Toward a More Dynamic Supplier Evaluation: A Time Series Forecasting Perspective : Membangun Upaya Evaluasi Pemasok yang Lebih Dinamis: Perspektif Peramalan Deret Waktu - Fikri, Muhammad Naufal; Pujawan, I Nyoman; Karningsih, Putu Dana (Universitas Muhammadiyah Sidoarjo, 2026)
General Background: Procurement continuity is essential for maintaining healthcare service operations, where supplier failures can disrupt service quality. Specific Background: This study evaluates supplier reliability in provincial government healthcare facilities in East Java, Indonesia, using three key performance metrics: on-time delivery (OTD), quantity fulfillment, and order lead time, based on 2023 contract data from 13 pharmaceutical suppliers. Knowledge Gap: Traditional supplier evaluation is often static, limiting the ability to detect temporal performance shifts and future reliability risks. Aims: This research aims to develop a dynamic supplier evaluation framework by integrating time series forecasting methods. Results: Historical performance showed moderate–high reliability (OTD ≈ 80.04%, quantity fulfillment ≈ 79.3%, lead time ≈ 20 days). Forecasting with exponential smoothing and Theta methods indicated declining OTD and quantity fulfillment, alongside improved lead time performance (≈ 10 days). Forecast errors were MAE ≈ 25% and RMSE ≈ 32% for service metrics, and MAE ≈ 8 days and RMSE ≈ 9 days for lead time. Novelty: The study advances supplier evaluation by combining multimetrical reliability assessment with forecasting-based temporal detection, moving beyond one-time performance scoring. Implications: This dynamic approach supports healthcare procurement managers in prioritizing resilient suppliers, adapting sourcing strategies, and mitigating operational risks in uncertain environments. Highlights: Supplier performance exhibited fluctuating reliability patterns across monthly contract periods. Forecasting results revealed decreasing delivery and fulfillment rates with shorter shipment durations. Service compliance metrics were strongly correlated, while lead time remained relatively independent. Keywords: Public Healthcare Procurement, Supplier Evaluation, Supplier Performance Forecasting, Supplier Reliability