Using Data Analytics to Streamline Supply Chain and Resource Management in Enterprises

  • Authors

    • Białek-Jaworska Anna Associate Professor, Department of Management and Information Technology, University of Warsawz, Poland. Author

    DOI:

    https://doi.org/10.67228/30713498/IJADSMC-2019PI6B2F

    Published 09-04-2019

  • Data Analytics, Supply Chain Management, Resource Management, Predictive Analytics, Inventory Optimization, Machine Learning, Artificial Intelligence, Big Data, Internet of Things (IoT), Blockchain Technology, Operational Efficiency, Demand Forecasting, Logistics Optimization, Supply Chain Automation, Enterprise Resource Planning (ERP)

    Issue

    Vol. 2 No. 2 (2019)

    Section

    Articles

    How to Cite

    [1]
    B.-J. Anna, “Using Data Analytics to Streamline Supply Chain and Resource Management in Enterprises”, IJADSMC, vol. 2, no. 2, pp. 01–17, Sep. 2019, doi: 10.67228/30713498/IJADSMC-2019PI6B2F.

  • Abstract

    In today’s rapidly evolving business landscape, the efficient management of supply chains and resources is paramount for ensuring competitiveness and sustainability. Data analytics has emerged as a transformative tool, enabling enterprises to make informed decisions, optimize operations, and achieve greater cost-efficiency. This paper explores the role of data analytics in streamlining supply chain and resource management, highlighting the key technologies such as big data, machine learning, artificial intelligence, and the Internet of Things (IoT). By leveraging advanced data-driven techniques, businesses can improve demand forecasting, inventory management, and logistics while reducing operational costs. However, challenges such as data privacy concerns, high implementation costs, and the need for skilled personnel must be addressed to fully realize the potential of these technologies. Through a series of case studies, this paper also demonstrates the successful application of data analytics by leading enterprises. The future of supply chain and resource management lies in the integration of innovative data analytics tools that will drive sustainability, operational efficiency, and enhanced customer satisfaction.

  • References

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