How Trending Technologies Can Improve Your Logistics Services

In today’s world, adopting new technologies can improve the efficiency of your logistical services. Some of these cutting-edge technologies include drones, artificial intelligence, blockchain and data science. When choosing a supply chain management solution, look for a customized solution for your company. As no two companies have the same market or product, a pre-built logistics solution will not help you. Instead, find a solution tailored for your industry, and you’ll be on your way to improving productivity.

Connected technology

The logistics industry is one of the first industries to use Internet of Things (IoT) technology. It helps logistics companies integrate all aspects of the business and digitize the supply chain. With IoT, companies can collect data from all physical items and use that information to make better decisions and improve their services. This can change everything from the way you do business to your go-to-market strategy. In addition to improving your logistics services, IoT will improve the experience for the shipper.

IoT-powered trucks will provide you with real-time information on fuel usage, vehicle location, and more. Using this data, fleet managers can use predictive maintenance, reducing diagnostic and repair costs. By using connected trucks, fleet managers will be able to manage their assets more efficiently. This technology isn’t just for large companies – it will help small and midsize businesses improve their logistics services, too.

Robotic warehouses

When it comes to increasing the speed of delivery, a robotic warehouse system can be a huge help. With the help of a robot, warehouse workers can perform tasks such as replenishment, sorting, and returns. Robots can also be used wall-to-wall. While there are several benefits to robotic warehouses, determining which system is right for your needs is key. Different challenges call for different robots and systems.

The first supply chain robot could move material approximately 12 feet. However, they were only used in the industrial sector for several years due to the risk of them hurting employees or the environment. In order to overcome these challenges, innovative logistic robotic companies have been hard at work harnessing the power of AI, machine learning, better sensors, and warehouse management software to make them more effective. XPO Logistics, for example, has been investing heavily in robotic warehouses to increase their efficiency and customer satisfaction.


The use of IoT in logistics services is one way to streamline processes and elevate warehouse functions. Companies can use sensors to manage inventory levels and avoid overstocking. IoT solutions monitor inventory levels daily and can alert companies when they fall below certain thresholds. They can also automate communication with vendors to increase or decrease production rates as needed. By using IoT, companies can better track and monitor the progress of their fleet trucks.

With connected bots, managers can use IoT to streamline the process of shipping and receiving orders. This technology helps businesses cut costs and increase customer satisfaction. Companies such as Amazon have been using these connected bots for years. Internet of Things applications can collect and analyze multifaceted data so that managers can plan their operations and predict the results of business decisions. With these data, they can make better business decisions. The benefits of connected bots are enormous.

Machine learning

The freight business creates vast amounts of data. Approximately 400 million class 8 shipments happen every year in the United States. Computers track thousands of data bits for each shipment, including pick up and drop off times, facility wait times, pricing and tender acceptance, and even GPS coordinates all the way through the shipment. These data are nearly impossible for a single person to analyze, but machine learning can help improve logistics services by recognising patterns and trends that humans cannot.

Before implementing machine learning for your logistics services, you must first assess the structure of your supply chain. Determine your most important factors, including risks, and identify weaknesses. Define your objectives and goals for the operation. Define your Total Cost of Ownership and calculate your Return on Investment (ROI). Using predefined KPI’s helps you define the scope of problems you’ll be solving. Once you’ve completed this, you’re ready to apply machine learning to your logistics services.

Crowdsourced delivery

In today’s world of online shopping, retailers need a way to meet customers’ demands while reducing costs. With technological shifts causing customers to expect faster delivery times, the demand for fast shipping is increasing by the day. Most buyers now prefer to receive their purchases the same day so they can experience instant gratification. This is where crowdsourced delivery can help. It is a service that allows retailers to tap into the network of existing drivers to meet consumer demand.


The concept behind crowdsourced delivery is both tech and asset-light. In crowdsourced delivery, independent drivers make deliveries from the retailer’s store location, typically for a fee based on the number of deliveries made or the amount of shifts. The process cuts costs associated with fleet management, employee benefits, and warehouse operations. Even big players, such as Amazon, are starting to experiment with this model, which will likely have a big impact on the way their customers shop.

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