The modern logistic industry is all about high-tech integration; transport management systems (or TMS) are among the most widely used software there, becoming a necessity for any strong logistics enterprise.
Advanced logistic software development allows them to satisfy the market’s demand for lowering costs at any stage of the supply chain, as well as transform the industry to be more responsive in times of post-COVID global challenges.
A good TMS can boost a company’s productivity in many areas, creating a huge overall effect on the results of activity, decreasing expenses, making more effective use of human resources, and drastically reducing the number of process mistakes.
This leads to the constant increase in TMS adoption worldwide — a report by Grand View Research forecasts the TMS market to reach $31.18 billion by 2030 with a CAGR of 14.6 percent.
TMSs have been present on the market for a while and have undergone several waves of updates correlated with new technological breakthroughs and improvements and aimed at improving their interoperability with other logistics software. Let’s take a deeper look at this trend.
Combining TMS with other logistic systems
TMSs tend to show increased productivity when combined with other software used in logistics, such as fleet management systems or FMS, invoice systems, truck navigators, and stock management systems. The combined use of this software leads to increased accuracy of interactions with customers and contractors, as well as reduced number of manual operations throughout the supply chain data visualization.
Combining TMS and FMS
Fleet management systems are mainly used to distribute data to other logistics software, therefore, they are perfect for coordinating with TMSs. This coordination will in turn increase the efficiency of TMS because the real-time information from the fleet will be used to improve the planning precision. As a result, the overall enterprise productivity will be improved greatly, simultaneously with the decrease in operational costs.
TMS and route optimization
The transport management system is also a key factor in improving the route planning process. After TMSs and FMSes provide precise information about the state of vehicles and orders, the efficiency of trip planning and truck loading gets extremely efficient.
A lot is going on in the logistics industry besides the tendency to combine software. Let’s get a more detailed look at some of the future TMS trends.
Most promising TMS trends
Time flows, and market requirements change as well as customer expectations. TMSs have to change along to stay relevantly robust and help enterprises stay ahead. A lot of technologies that currently emerge and take their place in various industries and spheres of life all over the globe can find their place in TMS development as well.
Any large market player can consider introducing these technologies into their TMS to improve their chances of success in the competitive market of logistics and supply chain. Here are the most prominent technological trends worth considering:
One of the main problems with TMS implementation for small and medium-sized logistics companies was the number of resources you’d need to invest in it to conduct properly. Both implementing and maintaining a complex TMS were very expensive.
It might not be the case now, though, with the worldwide shift towards cloud computing and cloud-based services. Implementing a cloud-based TMS is much cheaper and, subsequently, much more affordable for small businesses.
Besides the financial benefits, the cloud-based model of TMS distribution also provides ease of access to TMS users: they require only a stable internet connection to work it.
Advanced technological integration
There are a lot of technological novelties around us today, and many of them can be efficiently employed to make TMSs faster, smarter, and more flexible. Big data, AI developments, machine learning, and even 3D printing technology, all are used for creating smart TMS solutions already.
Another great tech usable for TMS benefit is the Internet of Things or IoT, a principle of arranging complex systems of data-gathering devices, sensors, and routers that helps to get precise information on driving conditions for vehicles, cargo conditions, enhanced route visibility, etc.
The best application for machine learning in TMS is the possibility to anticipate transportation timings with great precision due to the usage of historical data and analyzing trends. Machine learning also finds its uses in capacity planning, detecting risky situations and cargo batches, etc.
Machine learning-enabled solutions could also help responsible staff in decision-making when it comes to changing routes on the fly, following data from traffic analyzers.
While blockchain technology is usually associated with cryptocurrencies, it has its applications in TMSs as well, as a tool for organizing complex cooperation structures between TMS users — shippers, freight brokers, carriers, etc.
Blockchain provides incredible possibilities when it comes to tracking, and tracing, creating absolute transfer visibility across the supply chain since the information stored in the blockchain is hard to tamper with.
SaaS-related TMS trends
SaaS-based transport management software has become popular as of late: about 84 percent of logistics solutions nowadays are SaaS-based. This creates several nuance trends, each worth individual considering:
- Increased adoption of TMSs due to SaaS payment models
The spread of SaaS solutions led to significant changes in the way market participants look at investing money in software. They tend to compare the invested amount to the return-of-investment index, which, along with the various payment plans, has created favorable conditions for TMS adoption.
- API-enabled connectivity with legacy platforms
Another reason that made a TMS implementation hard in the past was the absence of interconnectivity between TMSs and some older solutions widely used by market players. The widespread software migration to SaaS made this problem obsolete as well because SaaS-based solutions employ API-enabled easy-to-implement systems
A lot of logistics companies have stated that SaaS-based TMS solutions attract them mostly because of their possibility to automate processes usually performed by human workers involved in the process of freight management. This feature allows enterprises to decrease delay timings and make several logistics processes faster.
Some final thoughts on the matter
The direction that TMSs and other logistics and supply chain software move is quite fascinating. Of course, it is too early to predict, but it looks like all the solutions developed and created for the industry tend to shift more and more towards unifying.
Perhaps, it won’t be long before we see some ultimate, AI-enhanced all-encompassing logistics solutions that efficiently address all the challenges at once, but for now, we can only follow the rapid growth of the TMS sphere.