数据分析和报告在现代采购中的作用:加强决策和供应商管理

Victor Ibukun Adebayo, Patience Okpeke Paul, Nsisong Louis Eyo-Udo
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引用次数: 0

摘要

本文探讨了数据分析和报告在现代采购实践中不断演变的作用,强调其对决策和供应商管理的变革性影响。采购工作历来以人工流程为基础,在技术进步的推动下,采购工作已过渡到数据驱动方法。主要方面包括从不同来源收集数据、整合到中央系统,以及应用预测分析和描述性分析等分析技术。这些方法使采购专业人员能够深入了解支出模式,准确预测需求,优化采购战略,并加强与供应商的关系。实时报告在采购决策中的重要性得到了强调,它可以根据对市场条件、供应商绩效和运营指标的最新了解及时做出调整。决策支持系统(DSS)通过综合复杂的数据集、促进情景分析以及推荐最佳成本削减和风险缓解战略,进一步增强了采购经理的能力。供应商管理从数据驱动的方法中获益匪浅,通过数据分析对质量绩效、交付指标和成本竞争力等标准进行严格评估。风险管理战略利用数据来预测和降低与供应商相关的风险,确保供应链运作的连续性和弹性。对未来采购的影响强调了向预测性供应链分析、透明区块链技术、人工智能驱动的自动化、可持续发展倡议和增强型供应商协作平台的持续发展。这些进步将进一步优化采购流程,加强战略合作伙伴关系,并在竞争日益激烈的全球市场中推动可持续的业务实践。关键词 数据分析、报告、采购、决策、供应商管理。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The role of data analysis and reporting in modern procurement: Enhancing decision-making and supplier management
This paper explores the evolving role of data analysis and reporting in modern procurement practices, emphasizing their transformative impact on decision-making and supplier management. Historically rooted in manual processes, procurement has transitioned to data-driven methodologies propelled by technological advancements. Key aspects include data collection from diverse sources, integration into centralized systems, and application of analytical techniques such as predictive analytics and descriptive analytics. These methodologies enable procurement professionals to gain insights into spending patterns, forecast demand accurately, optimize procurement strategies, and enhance supplier relationships. The importance of real-time reporting in procurement decision-making is highlighted, enabling timely adjustments based on up-to-date insights into market conditions, supplier performance, and operational metrics. Decision Support Systems (DSS) further empower procurement managers by synthesizing complex data sets, facilitating scenario analysis, and recommending optimal cost reduction and risk mitigation strategies. Supplier management benefits significantly from data-driven approaches, with criteria like quality performance, delivery metrics, and cost competitiveness being rigorously evaluated through data analysis. Risk management strategies leverage data to anticipate and mitigate supplier-related risks, ensuring continuity and resilience in supply chain operations. The implications for the future of procurement underscore the continued evolution towards predictive supply chain analytics, blockchain technology for transparency, AI-driven automation, sustainability initiatives, and enhanced supplier collaboration platforms. These advancements will further optimize procurement processes, strengthen strategic partnerships, and drive sustainable business practices in an increasingly competitive global market. Keywords:  Data Analysis, Reporting, Procurement, Decision-Making, Supplier Management.
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