How Real-time Data Analytics is used to Navigate Global Supply Chain Issues

There’s no question that high-quality, actionable data has become one of the most valuable commodities wielded by organizations in the modern world. With the global economy more connected than ever before, and entire industries now heavily reliant on international trade partnerships to secure essential resources, the global supply chain must function efficiently. 

In an ideal world, there would be a margin of error present to shield international businesses from unexpected turbulence and potential oversights in logistics management. However, as recent world events have illustrated, unforeseen economic and political instability can quickly derail supposedly stable supply chains, negatively impacting both businesses and consumers. 

For enterprise-level organizations to mitigate these concerns, leaders must be well-positioned to accurately predict and analyze expected demand, resource availability, inventory management and several wider aspects of commercial logistics, enabling teams to optimize and adjust core processes in line with market instability. With modern smart technology software, these pursuits are possible, this is how real-time data analytics is used to navigate global supply chain issues. 

Real-time Data and Decision-making

The importance of real-time data analytics with regards to effective supply chain management is clearly illustrated by the potential for businesses to make informed decisions both efficiently and accurately. By designing systems positioned to monitor live data from multiple sources, leaders gain high quality insights into the demand for various materials to improve forecasting accuracy.

For example, rather than simply committing to repeat orders based only on historic demand and intuition, businesses can assess both the current availability of select resources and a range of wider logistical considerations, like disruptions to transport networks, that may impact fulfillment. 

As this data is collected and analyzed in real-time, teams are able to freely adjust key processes in line with sudden fluctuations across the supply chain, meaning informed decisions regarding resource procurement and inventory management can be made quickly to help organizations avoid incurring unwanted additional costs.

Increased Inventory Visibility

Real-time data analytics is also essential in helping enterprise-level organizations gain a more accurate picture of stored inventory, with one study finding almost 70% of organizations desire better visibility over procurement functions, the adoption of data analytics systems will likely rise.  Modern inventory management systems are designed to scan all raw materials and saleable inventory as soon as these resources enter manufacturing or warehouse facilities, providing teams with accurate stock levels used to inform wider operations.

Serial number tracking systems will typically be deployed to monitor specific resources as they travel throughout the supply chain, automatically updating inventory management systems as each product reaches a new location. Implementing such a system ensures that businesses are  always able to reference accurate records when evaluating responses to supply chain issues.

In addition, by providing teams with real-time data pertaining to held inventory, admins are able to accurately identify suspected bottlenecks and inefficiencies present in existing supply chains. Analysis of this data enables management staff to address such issues immediately, and enact proactive solutions to ongoing problems before possible repercussions affect related processes.

Enhanced Logistics and Navigation Capabilities 

Recent global supply chain issues have been caused, in part, by limitations placed on air freight transportation alongside disruptions to typically stable rail and shipping routes. These logistical issues can lead to businesses experiencing significant delays and backlogs in order fulfillment processes, potentially leading to consignments becoming lost or perishable items being wasted.

Many of these issues can be appropriately addressed with support from real-time data analytics provided by RFID and NFC cargo tracking systems. RFID or NFC tags are attached to individual items to present management teams with accurate real-time location data, enabling businesses to monitor the status of shipped cargo to ensure backlogged goods are appropriately monitored.

By analyzing real-time location data, teams make sure that items experiencing shipping delays remain accounted for, and that customers waiting for orders are updated when circumstances change. In addition, teams can assess whether any delayed consignments can be reallocated to alternative routes in relation to their location, potentially easing congestion along specific routes.

Conclusion

As the global supply chain continues to be impacted by a variety of ongoing economic and political factors, the importance of accurate real-time data analytics deployed within inventory management and order fulfillment processes will continue to rise. For international businesses to reliably navigate unpredictable markets, high-quality insights will almost certainly be required.

By developing multifaceted management systems designed to monitor and analyze information collected from multiple points within the supply chain, businesses are better positioned to adapt to uncertainty, enabling leaders to enact proactive solutions to seemingly complicated problems.

With more visibility over both raw materials and saleable inventory, resource procurement and allocation processes can be adjusted with precision and accuracy, helping organizations avoid incurring unexpected costs. Real-time data analytics enables businesses to not only respond to novel risks, but predict incoming threats accurately, mitigating the impact of supply chain issues.