Citation:

Derry Sumargo Basyir, Dermawan Wibisono. "Integrative Cost Optimization Framework for FMCG Logistics: A Case Study of PT. KSN using SCOR, Five Levers, and Strategic Profit Modelling" International Research Journal of Economics and Management Studies, Vol. 4, No. 7, pp. 193-205, 2025.

Abstract:

The increasing complexity of international logistics, particularly in the fast-moving consumer goods (FMCG) sector, has amplified the need for an integrative and data-driven framework to control export logistics costs. This research addresses that need by proposing and applying the Integrative Cost Efficiency Evaluation Framework (ICEEF), which combines three proven models: SCOR (for operational diagnostics), Gartner’s Five Levers (for strategic cost driver identification), and Strategic Profit Modelling (SPM) (for profitability simulation). Using PT. KSN, as a case study, the research applied a mixed-method approach, combining quantitative data analysis of over 350 shipment records from 2021 to 2023 with qualitative insights from interviews and focus group discussions. SCOR metrics—including CO 1.1 (Total Supply Chain Cost), Metric 3.5 (Planning Cost Efficiency), and RS.1.1 (Cycle Time)—were used to evaluate baseline performance. Additionally, a new metric, the Planning Cost Index (PCI), was introduced to measure planning inefficiencies. Data analysis revealed that cost overruns peaked at 43% in 2022, while PCI increased to 9.4%, signaling fragmented coordination across internal functions. Three scenario simulations were conducted to assess the financial impact of various interventions. In the renegotiated vendor contract scenario, CO 1.1 improved from 43% to 21%, while PCI dropped to 6.7%. In the integrated planning scenario, operational projection saving (OPS) recovered to 97%, demonstrating that proactive synchronization between production readiness and dispatch significantly reduces overstay and premium costs. These findings were validated through stakeholder engagement, confirming the relevance of all Five Levers, particularly in the areas of Demand Management, Lean Operations, and Deal Structuring. This study concludes that the ICEEF framework provides an effective decision-support tool for diagnosing inefficiencies, quantifying cost-to-profit impact, and aligning operational execution with strategic objectives. Limitations include reliance on internal shipment-level data and assumptions of vendor behavior consistency. Future research is encouraged to expand validation across industries and integrate AI-based forecasting to enhance proactive cost controlity.

References:

[1] APICS. (2017). APICS SCOR Model Version 12.0. Chicago: APICS.
[2] Supply Chain Management: Strategy, Planning, and Operation (6th ed.). Pearson.
[3] Wibisono, D. (2003). Sistem Manajemen Kinerja yang Terintegrasi. Penerbit Guna Widya.
[4] McKinsey & Company. (2020). Next-generation supply chain cost modeling. [Report].
[5] Ellram, L.M., Tate, W.L. (2004). Understanding and Managing the Services Supply Chain. Journal of Supply Chain Management, 40(3), 17–32.
[6] O’Byrne, R. (2017). AGCO’s Supply Chain Transformation: Journey to World Class Logistics. Logistics Bureau Publication.
[7] Basyir, D. S. (2025). Integrative Cost Optimization Framework for FMCG Logistics: A Case Study of PT. KSN using SCOR, Five Levers, and Strategic Profit Modelling. Master’s Thesis, Institut Teknologi Bandung.
[8] Qureshi, K.M., Mewada, B.G., Kaur, S., et al. (2024). Digital integration in fragmented supply chains: A framework for logistics financialization. Heliyon, 10, e30661. https://doi.org/10.1016/j.heliyon.2024.e30661:contentReference[oaicite:0]{index=0}
[9] Kudla, N.L., Klaas-Wissing, T. (2012). Sustainability in shipper–LSP relationships: A tentative taxonomy based on agency theory. Journal of Purchasing & Supply Management, 18(4), 218–2311-s2.0-S147840921200019…
[10] Cao, J., Sil, A., Alikhani, R., et al. (2025). Logistics efficiency under stochastic uncertainty: Route selection under fleet limitations. Computers & Industrial Engineering, 203, 1109851-s2.0-S036083522500131…
[11] Jasman, N. A., & Ariffin, N. H. M. (2024). Risk Factors Analysis in Halal Supply Chain Management. Journal of Advanced Research in Applied Sciences and Engineering Technology, 46(2), 213–226.
[12] Kusrini, E., Helia, V. N., Miranda, S., & Asshiddiqi, F. (2023). SCOR racetrack to improve supply chain performance. International Journal of Supply Chain Management Studies, [online first].
[13] Georgise, F.B., Thoben, K.D., & Seuring, S. (2012). Adapting the SCOR Model to Suit Different Scenarios: A Literature Review & Research Agenda. International Journal of Business and Management, 7(2), 1–13.
[14] Zimmer, L. (2006). Qualitative meta-synthesis: A question of dialoguing with texts. Journal of Advanced Nursing, 53(3), 311–3181-s2.0-S036083521200303…
[15] Sil, A., Mallick, S.C., & Bhattacharya, A. (2022). Multi-echelon routing and dynamic decision-making in perishable product supply chains. European Journal of Operational Research, 300(2), 647–663

Keywords:

Logistics Cost Optimization; SCOR Model; Gartner’s Five Levers; Strategic Profit Modelling (SPM); Planning Cost Index (PCI); Operational Projection Saving (OPS); FMCG; Export Logistics; ICEEF Framework; Supply Chain Efficiency.