{"id":22987,"date":"2023-10-13T18:29:03","date_gmt":"2023-10-13T18:29:03","guid":{"rendered":"https:\/\/corporate.nvisionglobal.com\/?p=22987"},"modified":"2023-12-11T10:03:39","modified_gmt":"2023-12-11T10:03:39","slug":"how-data-analytics-is-transforming-logistics-and-supply-chain-management","status":"publish","type":"post","link":"https:\/\/corporate.nvisionglobal.com\/how-data-analytics-is-transforming-logistics-and-supply-chain-management\/","title":{"rendered":"How Data Analytics Is Transforming Logistics and Supply Chain Management"},"content":{"rendered":"

\"\"<\/p>\n

As supply chains become increasingly complex and global disruptions persist, data analytics is becoming more essential for effective supply chain management. By using data analytics to gain insights into their operations, companies can improve efficiency, reduce costs, and improve customer service.<\/p>\n

But simply having data isn\u2019t enough. For a transformative, innovative approach to supply chain management, organizations must make data accessible, trustworthy, and actionable.<\/p>\n

Supply Chain Analytics<\/h2>\n

Realizing the significance of data analytics for supply chain management first requires an understanding of what it is and where the data comes from. Supply chain data analytics encompasses the collection, processing, and analysis of various data types. This data often includes sales data, inventory levels, transportation data, and more. Data streams in from different points in the supply chain and across numerous points in the chain of custody from suppliers, manufacturers, distributors, retailers, and transport and logistics partners.<\/p>\n

It\u2019s important to analyze data from multiple capture vehicles, such as a transportation management system (TMS)<\/a> or warehouse management system (WMS). These systems provide real-time insights into the movement of goods, inventory levels, and the efficiency of processes within the supply chain. In turn, this allows you to make data-driven decisions.<\/p>\n

Organizations use supply chain data for several purposes. For example, you can use your data to optimize inventory management, transportation routes, warehousing processes, and other systems. As a result, you\u2019ll make smarter, more informed decisions to improve your overall supply chain performance.<\/p>\n

Examples of Data Analytics at Work<\/h2>\n

What can data analytics do to help you meet operational key performance indicators? Here\u2019s how crunching the numbers and actioning the data can make a difference in logistics and supply chain management:<\/p>\n