Management and Economics
| Open Access |
DOI: Methodologies for Cost Reduction and Profitability Enhancement in Industrial Procurement
Daniyar Jailaubayev , CEO of "System Integrator Project LLP"Charlotte, USA)Abstract
The article reviews a comprehensive set of methodologies for cost minimization and profit maximization in industrial procurement within the oil and gas value chain amidst “dual margin compression.” Geopolitical volatility, logistical disruptions, and tightening ESG regulations express dual margin compression. The purpose here is to evidence and synthesize managerial and digital tools that are integrated to a level high enough to reposition the procurement function from mere transaction processing to adding strategic value for driving sustainable margins. It will do this by demonstrating how procurement’s increasing share in the CAPEX/OPEX structure makes it relevant due to its vulnerability toward external shocks on price levels and delivery times. A cross-segmental comparative analysis of practices between the Upstream/Midstream/Downstream segments forms part of this study, together with a systematic review on how external factors (geopolitics, logistics, climate regulation) influence supply cost and content analysis regarding digital transformation strategies (e-Procurement, machine learning, distributed ledgers). Core findings are that the combination of category management, the TCO approach, and e-Procurement platforms infused with ML algorithms for deep item segmentation and traceability on the blockchain sustain reductions in transactional and logistics costs plus working capital available; VMI/consignment models together with local additive manufacturing eliminate shortages as well as lead times on critical items; digital twin-based predictive maintenance eliminates downtime while keeping cash flows steady. The long-term reproducibility of the effect is achieved when KPI are simultaneously shifted toward the life cycle and data quality, pilot waves are launched with measurable metrics, a competence center is established, and the cybersecurity of the digital supply ecosystem is strengthened. The novelty of this study lies in the author’s integrated framework that combines category management, TCO-based decision-making, and advanced digital technologies (AI-driven procurement, blockchain traceability, and digital twins) into a unified organizational model. This framework represents an original contribution of major significance to the oil and gas industry, enabling corporations to sustain profitability under conditions of geopolitical turbulence and energy transition. This article will be of interest to Heads of Procurement and Supply Chains, COO and CFO, EPC Project Leaders, and Risk & Compliance Specialists in the Oil & Gas Industry.
Keywords
industrial procurement, oil and gas industry, category management, total cost of ownership (TCO), e-Procurement, machine learning, digital twins, predictive maintenance
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Copyright (c) 2025 Daniyar Jailaubayev
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