Depending on the size of your company, you may be using a transportation management system (TMS). When they first arrived on the market, TMS were fancy "toys" the big players used to help drive down costs. Over time, TMS became more powerful, and dropped in price. The addition of cloud-based Software-as-a-Solution (SaaS) systems in recent years has opened up TMS to more shippers than ever before, and many are taking advantage of that access to lower costs and improve operational efficiencies.
According to Transparency Market Research, the market for TMS is growing at more than 13 percent a year and will become a $30 billion market by 2025. Those using a TMS can save approximately 8.5 percent on their freight costs, according to a report from ARC Advisory Group. A Gartner survey found that TMS users typically expect between a 5 percent and 15 percent yearly savings.
The "old-school" TMS used to provide tracking information and some basic functions such as rate and customer information. Modern systems now incorporate all aspects of the supply chain, from the time the order is placed until invoicing, and every step in between. It is these incremental steps in the supply chain where so many shippers are now finding value.
"The biggest differentiator for many buyers is the need for a proprietary algorithm for optimization. Without the optimization, many potential customers will look elsewhere," a 2018 ARC Advisory Group brief on the subject pointed out.
The decision to adopt a TMS depends on the return on investment. While an 8.5 percent savings on freight spend is enough for some businesses, there are other expenses that can be reduced through use of an advanced TMS.
It starts with integration. Even in situations where mergers or acquisitions result in different systems being used across an organization, a TMS can bring those systems together through API integrations. With visibility across locations, data can be collected and analyzed to identify inefficiencies in one location such as long loading/unloading times. Once identified, a company may look for similar datasets across the enterprise to identify if this is an isolated issue.
One big benefit of modern TMS solutions is multimodal functionality. In an e-commerce world, the integration of modes in a single supply chain has grown, and that has added complexity in appointment times, routing, and tracking. The ability of a TMS to properly track a shipment and ensure it is traveling on the most appropriate and cost-effective mode throughout its journey is a critical component of modern systems. Even along that journey, the TMS is providing additional value through machine learning, resulting in not just a freight spend reduction, but also additional organizational savings.
Machine learning gives TMS platforms the ability to take all the data being collected, combine real-time reporting and analytics, and provide actionable recommendations – or even automate processes – that drive savings. One example would be route optimization, but another is identifying preferential patterns for customers. The TMS incorporates all the data on each shipment/customer and can build and identify for each important datasets that can be used to make more informed decisions in the future.
"A shipper can analyze which carriers are too often late, and which lanes and destinations often receive late shipments. Consequently, it is not surprising that most companies using a TMS maintain or improve their service levels," Steve Banker, the vice president of supply chain services at ARC Advisor, wrote in a recent Forces article.
The systems are also capable of generating vast amounts of data that can be used in additional ways. "I would argue, for example, that a balanced set of metrics also should include some measure of how popular a shipper is with carriers; whether the shipper is a shipper of choice. First tender acceptance rate for the lead carriers on your lanes is a good proxy for performance as a shipper of choice," Banker wrote.
How valuable each of these are to companies varies, but effective route planning is known to reduce costs. Previously, much of that savings came from load optimization of multi-stop routes or improved linehaul route optimization. But did it really? Some studies have indicated that it takes 1.4 tenders on average to get a load covered and the closer to the load time, the more likely the tender is to get rejected. Done manually, load optimization can eat any savings very quickly. Automating the process through a TMS that uses machine learning to understand and incorporate carrier and shipper preferences can regain much of that cost saving.
Automation could also automatically dispatch loads that must be covered and provide lane analysis to find carriers, based on past activity, most likely to accept loads along a given lane, thereby reducing time and cost in finding a carrier. Analysis might also provide data on when moving to the spot market to cover a load is the best option.
Locating backhaul opportunities for carriers, more dynamic routing, and even improved communication are other opportunities to reduce costs for supply chain participants.
TMS solutions must also handle large amounts of data, as previously noted. Sorting through that data requires having the right solution in place to effectively digest, analyze and compartmentalize the data before distribution to the correct parties.
Finally, perhaps the biggest advantage advanced TMS offer is their price competitiveness. As technologies have progressed, the price of the systems have dropped, offering smaller businesses the opportunity to implement robust TMS solutions to drive down costs and giving them a new weapon in competitive shipping.
© 2024 Benzinga.com. Benzinga does not provide investment advice. All rights reserved.
Trade confidently with insights and alerts from analyst ratings, free reports and breaking news that affects the stocks you care about.
