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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.

References

Transportation and Logistics Industry Trends July 2024 - Atradius USA [Electronic resource]. Access mode: https://atradius.us/knowledge-and-research/reports/industry-trends-transport-and-logistics-industry-trends-july-2024 (date of access: 07/25/2025).

DHL Road Freight Market News – Q 4 2024 [Electronic resource]. Access mode: https://dhl-freight-connections.com/en/business/dhl-road-freight-market-news-q-4-2024/ (date of access: 07/27/2025).

Trucking Industry Segments Post Mixed Results in 2024 [Electronic resource]. Access mode: https://www.ttnews.com/articles/top-100-for-hire-sectors-2025 (date of access: 07/29/2025).

Road Freight Services Market Size - By Service, By Vehicle, By Destination, By End Use, Analysis, Share, Growth Forecast, 2025 - 2034 [Electronic resource]. Access mode: https://www.gminsights.com/industry-analysis/road-freight-services-market (date of access: 07/29/2025).

Transport & Logistics Barometer [Electronic resource]. Access mode: https://www.pwc.de/de/transport-und-logistik/pwc-transport-and-logistics-barometer-h2-2024.pdf (date of access: 07/29/2025).

‘State of Logistics’ Report Highlights AI’s Freight Impact [Electronic resource]. Access mode: https://aashtojournal.transportation.org/state-of-logistics-report-highlights-ais-freight-impact/#:~:text=U.S.%20business%20logistics%20costs%20totaled,pandemic%20patterns%20in%20some%20areas. (date of access:08/18/2025).

Moshood T. D. et al. Digital twins driven supply chain visibility within logistics: A new paradigm for future logistics //Applied System Innovation. – 2021. – Vol. 4 (2). https://doi.org/10.3390/asi4020029.

Logistics Trends 2023/2024: Which Direction for AI? [Electronic resource]. Access mode: https://dhl-freight-connections.com/en/trends/logistics-trends-2023-2024/ (date of access: 08/29/2025).

Lagorio A. et al. A systematic literature review of innovative technologies adopted in logistics management //International Journal of Logistics Research and Applications. – 2022. – Vol. 25 (7). – pp. 1043-1066.

Arunachalam D., Kumar N., Kawalek J. P. Understanding big data analytics capabilities in supply chain management: Unravelling the issues, challenges and implications for practice //Transportation Research Part E: Logistics and Transportation Review. – 2018. – Vol. 114. – pp. 416-436. https://doi.org/10.1016/j.tre.2017.04.001.

Zaidi S. A. H., Khan S. A., Chaabane A. Unlocking the potential of digital twins in supply chains: A systematic review //Supply Chain Analytics. – 2024. – Vol. 7. https://doi.org/10.1016/j.sca.2024.100075.

Digital Logistics Market Size, Share | Growth Report [2032] [Electronic resource]. Access mode: https://www.fortunebusinessinsights.com/digital-logistics-market-109139 (date of access: 09/07/2025).

Supply chain trends 2024: The digital shake-up - KPMG International [Electronic resource]. Access mode: https://kpmg.com/xx/en/our-insights/ai-and-technology/supply-chain-trends-2024.html (date of access: 08/19/2025).

Guan Q. et al. Real-time multi-depot urban logistics optimization in megacities via transformer-based deep reinforcement learning //International Journal of Geographical Information Science. – 2025. – pp. 1-24.

Davuluri M. Optimizing Supply Chain Efficiency Through Machine Learning-Driven Predictive Analytics //International Meridian Journal. – 2023. – Vol. 5 (5).

Wang K., Fan K., Chen Y. Optimization of Logistics Distribution Centers Based on Economic Efficiency and Sustainability: Data Support from the Hohhot–Baotou–Ordos–Ulanqab Urban Agglomeration //Sustainability (2071-1050). – 2025. – Vol. 17 (7).

Özarık S. S., da Costa P., Florio A. M. Machine learning for data-driven last-mile delivery optimization //Transportation Science. – 2024. – Vol. 58 (1). – pp. 27-44.

Li X. Optimization of logistics flow management through big data analytics for sustainable development and environmental cycles //Soft Computing. – 2024. – Vol. 28 (3). – pp. 2701-2717.

Mandičák T. et al. Supply chain management and big data concept effects on economic sustainability of building design and project planning //Applied Sciences. – 2021. – Vol. 11 (23). https://doi.org/10.3390/app112311512.

Rodríguez-Espíndola O. et al. Humanitarian logistics optimization models: An investigation of decision-maker involvement and directions to promote implementation //Socio-Economic Planning Sciences. – 2023. – Vol. 89. https://doi.org/10.1016/j.seps.2023.101669.

Carnero Quispe M. F. et al. Humanitarian logistics prioritization models: a systematic literature review //Logistics. – 2024. – Vol. 8 (2). https://doi.org/10.3390/logistics8020060.

Alanazi A., Al-Gahtani K., Alsugair A. Framework for smart cost optimization of material logistics in construction road projects //Infrastructures. – 2022. – Vol. 7 (5). https://doi.org/10.3390/infrastructures7050062.

Zdolsek Draksler T., Cimperman M., Obrecht M. Data-driven supply chain operations—the pilot case of postal logistics and the cross-border optimization potential //Sensors. – 2023. – Vol. 23 (3). https://doi.org/10.3390/s23031624.

Tehnički glasnik - Technical journal - Sveučilište Sjever [Electronic resource]. Access mode: https://www.unin.hr/wp-content/uploads/tj_17_2023_3.pdf (date of access: 08/26/2025).

Frederico G. F. From supply chain 4.0 to supply chain 5.0: Findings from a systematic literature review and research directions //Logistics. – 2021. – Vol. 5 (3). https://doi.org/10.3390/logistics5030049.

Tay H. L., Loh H. S. Digital transformations and supply chain management: a Lean Six Sigma perspective //Journal of Asia Business Studies. – 2022. – Vol. 16 (2). – pp. 340-353. https://doi.org/10.1108/JABS-10-2020-0415.

Mastering Telecom Inventory Management: Strategies, Trends, and Optimization for B2B Success [Electronic resource]. Access mode: https://geakminds.com/telecom-inventory-management-system/ (date of access: 08/26/2025).

Profitability Paradox: Streamlined Supply Chains Boost Cost-Efficiency & Revenue Growth [Electronic resource]. Access mode: https://www.nomadstrategies.ca/posts/the-profitability-paradox-how-streamlined-supply-chains-drive-both-cost-efficiency-and-revenue-growth (date of access: 08/26/2025).

Kumari S., Kumar R. Supply Chain Optimization Strategies for Enhanced Efficiency and Performance //IJFMR-International Journal For Multidisciplinary Research. – 2023. – Vol. 5 (4). https://doi.org/10.36948/IJFMR.2023.V05I04.4428.

Denga E. M., Rakshit S. Risks in Supply Chain Logistics: Constraints and Opportunities in North-Eastern Nigeria //International Journal of Risk and Contingency Management (IJRCM). – 2022. – Vol. 11 (1). – pp. 1-18.

Borovkov A. et al. Key barriers of digital transformation of the high-technology manufacturing: An evaluation method //Sustainability. – 2021. – Vol. 13 (20). https://doi.org/10.3390/su132011153.

Wang M., Pan X. Drivers of artificial intelligence and their effects on supply chain resilience and performance: an empirical analysis on an emerging market //Sustainability. – 2022. – Vol. 14 (24). https://doi.org/10.3390/su142416836.

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