Transportation optimization is driven by fast-paced business digitalization, improving efficiency and profitability by making supply chains more reliable for those who embrace technology. Transportation management solutions connect big data in logistics, making collaboration efficient like never before.
As a transporter or truck driver, it’s crucial to stay up-to-date on the latest trends and technologies so you can capitalize on new opportunities. Business owners and CEOs need to do the same to ensure their company stays ahead of the competition. This article provides an overview of the challenges and the most exciting changes in the transportation industry and how you can take advantage of them.
The world is becoming increasingly digitized, and that trend is starting to have a significant impact on transportation optimization. Transportation companies have primarily relied on physical infrastructure and paper records to track shipments and keep things moving. However, with the advent of big data, things are changing. Big data is a term for large data sets that organizations analyze to uncover trends and patterns. The data comes from various sources, including GPS devices, toll transponders, and smartphones. Big data in logistics is needed to do everything from route planning and optimizing shipments to predicting traffic patterns and identifying maintenance issues.
This rise is possible because of innovation in IoT (the Internet of things) and 5G networks. They work together to connect a vast array of sensors to collect and analyze huge amounts of logistics data quickly and efficiently.
Transportation management solutions (TMS) are one way to use big data in logistics to optimize transportation. TMS uses IoT and 5G to collect information about traffic conditions, weather, construction, and other factors impacting travel. All data is then analyzed to help planners decide how to route traffic, where to add capacity and provide alternative modes of transportation.
Case in point, UPS uses big data in logistics to develop last-mile analytics for its deliveries. The final leg of a shipment is usually the most inefficient. With big data, UPS stays informed on how long deliveries last to identify optimum strategies. Ultimately, big data helps the logistics industry to be more efficient and responsive to the needs of its customers.
While big data in logistics is great, the vast amount of information it produces needs quick analysis far beyond even the most intelligent human being. This is where artificial intelligence (AI) and Machine Learning (ML) come in.
AI is computer software that can simulate human intelligence. On the other hand, ML is a subset of AI that deals with creating algorithms that can learn and improve independently. These technologies are being used in transportation optimization to automate various tasks such as route planning, order picking, and warehouse management. Here are some of the ways AI is benefiting the transportation and logistics industry:
AI and ML algorithms will supercharge supply chains, making them more reliable but also more efficient, while increasing revenues and profitability for those who embrace the technology. However, while AI and ML are powering analytics and planning, they are also critical to transforming the most crucial part of the industry: the fleet.
Autonomous driving is the ability of a vehicle to drive itself without human input. The term is often used interchangeably with self-driving, but there is a subtle difference. Self-driving implies that the vehicle can operate without driver input. In contrast, autonomous driving indicates that the car can make its own decisions, including when and how to change lanes, turn, etc.
There are several different approaches to autonomous driving, but all of them involve using AI and ML. For example, Google’s self-driving cars use a variety of sensors to map their surroundings and then use ML algorithms to figure out the best way to navigate.
Autonomous driving technology has the potential to make a revolutionary impact on transportation optimization. With the ability to automate vehicles, there could be a significant increase in efficiency and safety for both companies and consumers.
This would allow faster delivery times, lower shipping costs, and fewer accidents. In addition, autonomous driving technology could also help to reduce traffic congestion and pollution.
Volvo and Tesla are both testing autonomous trucks that will soon be the mainstay of the trucking fleets. Waymo, formerly the Google Self-Driving Project, operates a self-driving taxi service in Phoenix.
Even Amazon and Uber are developing plans to involve autonomous driving in their operations. While there are still some problems to solve, such as connectivity and safety issues, the future of transportation is bright with autonomous driving.
Blockchain technology has the potential to change the transportation industry in several ways. The blockchain is a distributed database that allows for secure, transparent, and tamper-proof transactions in its simplest form.
The technology is based on a decentralized ledger of all transactions, constantly growing as “completed” blocks are added in chronological order. Each block contains a cryptographic hash of the previous block, a timestamp, and transaction data.
The first and most well-known blockchain application, Bitcoin, uses this technology to create a decentralized ledger of all Bitcoin transactions. The potential applications of blockchain technology and its integration with transportation management solutions are numerous and varied. Here are just a few examples:
The transportation industry is under pressure to improve efficiency and meet sustainability goals. Connecting big data, autonomous driving, AI, ML, and blockchain technology with a CRM can help the transportation industry become more efficient and sustainable.
A CRM system can help manage customer data, automate processes, and improve communication between different stakeholders. Big data in logistics can be used to improve the efficiency of transportation networks. Autonomous driving can improve safety and reduce emissions. Decision-makers can use transportation management solutions with AI and machine learning to predict traffic patterns and optimize route planning. Blockchain technology can help manage decentralized data and enable trustless transactions.
Perhaps the most important reason is that a CRM can be used as a transportation management solution to help streamline customer relationship management processes. In the past, transportation companies have often struggled with maintaining efficient communication channels with their customers.
This has led to frustration on both sides, as customers have felt ignored or forgotten, and companies have been unable to keep track of customer needs and requests. A CRM can help bridge this gap by providing a centralized platform for managing customer communications.
No doubt, a CRM tool is the best way to go if you’re looking for insights to understand your customer and focus on transportation optimization.