https://doi.org/10.1002/9781394197798.ch4
Yin, R. K. (2018). Case study research and applications: Design and methods (6th ed.). SAGE Publications.
Downloads
Published
How to Cite
Issue
Section
Citation Check
License
Copyright (c) 2026 Maudy Farras Raihan, Dermawan Wibisono
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution-ShareAlike 4.0 International License. In line with the license, authors are allowed to share and adapt the material. In addition, the material must be given appropriate credit, provided with a link to the license, and indicated if changes were made. If authors remix, transform or build upon the material, authors must distribute their contributions under the same license as the original.
