Application Of Big Data To Predict Future Demand Forecasting In Supply Chain Management
Supply chain management, Applications, Tools , Software , Technologies , RFID , GPS, ERP, WMS, TMS, Lean, Six Sigma ,Planning, Execution ,Monitoring, Optimization, Customer satisfaction , Competative.
This review examines the paper "Application of big data to predict future demand forecasting in supply chain management.” In Supply Chain Management (SCM), when we talk about "application," we're referring to using different tools, software, ways of doing things, and smart strategies to make the whole supply chain work better. For example, technologies like RFID and GPS help us keep track of things in real time, so we can see where our stuff is and avoid delays. Special software, such as ERP, WMS, and TMS, helps organize our business processes and handle things like inventory and transportation more efficiently. Approaches like Lean and Six Sigma are methods we use to reduce waste and make things run smoother. Big plans, like making our supply chain respond to what customers want, are part of our strategies. Good planning, using tools and smart calculations, helps us forecast, schedule, and manage our stock better. Doing things, like buying, making, and delivering products, is the execution part, where we might use robots and automation to be faster and more accurate. Checking on everything as it happens (monitoring) helps us catch and fix problems quickly. Always trying to do better (optimization) is like fine-tuning our processes using data and smart technology. By using all these tools and methods, companies aim to have a supply chain that's flexible, quick, and cost-effective, making customers happy and staying competitive.
"Application Of Big Data To Predict Future Demand Forecasting In Supply Chain Management", IJSDR - International Journal of Scientific Development and Research (www.IJSDR.org), ISSN:2455-2631, Vol.9, Issue 1, page no.31 - 35, January-2024, Available :https://ijsdr.org/papers/IJSDR2401004.pdf
Volume 9
Issue 1,
January-2024
Pages : 31 - 35
Paper Reg. ID: IJSDR_209736
Published Paper Id: IJSDR2401004
Downloads: 000347213
Research Area: Information Technology
Country: Palghar, Maharashtra, India
ISSN: 2455-2631 | IMPACT FACTOR: 9.15 Calculated By Google Scholar | ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 9.15 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
Publisher: IJSDR(IJ Publication) Janvi Wave
