The use of analytics to minimize risks and optimize processes in logistics and supply chain

the article discusses the possibilities of using analytics to minimize risks and improve the efficiency of processes in logistics and supply chain. Due to the fact that they are currently facing challenges caused by global instability, changing consumer preferences, and the complexity of business processes, the use of data analytics becomes a necessary tool for optimization and subsequent improvement of sustainability. The aim of this paper is to systematize existing approaches to the use of analytical methods, such as predictive modeling, big data analysis, machine learning, as well as to assess their impact on cost reduction, improving flexibility, and sustainability of supply chains. The methodological basis of the work was a system analysis, supplemented by a comparison of practical cases, modeling the potential effects of the introduction of analytics. Scientific papers, industry reports, as well as specific examples of technology implementation in companies, data on which are posted on the Internet, were studied. The results of the study show that analytical technologies allow companies to predict, prevent risks, improve inventory management, and integrate flexible strategies into operational activities. The findings demonstrate the importance of using analytics to achieve benefits and increase the sustainability of logistics systems. The article will be useful for heads of logistics departments, analysts, and specialists in the field of supply chain management.

analytics, logistics, supply chain, risk minimization, process optimization, predictive modeling, machine learning, big data