Basic overview of data analytics in supply chain

Why data analytics is important in Supply Chain?

Data is important to businesses in formulating strategies, streamlining operations, introducing new products and services, and ensuring customer satisfaction. But data alone isn’t much good unless it’s analyzed, understood, and acted upon. Data analysis is benefiting from new technology tools by allowing analysts to dig more deeply into supply chains. At the same time, human judgment remains the most important element in the analysis. Data is defined as facts, figures, or information that are stored in a variety of places such as invoices, contracts, and bills of lading. By collecting data, a business can improve shipment transparency, visibility, operational efficiency, and products and services. All of which attracts more users. Transparency and visibility are crucial, particularly if something goes wrong while shipments are in transit. By utilizing data, a split-second decision doesn’t have to make without adequate support. Transparency and visibility are also important when reviewing invoices and contracts with supply-chain partners. Despite good intentions, hidden costs can occur. They usually come in the form of surcharges such as extra delivery-area fees, additional handling, and fuel.. Consumption rates and inventory levels are among the data points critical to proper inventory planning and development.