Supply Chain Analytics and Data-Driven Decision Making
Supply Chain
What is it?
Supply chain analytics and data-driven decision making involve using data analytics tools and techniques to analyze supply chain data and make informed decisions. This includes predictive analytics, optimization models, and data visualization to identify trends, forecast demand, and optimize supply chain processes. Key aspects include data analysis, predictive modeling, and optimization. Effective supply chain analytics are essential for improving decision-making, reducing costs, and enhancing operational efficiency.
How it works?
Companies engage in supply chain analytics by first collecting and analyzing data from across their supply chain, using analytics tools and techniques to identify trends, forecast demand, and optimize processes. They then use predictive modeling to plan production schedules, optimize inventory levels, and reduce the risk of stockouts or overproduction. Companies focus on using optimization models to identify areas for improvement in supply chain processes, improving efficiency and reducing costs. Supply chain analytics efforts are regularly monitored through metrics such as forecast accuracy, cost savings, and operational efficiency, with adjustments made as needed to optimize performance. The benefits of effective supply chain analytics and data-driven decision making include improved decision-making, reduced costs, and enhanced operational efficiency.
What to watch out for?
Key principles of supply chain analytics and data-driven decision making include data analysis, ensuring that supply chain data is collected, cleaned, and analyzed to identify trends, patterns, and insights that can inform decision-making. Predictive modeling is crucial for using historical data to forecast future demand, optimize inventory levels, and plan production schedules, reducing the risk of stockouts or overproduction. Optimization is important for using analytics to identify areas for improvement in supply chain processes, such as transportation routes, order fulfillment, or supplier selection, improving efficiency and reducing costs. It�s also essential to regularly assess the effectiveness of analytics efforts through metrics such as forecast accuracy, cost savings, and operational efficiency to ensure they contribute positively to supply chain performance.
Suggested services providers
Vendors providing supply chain analytics solutions in Asia include SAP (Global), Oracle (Global), Tableau (Global), and Qlik (Global). These platforms offer tools for data analysis, predictive modeling, and supply chain optimization.
Get INSTANT comprehensive market research of any industry
Chat with AII Consultant Now!
Get INSTANT comprehensive market research of any industry
Chat with AII CHATBOT