Risk Mitigation Through Data Analytics: A Proactive Approach to Sourcing

Paper ID: EIJTEM_2023_10_4_159-170

Author's Name: Lakshmi Narasimha Raju Mudunuri

Volume: 10

Issue: 4

Year: 2023

Page No: 159-170

Abstract:

Processes in sourcing supply chain management exist within a changing environment of risks, ranging from economic uncertainty to global dislocation. Traditional risk management approaches that predict or mitigate these complexities must be revised, leaving organizations susceptible to unforeseen losses, escalating operational delays, and reputational damage. The technological advances in data analytics offer an opportunity for transformation, an approach from reactive to proactive risk management for organizations. Advanced techniques such as machine learning, natural language processing, and predictive modelling can use large volumes of data. With such approaches, hidden vulnerabilities within the companies, possible disruptions, and optimal sourcing strategies would be revealed. This paper discovers data analytics's multifaceted role in enhancing sourcing strategies: identification, predictive measures for possible disruptions, and providing mitigation. It further explores the frameworks, methodologies, and tools involved in such an analytics-intensive approach, supported by case studies and data analysis. The paper also identifies challenges like data quality, system integration, and workforce readiness that an organization must tackle to realize the true promise of analytics in risk mitigation. This study provides a comprehensive guide to industry practitioners and academia interested in using data analytics to build more resilient sourcing processes.

Keywords: Risk Mitigation, Data Analytics, Sourcing

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