Ineffective logistics management at S.Factory

Abstract

S. Factory, a key production hub of a multinational electronics corporation located in Saigon Hi-Tech Park, has contributed significantly to Vietnam’s export performance. However, despite its strong manufacturing capability and advanced systems, the factory has continuously struggled to meet its 95% On-Time Delivery (OTD) target, particularly in the Southeast Asia (SEA) region. This research aims to identify the root causes of OTD underperformance and propose feasible, data-driven solutions to improve logistics reliability and cross-functional coordination. The study employed a mixed-method approach using both primary and secondary data. Quantitative data were collected from SAP shipment dashboards, booking records, and OTD reports, while qualitative insights were obtained through in-depth interviews with key stakeholders from the Production Control, Sales & Distribution (SD), and Warehouse departments. The analysis confirmed that suboptimal vessel booking management is the main operational problem affecting shipment-week performance. Further validation identified inaccurate volume forecasting as the underlying issue, driven by three key causes: (1) demand-side uncertainty from subsidiaries, (2) KPI misalignment across departments, and (3) the absence of a standardized forecasting system. Among these causes, the lack of a clear and standardized forecasting system was validated as the root cause of recurring forecast errors and poor data synchronization. To address this, two alternative solutions were proposed: (1) developing a Forecasting T-Code (nERP) integrated within SAP, and (2) adopting an external cloud-based forecasting platform. After evaluating feasibility, cost, and long-term sustainability, the study recommends implementing Solution 1 – the SAP-integrated Forecasting T-Code, which leverages existing IT infrastructure and aligns with the principles of Business Process Re-engineering. This solution enables real-time collaboration between SD, SCM, and Production teams, ensuring consistent forecast data and improved booking accuracy. A 20-week action plan was developed to guide implementation through six phases—from system analysis to continuous improvement. The expected outcomes include higher forecast accuracy, reduced booking amendments, and improved OTD performance, thereby strengthening S. Factory’s operational excellence and supply chain competitiveness.