Penerapan Metode Collaborative Planning Forecasting & Replenishment (CPFR) dalam Perencanaan Persediaan untuk Meningkatkan Kepatuhan Lead Time Supply terhadap KPI pada Studi Kasus PT XYZ

Qisma Rosalina Wahda; Erna Indriastiningsih; Bekti Nugrahadi

doi:10.61132/jupiter.v4i2.1345

Authors

Qisma Rosalina Wahda Universitas Sahid Surakarta
Erna Indriastiningsih Universitas Sahid Surakarta
Bekti Nugrahadi Universitas Sahid Surakarta

DOI:

https://doi.org/10.61132/jupiter.v4i2.1345

Keywords:

CPFR, Forecasting, Inventory Planning, KPI, Lead Time Supply

Abstract

Ineffective spare part inventory planning may lead to supply delays and reduced compliance with lead time supply key performance indicators (KPIs). This study aims to implement the Collaborative Planning, Forecasting, and Replenishment (CPFR) method in spare part inventory planning at PT XYZ and to compare lead time supply performance before and after the implementation of the CPFR method. This research utilizes spare part usage data from January to June 2025, focusing on fast-moving spare parts. Demand forecasting is conducted using an error forecasting approach with the moving average method. Forecast accuracy is evaluated using the Mean Absolute Deviation (MAD) and Mean Absolute Percentage Error (MAPE). Furthermore, inventory planning is carried out through the calculation of safety stock and reorder point (ROP) as the basis for determining replenishment decisions. The results indicate that the simulated implementation of the CPFR method provides a more structured and anticipative inventory planning process. The comparison of performance before and after the application of CPFR shows an improvement in lead time supply compliance with the established KPIs. Therefore, the CPFR method has the potential to support improved spare part inventory planning performance at PT XYZ.

References

Badan Pusat Statistik. (2024). Produk domestik bruto menurut lapangan usaha. BPS-Statistics Indonesia.

Bowersox, D. J., Closs, D. J., & Cooper, M. B. (2019). Supply chain logistics management. McGraw-Hill Education.

Chopra, S., & Meindl, P. (2019). Supply chain management: Strategy, planning, and operation (7th ed.). Pearson.

Febrianto, A. (2025). Operational efficiency and sustainable asset management: A data-driven framework for heavy equipment management. Journal of Industrial Engineering & Management Systems. https://doi.org/10.1016/j.rineng.2025.106476

Heizer, J., & Render, B. (2020). Operations management (13th ed.). Pearson.

Ifraz, M. (2025). A systematic literature review on spare parts classification and inventory management. International Journal of Logistics Systems. https://doi.org/10.35378/gujs.1484883

Lewis, C. D. (1982). Industrial and business forecasting methods. Butterworths.

Ramadhan, I. (2024). Optimalisasi efektivitas preventive maintenance berbasis data pada industri manufaktur. Jurnal Teknologi dan Sistem Industri.

Shi, Y., Wang, J., & Liu, L. (2022). Optimization of preventive maintenance strategy using probabilistic failure models. European Journal of Operational Research.

Stadtler, H. (2021). Supply chain management and advanced planning: Concepts, models, software, and case studies (7th ed.). Springer.

Stevenson, W. J. (2018). Operations management (13th ed.). McGraw-Hill Education.

Toiviainen, T., & Hansen, J. (2011). Collaborative planning, forecasting, and replenishment research. Paper 2/2/2011 IOM 483 Operations Consulting - Spring.

Yang, Q., Li, Z., & Chen, Y. (2023). The impact of supplier relationship management on supplier collaboration and performance. International Journal of Production Economics.

Zhang, S., & Xie, J. (2021). Spare parts inventory management: A comprehensive review. Sustainability, 13(5), 2460. https://doi.org/10.3390/su13052460

Zhang, W. (2020). A review of equipment performance and availability metrics in modern industry. Journal of Manufacturing Systems.