Autonomous Agents Set to Revolutionize Transportation Infrastructure Management
A new survey by Manhattan Associates Inc., in collaboration with Vanson Bourne, has highlighted several key challenges that organizations are likely to face in their transportation management systems (TMS) by 2030. The research, based on insights from 1,450 senior decision-makers across various sectors, sheds light on the evolving demands of TMS in the face of technological advancements and sustainability mandates.
The survey focused on the importance and increasing complexity of transportation in supply chains, with 62% of organizations already implementing the Corporate Sustainability Reporting Directive reporting. Sustainability remains a priority in organizational thinking, requiring modern TMS to provide data visibility and functionality.
One of the significant challenges identified is the integration of AI and modern technologies into existing systems. Many organizations struggle with this, hindering the adoption of effective TMS. The lack of high-quality, accessible data also poses a significant obstacle, affecting the ability to make informed decisions and ensure operational efficiency.
Sustainability compliance is another area of concern, with 69% of organizations indicating that sustainability is a major mandate or pressure point. However, only a small percentage have effectively integrated sustainability into operational planning and procurement decisions. Navigating complex and shifting sustainability compliance requirements is a global challenge.
The need for end-to-end visibility across operations is increasing, but challenges in achieving this level of visibility affect operational efficiency. The value of visibility extends beyond data access, lying in the ability to address issues and make operational improvements more efficiently.
While many organizations anticipate the use of autonomous agents by 2030, almost every organization reported facing or expecting to face hurdles, including skill shortages, integration difficulties, and data quality and availability issues. Current adoption rates of AI and machine learning in TMS are low, with only 37% having deeply integrated these technologies.
By 2030, the demands on TMS to operate in smarter, more intuitive ways will intensify, increasing the pressure on organizations. A modern TMS can help deliver the data visibility and functionality needed to measure progress and demonstrate sustainability compliance. Failure to act now may expose organizations to rising costs, questions over long-term efficacy, and the risk of falling short of customer promises.
According to Bryant Smith, director of Transportation Management Systems at Manhattan Associates, challenges include shorter fulfilment times, capacity and cost efficiencies, tighter sustainability regulations, and the need for end-to-end visibility. By addressing these challenges, organizations can improve their TMS and better prepare for the technological and operational demands of 2030.
In conclusion, the survey by Manhattan Associates Inc. and Vanson Bourne underscores the importance of addressing integration difficulties, data quality issues, sustainability compliance, and the need for operational visibility to ensure the success of transportation management systems in the coming years. Organizations that take proactive steps to overcome these challenges will be well-positioned to thrive in the evolving landscape of TMS.
- As the demands on transportation management systems (TMS) continue to grow, it becomes crucial for organizations to focus on integrating artificial intelligence (AI) and modern technologies into their existing systems, as highlighted by 62% of the surveyed organizations.
- In the face of the increasing need for end-to-end visibility in operations, the finance industry will play a significant role in helping organizations navigate complex sustainability compliance requirements, a challenge identified by 69% of the senior decision-makers.
