5 Stale TMS Technologies
Woman tendering shipments manually with spreadsheets

Efficiency is a shipping and logistics best practice.

That shouldn’t even be up for debate in 2020. And the technology to transform the way you ship is readily available. However, the shipping and logistics category has been slow to adapt, favoring legacy processes over visibility, speed, and control. You may be surprised to find that TMS providers are still marketing these dead features as cutting edge technology. That’s why we compiled a list of 5 stale TMS technologies to leave behind in 2020.

#1 Routing Guides & Business Rules

Before the introduction of technology like AI, the static planning and table lookups used to execute shipping in supply chains made perfect sense. Routing by zone and assigning carriers by region & product weight was cutting edge in the 90s and early 2000s. But when you know better, you can do better. Creating static rules and attempting to predict the optimal way to execute shipments is no longer necessary. The rules are native to the shipment and real-time rating ensures best practices are enforced for every shipment. With advancements in AI, we can build shipments based on finished weight and dimensions and book them with the lowest cost carrier who meets the service requirements. With advancements in AI, TMS tech can be truly dynamic. If 2020 has taught us anything it's the importance of dynamic shipping technologies and strategies.

#2 Manual Tendering

A core component of “best practices” is efficiency. Sending emails and making phone calls to book a load or tender a shipment wastes time and creates extra work. It also makes accountability impossible. As blockchain technology is on the rise, eliminating manual processes will become a central focus of improving business practices. Be it an EDI 204 or an API call, utilizing technology to execute inbound and outbound tendering ensures a data ledger of the request and acceptance of a load.

#3 External Auditing

The past decade was fraught with auxiliary technologies appearing to try and fill the existing gaps in supply chain management and execution. While we should all be inspired by the concepts, the idea of further fragmenting shipping processes should terrify us all. Centralizing data and processes is only going to become more essential over time (see above re: blockchain). The TMS is the ideal place for auditing to begin and end. We know what was shipped, who executed the shipment, what the quoted cost was, what the contracted rate is, and when the invoice shows up we can reconcile those details to hold carriers accountable.

#4 Manual Load Planning

What will fit on this truck? What should go together? Should we combine these orders to be a multi-stop TL shipment instead of individual LTL shipments? These are really difficult and time-consuming questions to answer - for a human. AI and machine learning have the ability to build optimized loads based on size, weight, dimensions, ship-to location, and more. For businesses shipping temperature-sensitive items, knowing what will be on the truck and organizing it based on mass to ensure temperature stability is a process that should be fully automated.

# 5 On-Premise Systems

There was a time when the cloud was understood to be an unsecured environment. On-Premise systems that could be seen and maintained were believed to be safer - and perhaps that was true 10 years ago. Today the tangible comfort of on-premise technology is one of the greatest security risks to your business’ operations. What happens when your on-premise system goes down? Perhaps you have a backup server and switch over. But did you lose any data? Was a shipment missed in the time it took to fire up the backup? There’s also the question of scalability. An on premise system will be limited to the available server and can crash at times of peak demand. And what if you open a new location? You’ll need additional hardware. Cloud-architected systems are made to scale because they don’t need on-premise hardware to execute shipments.