Plan, procure, execute, & track transportation for every shipment across your supply chain & logistics operations
A SaaS solution to help grow your business by achieving 100% perfect order execution at high volumes
Increase vehicle capacity utilization and customer promise adherence
Grow your business with omnichannel presence and automated pickups
Consolidate shipments for hub to hub movement across land and air
Real-time customer communications and collect accurate PODs
Orchestrate logistics operations with multiple 3rd party carriers
Achieve cost effective, scalable, sustainable, and customer centric deliveries
Orchestrate all your cross-border logistics operations with ease
Improve address accuracy, ensure first-attempt delivery success, reduce costs and boost customer experience
Gain end-to-end shipment visibility, get proactive alerts, and send customers live tracking links
Grow business in a dynamic world and manage operations across First, Middle & Last mile
Delight customers by seamlessly managing store and online orders across own fleet and 3rd party
Reduce freight costs & get end to end visibility across shipments
According to a study by the Council of Supply Chain Management Professionals, approximately 93% of the shippers and 98% of the third-party logistics companies say that data analytics is important to make smart business decisions. As much as 71% say that implementing big data helped them improve operational efficiency and performance. Well, these statistics are sheer proof that data analytics holds great potential to optimize end-to-end logistics management. It can enhance crucial logistics operations, such as route planning and optimization, delivery scheduling, rider management, and more. Read on to learn how.
By leveraging data analytics, logistics managers can spot the reasons behind the poor delivery performance. For instance, they can figure out the reasons behind delayed deliveries: inefficient routing, unplanned stoppages, unnecessary diversions from the planned delivery routes, etc. Critical insights also enable logistics companies to efficiently manage orders, even during peak hours, festive seasons, or sales. They can get visibility of their own fleet’s future capacity depending on the promised delivery dates. By ensuring maximum utilization of resources, logistics managers can enhance logistics productivity. Using data analytics to optimize own rider and freelance fleet utilization leads to up to 28% cost savings.
Based on critical insights and rider performance data, logistics companies can automatically link the incentivization process. They can also ensure same-day and performance-based fair compensation. Apart from this, businesses can also leverage analytics-powered leaderboards to reward digital medals and badges to delivery executives. Data analytics also helps with gamification to enhance rider engagement.
As much as 85% of the shoppers don’t prefer to buy again from a retailer after one poor delivery experience, which could be a delay in delivery, delivery failure, inaccurate ETAs, or not accommodating customers’ requests. Data analytics enable businesses to suggest delivery time slots by automatically analyzing historical data associated with customers’ availability. It also empowers them to proactively manage deliveries and optimize workflows to ensure on-time deliveries.
Predictive analytics also enable businesses to forecast shipment delays and immediately reorganize supply chains to eliminate the impact of the same. For example, if the software knows in advance that a particular shipment will get delayed, it can immediately inform logistics managers to take corrective measures by assigning the same task/delivery to someone else. It contributes to improving the overall customer experience.
Analytics empowers logistics managers to spot customers with a history of order rejection and implement NDR (non-delivery reasons) verification processes to enhance SLA adherence. For example, any e-commerce company sets a limit on the number of returns for customers. And if any customer exceeds that limit, they have to pay for the next return. NDR management also helps businesses to identify reasons for “failed deliveries”; they can use them to take corrective measures, which avoids the cost of repeated delivery attempts and improves customer experience.
With the help of analytics, businesses can improve inbound, outbound, and backhaul transportation by avoiding non-productive routes. Logistics software with data analytics capabilities offer instant order allocation based on business needs and constraint-based routing for SLA adherences and to ensure productive and cost-efficient deliveries.
Data analytics can do wonders to optimize logistics operations, boost business productivity, reduce shipping costs, and enhance customer experience. Leveraging critical insights, logistics service providers can minimize line haul costs by 12%, enhance customer experience by 28%, improve vehicle capacity utilization by 31%, and improve NPS (net promoter score) by 18%. All it requires is to implement an AI-powered logistics management solution into your existing technology infrastructure. Such solutions equip third-party logistics providers and other businesses with the ability to make informed or data-driven decisions.
