Agile, IoT, and AI: Revolutionizing Warehouse Tracking and Inventory Management in Supply Chain Operations

Authors

  • Wazahat Ahmed Chowdhury Master in Supply Chain Management, College of Business, University of Michigan, Ann Arbor, Michigan, United States.

DOI:

https://doi.org/10.58425/jpscm.v4i1.349

Keywords:

Agile methodologies, internet of things (IoT), artificial intelligence (AI), supply chain operations, warehouse tracking, inventory management, predictive analytics, real-time data, operational efficiency, scrum

Abstract

Aim: The way traditional supply chains operate has shown limited success in coping with changes in supply chain requirements related to inventory tracking and warehouse management. The research evaluates the collaborative effects of Agile methods with IoT devices and AI capabilities to optimize these processes.

Methods: This study examines three vital aspects of data science deployment within a consumer product distribution company that uses IoT sensors (RFID tags and Texas Instruments CC2650) for real-time data combined with AI analytics (Random Forest and reinforcement learning in Python) through an Agile (2-week cycles via Jira) deployment approach for inventory management. A twelve-month project employs AI modeling based on Python and utilizes Scrum sprints as its methodology.

Results: The systematic study produced three significant results which include a 25% higher inventory turnover rate, 20% fewer tracking errors, and 15% lower operating costs. Strong solutions emerge from the combination of Agile with IoT and AI and demonstrate promising capabilities for enhancing supply chain resilience at a large-scale level.

Conclusion: Practical applications from the research follow some practical suggestions and directions for upcoming scientific investigations into blockchain technology implementation.

Recommendation: The research presents real-world implications for medium firms and recommendations for blockchain-based secure data-sharing studies to advance supply chain functions.

References

Atzori, L., Iera, A., & Morabito, G. (2010). The Internet of Things: A survey. Computer Networks, 54(15), 2787–2805. https://doi.org/10.1016/j.comnet.2010.05.010

Beck, K., Beedle, M., van Bennekum, A., Cockburn, A., Cunningham, W., Fowler, M., Grenning, J., Highsmith, J., Hunt, A., Jeffries, R., Kern, J., Marick, B., Martin, R. C., Mellor, S., Schwaber, K., Sutherland, J., & Thomas, D. (2001). Manifesto for Agile software development. Agile Alliance. https://agilemanifesto.org

Boute, R. N., & Van Mieghem, J. A. (2021). Digital operations management. Management Science, 67(9), 5345–5368. https://doi.org/10.1287/mnsc.2020.3877

Chopra, S., & Meindl, P. (2016). Supply chain management: Strategy, planning, and operation (6th ed.). Pearson.

Conforto, E. C., Salum, F., Amaral, D. C., da Silva, S. L., & de Almeida, L. F. M. (2014). Agile project management in non-software contexts. Project Management Journal, 45(3), 19–34. https://doi.org/10.1002/pmj.21414

DHL Trend Research. (2020). Artificial intelligence in logistics. DHL Customer Solutions & Innovation. https://www.dhl.com/global-en/home/insights-and-innovation.html

Fawcett, S. E., Wallin, C., Allred, C., & Magnan, G. (2011). Information technology in supply chain collaboration. Supply Chain Management: An International Journal, 16(2), 87–98. https://doi.org/10.1108/13598541111115349

Gunasekaran, A., Subramanian, N., & Papadopoulos, T. (2017). Big data analytics in logistics. International Journal of Production Economics, 187, 98–110. https://doi.org/10.1016/j.ijpe.2017.02.008

Ivanov, D., Dolgui, A., & Sokolov, B. (2019). Digital technology in supply chain management. International Journal of Production Research, 57(3), 829–846. https://doi.org/10.1080/00207543.2018.1445910

Lee, C., Zhang, S., & Ng, K. K. H. (2021). Machine learning in supply chain forecasting. Journal of Supply Chain Management, 57(2), 45–60. https://doi.org/10.1111/jscm.12241

Lee, H. L., Padmanabhan, V., & Whang, S. (1997). The bullwhip effect in supply chains. Sloan Management Review, 38(3), 93–102.

McKinnon, A., Browne, M., Whiting, A., & Piecyk, M. (Eds.). (2015). Green logistics (3rd ed.). Kogan Page.

Rushton, A., Croucher, P., & Baker, P. (2017). The handbook of logistics and distribution management (6th ed.). Kogan Page.

Sanders, N. R. (2018). Supply chain management: A global perspective (2nd ed.). Wiley.

Downloads

Published

2025-05-03

How to Cite

Chowdhury, W. A. (2025). Agile, IoT, and AI: Revolutionizing Warehouse Tracking and Inventory Management in Supply Chain Operations. Journal of Procurement and Supply Chain Management, 4(1), 41–47. https://doi.org/10.58425/jpscm.v4i1.349