Managing Operational Risks in High-Frequency Route Planning

Shalamov Ruslan

Citation: Shalamov Ruslan, "Managing Operational Risks in High-Frequency Route Planning", Universal Library of Business and Economics, Volume 02, Issue 02.

Copyright: This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

This article presents a systematic analysis of operational risks emerging during the implementation and operation of high-frequency route planning systems in logistics, driven by the need for rapid response to changes in traffic conditions, new orders, and service quality requirements. The relevance of the study is determined by the growth of e-commerce volumes and heightened customer expectations regarding delivery speed. The objective of the research is to classify and assess operational risks in the context of high-frequency route planning, as well as to develop recommendations for their mitigation through the integration of modern technologies and organizational practices. The methodology includes the collection of incident data, analysis of IT project budget overruns and human errors statistics, and evaluation of the consequences of failures through examples of downtime costs. The novelty of the work stems from the holistic integration of process-oriented and strategic approaches to risk management: using ISO 31000:2018 standards and the COSO ERM model, a set of KPIs is suggested for dynamic route planning along with recommendations on how to configure SLAs regarding infrastructure resilience. The main findings show that switching to high-frequency planning can trim down total travel time by at least 23% in comparison to the static approach however, it would entail huge investments in reliable IT infrastructure, high-quality data, and personnel training. Key areas of risk management include ensuring the throughput capacity and fault tolerance of computing resources, regulating data input and processing procedures, automating notifications for immediate response, regular stress-testing of systems under realistic scenarios, and setting KPIs and SLAs with resource redundancy in mind. Integration of predictive analytics, digital twins, and AI-driven alerts increases transparency and reduces failure likelihood, while a “safe-to-fail” culture lessens the impact of the human factor. The article will benefit the managers of logistics operations, risk managers, and IT infrastructure specialists in transport companies. It will also benefit researchers interested in dynamic route planning optimization.


Keywords: Operational Risks, High-Frequency Route Planning, Dynamic Planning, Predictive Analytics, Digital Twins, ISO 31000, COSO ERM, KPI, SLA, IT Infrastructure, Human Factor, Automated Notifications.

Download doi https://doi.org/10.70315/uloap.ulbec.2025.0202005