The Influence of Big Data Analytics on the Supply Chain:
Leveraging various tools, algorithms, and processing systems, big data analytics extracts important information from structured and unstructured data in real-time. The data is categorized based on its volume, velocity, and variety, enabling effective analysis throughout the supply chain. Let’s explore the role of big data analytics in each phase of the supply chain:
Big data analytics enhances forecasting accuracy by integrating data from the entire supply chain. This approach enables better inventory management and proactive planning for replenishment, reducing the occurrence of stock-outs. By considering market trends, competitive data, and real-time information, organizations can make more accurate predictions and improve their planning processes.
Big data analytics improves purchase coordination, leading to significant cost reductions. Regularly assessing supplier performance using supply chain analysis helps organizations identify potential issues in advance and establish proactive solutions. Real-time data from suppliers enables better decision making and reduces costs associated with data acquisition.
Big data analytics optimizes resource utilization, including human resources, tools, and space, to maximize productivity. Internet of Things (IoT) sensors play a crucial role in increasing production capacity and asset performance. By forecasting potential issues, organizations can proactively address them and improve overall efficiency.