Transportation Management System Market Size, Share, Growth Analysis, By component (Solution, Services), By Deployment Mode (On-Premises, Cloud), By Transportation Mode (Roadways, Railways), By Region -Industry Forecast 2024-2031

Global Transportation Management System Market size was valued at USD 13.61 Billion in 2022 and is poised to grow from USD 15.98 Billion in 2023 to USD 49.11 Billion by 2031, growing at a CAGR of 17.4% in the forecast period (2024-2031).

Factors fueling growth of the global transportation management system market include expansion of the retail and e-commerce sectors globally, sustained technological advancement that keeps giving birth to new solutions that enter the market, and continuing progress in the two-way trade relationship between several countries globally. TMS systems enable the automatic processing of manual supply chain management activities such as shipment tracking and route optimization as well as planning and execution. Hence, the key drivers of market growth focus on error reduction by human intervention, time saving, and the cost associated with transportation management operations. Supply chains tend to depend on transportation management systems, which constitute a crucial component of most elements of the process, such as operational planning, procurement, logistics, and lifecycle management. TMS provides wide visibility that aids in the proper planning and monitoring of transport, thereby improving the customer experience. With this dynamic change in the trade environment and transits in the global arena, enterprises need a system of TMS that will help them negotiate complicated transit operations and procedures around trade rules and compliance. The following, therefore, are expected to drive market growth. According to the World Economic Forum, many industries, including those in logistics, supply chain, and transportation, now use AI. Increased amounts of data in supply chain management and transportation call for more efficient ways to process data, meaning there is a growing need to have AI used by the transportation management system to track data in real time to maximize efficiency. For instance, IBM Watson is already using AI adaptation in transport management for identification of damages to logistics assets by many organizations operating in the transportation sector. The solution also leverages on cognitive visual recognition capabilities that are expected to foster market growth, through its exploitation of predictive analysis for better routes and management of networks.