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
Big data is revolutionizing almost every sector, and logistics is no exception. The complex and dynamic nature of the industry, the involvement of various stakeholders, and changing delivery trends demand logistics leaders to make data-backed decisions to improve business profitability and customer experience. That’s why the idea of implementing big data analytics in logistics and supply chain management is changing from a “nice-to-have” to a “must-have.
According to the research and markets, the supply chain big data analytics market is expected to reach $9.28 billion by 2026. From route optimization, tracking shipments, and warehouse management, to network and capacity planning, there are various use cases of big data analytics in the supply chain.
Most logistics service providers have already invested in logistics solutions powered by big data; however, only a few are using this technology to its full potential. To make the most of this technology, it is important to consider a few things that have been mentioned below:
Big data analytics examines big data to extract useful information, such as market trends, consumer preferences, hidden patterns, and more. The analytics help to make data-driven decisions. However, if the data source is not right, the output will not be constructive. So whether it is mobile apps, cloud apps, survey responses, or social media, make sure it is the right data source.
Data silos hinder business growth; therefore, it is important to make an orchestrated ecosystem of platforms that captures siloed data from different sources. To understand how data silos impact business success, let’s take an example. A customer support team in a company has data on the current and upcoming customers’ requests.
On the other hand, the marketing team has data on customers’ shopping habits. In order to make effective marketing strategies, it is important to collect and combine the data that both teams have. A developed ecosystem will automatically collect the siloed data to process and find useful information from it.
Data is a raw form of information, and to make the most out of the data, it is critical to clean, aggregate, and preprocess it before considering it for a particular use case. For instance, to use big data analytics for route optimization or warehouse management, the data collected from various sources need to be cleaned and preprocessed. To perform all these three operations on the data, logistics leaders can leverage data science, machine learning, and other top-notch technologies.
Visualizing insights in the form of graphs or charts can help logistics companies to understand hidden patterns or market trends easily. These insights enable logistics leaders to make data-driven decisions to improve logistics processes. They can also leverage insights to understand customer behavior and shopping pattern to prepare inventories and make delivery management strategies.
Big data analytics is a boon for the logistics and supply chain industry. It empowers logistics leaders to have useful insights to revamp their logistics strategies and increase efficiency, mainly within logistics networks and distribution. The technology can also be useful for comprehending delivery trends and customer demands while planning logistics strategies. It enables logistics managers to improve customer experience by analyzing data gathered from various online surveys, delivery feedback, social media, and other sources.
Big data analytics plays a pivotal role in route optimization; it uses shipment data, real-time weather and traffic data, and delivery sequences to optimize delivery routes. Similarly, it also enables logistics leaders to go beyond traditional track and trace practices and have a whole new level of visibility. Big data analytics leverages GPS devices, RFID sensors, and bar codes to capture the data and enable stakeholders can track their packages in real-time.
Apart from deliveries, big data analytics can also help with warehouse management by providing logistics managers with minute-by-minute updates on the stock availability and maintenance of goods. To make the most of this technology, courier service providers can implement logistics management solutions powered by artificial intelligence, machine learning, big data, and other top technologies.
Most of these solutions are customizable and scalable to meet specific business requirements. Besides, they can be seamlessly integrated with existing WMS/ERP/OMS, which means no additional hassle of writing codes to use the solution.
Technologies such as IoT make the most of available data and provide a broader view that can help improve the way a company performs and manages its logistics operations.
The international logistics market is expected to grow at a CAGR of 11.71% and reach the USD 55.47 bn mark by 2026. Here are five core transformation trends playing a crucial role in this growth.
