From traditional supply chain execution systems with multiple employees performing their specific role in the process to big data, supply chains have undergone drastic changes with the proliferation of technologies, computer networks, and internet tools. In this competitive age, supplier networks need contextual intelligence to compete on accuracy, speed, and quality, which arenot possible with legacy enterprise resource planning (ERP) and supply chain management (SCM) systems. Big data provides supplier networks precise and accurate data and greater insights, leading to the flow of more contextual intelligence across supply chains. Big data and cloud-based technologies enable manufacturers to look beyond the constraints of legacy ERP and SCM systems.

Real-Time, Contextual Data Help Strategic Supply Chain Management

Soon contextual information in the form of real-time data streams, like weather data and Twitter feeds, will be used to predict the status of orders more accurately than before. These predictions will allow decision makers to better manage their supply chains, prevent delays, and mitigate risks. Firms that can aggregate, filter, and analyze internal and hybrid data will derive the benefits of the insights for a better decision-making at all levels of the supply chain.

This is why companies that have already integrated big data into their supply chains will have a competitive advantage over those that haven’t done so.

How is big data/real-time data helping supply chain management? 

  • Knowledge-sharing networks can be created only on the insights gained from big data analytics. Big data is revolutionizing how supplier networks form, grow, proliferate into new markets, and mature over time.
  • Geoanalytics based on big data can help plan the merger of several delivery networks.
  • According to a study, integration of big data analytics in operations leads to a 4.25x improvement in order-to-cycle delivery times and a 2.6x improvement in supply chain efficiency of 10% or greater. The study also found that embedding big data into supply chain operations accelerates supply chain processes a minimum of 1.3x over using big data on an ad hoc basis.
  • Financial outcomes of supply chain decisions can be measured with big data app integration in financial systems and is quite effective in industries with rapid inventory turns.
  • Big data provides improved traceability performance and reduces the man-hours lost in trying to access, integrate, and manage product databases to facilitate recall or retrofit of products.
  • Internet of Things (IoT) is set to transform the supply chain industry. IoT will influence productivity and efficiency improvements in all spheres of predictive maintenance and quality control to warehouse, fleet, and inventory management. Sensor networks, intelligent accounting, and RFID will play a greater role in optimization and planning in all areas. Manufacturers and distribution centers will be able to link their operations with real-life happening in-store and improve their goods shipments and processes accordingly.
  • Implementation of the Collaborative Planning, Forecasting, and Replenishment (CPFR) method with key suppliers would enable a business to cater to the JIT (Just-In-Time) order without any element of surprise.
  • According to various studies, web-based inventory solutions improve the visibility of inventory across the supply chain and reduces inventory by approximately 20%.
  • Improved visibility on material scheduling helps in reducing inventory build-up to the tune of 6 – 8%.
  • The prescriptive approach based on the processing of hybrid data helps in formulating an optimal course of action in real time.

An effective supply chain management based on big, real-time, contextual data will not only revolutionize supplier chain but will also enhance customer responsiveness, reduce inventory, lower costs, improve agility, and maximizes the profit of the organization.