The Role of Big Data Analytics in revolutionizing global supply chain
In the past few years, the advancement of technology has affected all aspects of life. From health to education and supply chain management, technological advancement not only improved overall functionality but boosted productivity as well.
Big data analytics is one of the emerging technologies in supply chain management. It plays an important role in each step of supply chain management. Starting from strategic planning of the supply chain to operations and customer services, big data analytics acts as a catalyst and works great in overcoming various challenges of supply chain management.
As per the SCM world report, about 64% of supply chain executives considered big data analytics as an important tool and plan to include it as the long-term supply chain management of their organizations.
What is big data analytics?
Supply chain analytics involve extracting and presenting supply chain information to facilitate measurement, monitoring, forecasting, and management. Big Data analytics can sift through vast amounts of data to make better data–driven decisions. This is a great tool for businesses to reduce costs and improve overall operational efficiency.
Big Data is a great tool in the arsenal of a seasoned supply chain manager, a freight forwarder, shipping and airline companies and big enterprises that have global businesses and supply chain networks. The capability of the technology to manage vast amounts of data and infer important cues makes it so important in today’s day and age.
The Role of big data analytics in revolutionizing supply chain management globally
Improve product visibility
Product visibility is one of the important aspects of improving customer experience in the supply chain flow. The RFID tags on ordered products improve traceability. Big data analytics can be used to analyse real time tracking of order and its status at multiple locations. This impacts the overall customer experience. Such data is also helpful in taking quick decisions in unpredictable situations.
Reduce the order to delivery time and improve the overall efficiency
In today's fast-paced world, delayed deliveries directly impact a freight forwarder's reputation. Big data analytics help in identifying patterns, improving the delivery system’s efficiency, unravel possibilities/ disruptions to help the freight forwarder be better prepared.
Help in maintaining fluctuating product demand
Consumer behavior changes from time to time and results in fluctuating product demands. Manufacturers and suppliers need to adjust product demands without disrupting the supply chain process. Big data analytics provide quick updates and minute details to operational managers. It helps in better inventory management and helps business be resilient to fluctuating product demand, keeping the customers satisfied despite changing trends or product demands.
Play a vital role in smart inventory management
Inventory management is one of the most important parts of supply chain management. With big data analytics, the business management team gets quick updates on fluctuating product demands, stock availability and any other loopholes like slower order fulfilment etc. that are present in supply chain management. This real-time data helps the operational team plan better, pivot quickly to stay ahead of time.
Help e-commerce businesses improve their management process
With big data analytics, e-commerce businesses can predict product/raw material delivery time, maintain product stock availability and can improve their management process while staying lean on resources.
Reduced the overall cost of production
Big data analytics provide businesses with a deep insight into each aspect of product production. Starting from analyzing customer behavior to delivering the product, big data analytics generates databases and helps businesses in taking data-driven decisions which reduce the overall cost of production, reduce financial loss and improve business profitability.
Improve customer satisfaction
Big data analytics work at various levels of supply chain management and help in improving various aspects of delivering a product. Thus, improving customer satisfaction and retention.
Best Practices for incorporating Big Data Analytics in Logistics
Starting with a pilot project can help to identify potential issues and demonstrate the value of big data analytics to stakeholders. Setting clear goals and key performance indicators (KPIs) is also important to measure the success of the project.
Involve stakeholders from different departments to ensure that the project aligns with the company's overall strategy and addresses the needs of all stakeholders. Successful examples of big data analytics implementation in logistics include companies like DHL and UPS, who have invested in data-driven decision-making and analytics-driven operations to improve their supply chain management.
Big data analytics is the future of supply chain management. As of now, not too many companies are using it to the fullest. Big Data is a potent combination of speed and accuracy, helping seasoned supply chain experts unearth crucial pieces of informations and patterns that can save businesses huge costs in the long run. We believe this is one technology that a supply chain expert should master to achieve optimum performance.