Samir Lambay, CEO and Co-Founder of FreightCrate TechnologiesSamir Lambay, CEO and Co-Founder of FreightCrate Technologies
Driven by exponential demands, especially with the rise of e-commerce and digitally empowered consumers, the need for efficient and cost-effective supply chain management is becoming even more vital. New age logistics is thus turning to big data and analytics to handle the huge scale of operations and build a transparent and automated system.Modern logistics is a complicated process with critical aspects catering to global consumers through efficient and cost-effective supply chain management, facilitating timely last mile delivery and customer satisfaction. Technological advances in data and with devices such as GPS, RFID tags, sensors and scanners have warranted a shift in the logistics business model, helping to fuse multiple data sources and assisting in complex calculations to provide real-time or near real-time insights for timely decision making.

Increase Efficiency

With Big Data Analytics, the Logistic service providers can gain end-to-end visibility of the supply chain and monitor prospective loss of revenues and profits that could occur at various points in the chain. The process also facilitates in increasing asset uptime, expand reach, enables preventive maintenance of assets, resource optimization, and conducts real-time supply planning using dynamic data feeds. This clear visibility ensures better operational planning, resulting in enhanced service and increased efficiency for the customers.

Real-Time Tracking and Order Management

Managing multiple international shipments via different transport modes using multiple freight forwarders can be a daunting task. As a result, even when dealing with the best of freight forwarders, businesses miss out on vital information required to track progress of the shipment, often being rudely surprised with delays and penalties. New age logistics platforms offer a single shipment management dashboard with real-time tracking for multiple shipments. This is helping create a reliable and trusted ecosystem for clients and logistics service providers. Leveraging big data and using predictive analysis allows service providers to optimize route selection and proactively avoid shipment delays and exceptions.

Builds Transparency

Data analytics can be of vital assistance when managing complex supply chains. Leveraging data to map the product’s journey across the supply chain can help reveal the shipments’ true origin and touchpoints on an open, easily accessible platform. Further, it also assists in accurate documentation, controlling costs incurred due to delays and penalties and inaccurate customs documents. The use of big data thus facilitates transparency, allowing customers, OEMs and regulators have access to relevant logs and data.

Forecasting

Leveraging data analytics, logistics service providers can help clients cut logistics expenses through effective forecasting. With intelligent insights into data related to past shipments, frequent destinations, frequently used international freight forwarders, preferred mode of transport, average delivery times, average freight costs per shipment, weight/ volume of shipments, and type of material etc., modern logistics service providers can facilitate customers in acquiring lower rates for future shipments. The data driven approach also helps eliminate variability and helps customers procure accurate and transparent charges with little scope of additional/ hidden costs.

Smart Consolidation

Consolidation of shipments through centralised warehouses is a trend that is helping shape the organised logistics framework for retailers. With the help of Data Analytics, organised logistics service providers can help reduce shipment costs through bulk volume discounts, cut down other ancillary charges like customs fee and documentation charges (which could have been higher for individual shipments), and facilitate better order management and timely delivery. For example, the free flow of goods across the European Union can be leveraged to create a centralised hub for shipping to international destinations. Shipments from all over the continent can be clubbed together on basis of their destination, and shipped from a single port, thus creating an organised logistics system.

Network Optimization Model

With the presence of exponential variables and dynamic scenarios, logistics service providers can leverage data analytics to integrate intelligent insights with other interconnected business systems. Analytics on warehouse layout, product inventory and demand can, for example, help optimize operations within the warehouse, also enabling alerts on depleted inventory or potential roadblocks. Similarly, by integrating data from weather and environment forecast agencies, local news and port updates as well as insights into specific industry related policy changes that can impact logistics costs and customs fee, etc., it is possible to receive real-time insights and take prompt action to ensure smooth and efficient delivery of the shipments.

E-commerce – the biggest driver of predictive and data analytics for logistics in India

The e-commerce boom has spawned the need for data analytics in logistics, especially in Last Mile Delivery services, where predictive analytics is employed in gathering real-time data for route optimization or re-routing. From measuring the pulse of how the supply chain is performing to optimizing logistics costs and significantly shortening order length cycle, analytics is driving operational excellence in three big ways:
  • Getting to market faster: Dynamic, automated real time tracking in networks for route optimization
  • Forecasting analysis: Helps in responding to changes at a short notice
  • Increased transparency across supply chain: Customers can track ETAs
Usage of big data and advanced analytics to simplify distribution networks also helps logistic companies acquire savings that range from 10 to 20 percent of freight and warehousing costs, shortened order-to-delivery cycle time and improved cost of service.
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