For yield management, employing advanced optimization algorithms, the generative AI capability would suggest the most efficient container configurations, minimizing empty space and maximizing the utilization of available capacity. This would reduce operational costs and optimize resource utilization, leading to improved yield management.
Developing the Right Architecture for High Volumes of Data
One of the biggest challenges in adopting AI tools is centered around data. AI’s effectiveness depends on the availability of existing data. The more data an algorithm processes, the better it performs for an organization’s unique business needs. But how can relevant data be made accessible when most of it is unstructured, scattered, and unavailable in many cases?
An AI-based solution might alert an importer about potential demurrage fees if the organization’s container is held at the port for five days. As comprehensive as this AI model may be, it does not initially recognize the importer’s unique terms with the port, such as excluding demurrage fees for the first eight days. It’s only after scanning the contract that AI tools can provide customized alerts against ocean freight hazards.
How is it possible to process hundreds of such contracts, along with endless other unstructured data, and do so at scale? Both organizations and software providers are increasingly focusing on standardizing data to maximize processing capabilities. When this isn’t feasible, they work to facilitate the proper data architecture needed to process “dirty data” – data that isn’t unified, or standardized.
This approach is crucial across TMSs, software, carriers, and other supply chain providers. Different stakeholders in the supply chain must develop strategies to unify and effectively process large data volumes.
Integrating AI & Technological Enhancements into One Platform
The supply chain industry will find itself at a crucial juncture in 2024. Staying relevant demands keeping pace with technological advancements. A key challenge will be the need to adopt and adapt to emerging AI technologies, without replacing existing transportation management systems (TMS).
When using a legacy system or TMS, toggling between UIs and screens that offer actionable insights is clumsy. It takes too much time when it is necessary to come up with quick risk assessments and decisions.
The trend is shifting towards enhancing these platforms with advanced technological capabilities, allowing for seamless integration of third-party software into existing systems and workflows.
For instance, an organization using a specific TMS for ocean freight operations might spot an opportunity to incorporate an AI-based tool for demurrage risk notifications. Instead of replacing their current system, they can embed this new functionality directly into their existing TMS. This approach not only preserves the familiar operational environment, but also leverages cutting-edge technology for improved efficiency.
This path is not without challenges. Shipping and supply chain stakeholders enjoy benefitting from as many AI-based insights as possible, especially considering the complexity of the maritime ecosystem and the growing number of sanctions since Russia’s invasion.
But selecting the most appropriate tool that aligns with the business’ unique needs and ensuring its seamless integration into existing systems are steps that require careful consideration. The success of this strategy hinges on the ability to choose and smoothly incorporate these enhancements, transforming existing supply chain management technology into a more efficient, responsive, and intelligent system.
Obtaining a holistic picture on one screen, within existing workflows, solves the pain point of endless toggling when trying to gain a complete assessment of shipments, vessels, and containers, and generates fast and accurate risk assessments.
Implementing Technology Transformation Across All Employee Levels
An engaged team is essential for adopting digitalization effectively. Without proper engagement, financial investments alone won’t prevent organizations from falling behind. A key challenge for 2024 is not just selecting technologies that elevate performance, but also training employees to use innovative tools and implementing them throughout the organization.
This is especially crucial during times of restricted spending and smaller work forces. Logistics organizations and software solution providers must ensure all employees are on board. Various companies have noted that a feasible training and implementation plan for all employees, coupled with a user-friendly experience, is critical for transforming business operations.
Greater Need for Agility and Velocity
Supply chain velocity is vital for optimizing operations in 2024 and preparing for unforeseen disruptions, such as the recent and repeated Houthi attacks in the Red Sea area, the Panama canal restrictions, or even port strikes and weather conditions. The pandemic taught logistics organizations to prepare for major disruptions.
Supply chain velocity is the speed at which supply chain actions are completed, or the pace at which orders move through the supply chain, from processing, to arrival at the customer. High supply chain velocity enables organizations to change direction quickly on short notice, by shortening order cycle time, minimizing lead times, and streamlining supply chain processes.
High supply chain velocity enables customers to receive orders with relatively little turnaround time between order placement and delivery, and allows businesses to respond quickly and accurately to changes in demand, leverage market opportunities, and efficiently manage supply chain resources. Improvements to the various stages of the supply chain can increase supply chain velocity in areas such as loading, unloading, and cargo discharge.
With the right approach, organizations can achieve high supply chain velocity. Let’s look at two ways to make this work.
Exception Management
To keep their business operations running smoothly and maintain the integrity of the supply chain, freight forwarders, importers, exporters, and others must be able to perform container tracking for all their shipments, monitor delivery statuses, and ensure on-time arrival at the intended destinations. Trying to do this manually is a huge challenge.
Exception management automatically sends alerts about problematic cargo, allowing organizations to quickly identify deviations from the plan, and analyze and resolve the issues. It enables companies to speedily overcome the costly risk of disruption. Wasting time and human resources manually analyzing cargo shipments has a negative impact on an organization’s supply chain velocity.
Automated alerts reduce the time it takes to analyze shipments from hours or days, to just minutes, contributing to high supply chain velocity.
Share Freight Information
When significant events occur, such as 2023’s historic drought in the Panama Canal region and the resulting limit on vessel passage, advanced container tracking assumes even greater importance than it does during business-as-usual.
It’s one thing knowing what is happening, or what could happen, but without being able to quickly and easily share information and collaborate during fluid situations, organizations don’t really possess agility or flexibility. Providing stakeholders with access to specific container information is critical to supply chain velocity.
Supply chain personnel should not have to manually send and manage a sea of emails while trying to communicate vital information to the container’s stakeholders in real time to avoid disruptions and improve cargo status visibility. An advanced and shareable shipment page within the transportation management system enables easy sharing of a real-time view of a container, with automated tracking for both users and non-users.
This streamlines the tracking process for customers, shippers, consignees, and other key stakeholders, seamlessly creating a single source of truth, and improving supply chain velocity.
