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International Journal of Management and Business Development

Open Access Peer Review International
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Features of The Data-Driven Logistics 360° Methodology as A Comprehensive Approach to Optimizing Logistics Processes and Increasing A Company’s Operating Profit

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Maxim Andreevich Perminov 1 ,
4 Expert in International Logistics and Predictive Supply Chain Management Saint Petersburg, FL, USA

Abstract

Under the intensifying pressure on the logistics sector’s margins, driven by outpacing cost dynamics, standard managerial practices are losing effectiveness. This study is aimed at the conceptualization and empirical validation of the comprehensive Data-Driven Logistics 360° methodology designed for the systemic optimization of logistics operations and the direct increase of operating profit. The research objective is to demonstrate a causal link between the implementation of data-based tools and the achievement of measurable financial outcomes. The methodological foundation rests on a mixed approach combining a systematic review of academic sources and a single-case study of George Biosystems for 2020–2023. Based on the analysis, an iterative three-tier model was developed: Diagnostics and analytical assessment, Identification and prioritization of problem areas, Implementation of solutions and verification of results. Practical testing of the model recorded a sustained reduction in key cost items, primarily for fuel and raw material procurement, within the range of 10–40%, which translated into a 7–14% increase in monthly operating profit. The study concludes that the proposed methodology serves not only as a tool for improving efficiency but also as a foundation for building operational resilience in supply chains. The reported results are addressed to leaders of logistics and operations functions as well as researchers in the field of supply chain management.

 

Keywords

data-driven logistics, logistics optimization, supply chain management, operating profit, efficiency improvement, case study, supply chain resilience, Internet of Things, big data analytics, cost management.

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