3PLs and Carriers must invest in a nerve center that truly powers their muscle.
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It has been four years since the pandemic. That has been followed by an ongoing war, persistent inflation, Suez Canal blockage, Baltimore disruptions, high fuel prices, and a fractured economy. Have we fully recovered from its impact? Industry data tells the story. The ratio of business logistics costs to nominal US GDP remains stubbornly high at more than 9% compared to less than 8% in the pre-pandemic times.
Even as volatility and disruptions become the norm in the years ahead, how can we ensure our transportation and warehousing systems are flexible, robust, and more importantly resilient? Market leaders like Amazon have demonstrated the central role of Digital Tech in building this capability. With a plethora of choices, the question for regional and mid-size companies is ‘what is the right architecture for them?’
Move From Slow, Standalone Software to Resilient, Holistic Tech Ecosystem
To be truly resilient, one must approach tech holistically and embed it at the core of logistics operations. Piecemeal and standalone applications add muscle but end up creating silos that result in incremental benefits and limit your ability to capitalize on opportunities or respond to challenges.
The key to true resilience comes with an intelligent control center – what we call a versatile nerve center. It assimilates vast amounts of data generated by the disparate enterprise applications, transforms them into insights, and drives action, essentially infusing an ability to respond to opportunities or uncertainties in real time. In essence, slow and reactive enterprise systems such as the ERP, TMS, and WMS gain dynamic, adaptive muscle power through the AI-control center.
Intelligent Control Center: Embed Resilience at the Core
An Intelligent Control Center is analogous to the human brain. Information from across the business is centrally collated, AI algorithms process the data, generate intelligent insights that drive a suite of Distributed Serverless Applications to execute the appropriate action. And just like the brain, data from the outcome of these actions are tracked and serve as inputs for continuous learning. This allows the business to anticipate changes, allocate resources to address new opportunities, and be resilient to changes.
Data Engineering, Machine Learning, AI – The Core of the Intelligent Control Center
The core of the Intelligent Control Center comprises a network of Data Pipes for data gathering, a Data Warehouse or Data Lake for information storage, and a DataOps system to process the data and train the AI algorithms for accuracy.
The Data Pipes consolidate data from various Enterprise Applications such as TMS, WMS, and ERP. The Extract-Transform-Load (ETL) process is used to clean, format and organize the information into well-defined data sets and stored in a Data Lakehouse.
Business Intelligence tools utilize the data to analyze the performance, generate reports, and provide insights for data-driven decision-making. The data is also used to train AI models that power intelligent applications for improved performance and efficiency.
Secure API Framework: Distribute Resilience across Systems
Just as nerves transmit signals between the brain and the muscles, the APIs function as vital communication pathways relaying information between the AI-control center and your enterprise applications.
For example, when your transport management system (TMS) needs real-time route optimization from the AI Core, APIs serve as the conduitseamlessly transmitting data between systems.
APIs can also create seamless pathways between systems. For example, once an order is received, the API allows the ERP system to share relevant order details with the warehouse management system (WMS), ensuring the right order is prioritized. While the WMS continues to update on order fulfillment status, the TMS system is informed to initiate transportation planning, ensuring the right quantities are shipped at the right time.
Connected Devices, IoT, Telematics: Monitor, Sense and Trigger Intelligent action
The purpose of these systems is to monitor the status of shipments, drivers, and vehicles, and accordingly alert the intelligent control center for accelerated decision-making. Just like how sensory organs such as eyes and ears sense the changes in the external environment and alert the brain, these systems continuously monitor factors such as vehicle location, temperature, vibration, and fuel levels in real time.
Modern systems have far superior capabilities compared to older generation Telematics and Tracking technologies. When anomalies or deviations are detected, they trigger notifications to the AI control center, enabling swift, adaptive responses to enhance efficiency and ensure smooth logistics.
For example, if the temperature of a refrigerated truck rises above acceptable levels, IoT sensors alert the AI control center, which in turn instructs the driver with the appropriate remedial measures or dispatches service personnel to prevent damage to perishable goods.
Orchestrate Logistics: Coordinate Information Flow between TMS, WMS, CRM and Back Office Systems
In logistics, every minute saved in processing an order (CRM), every inch of space saved within the warehouse (WMS), and every second reduced in delivery execution (TMS) add up to big cost savings for the logistics enterprise. This is the true value proposition gained from implementing intelligent enterprise applications. Just as the muscles depend on the brain’s commands to perform physical actions, these systems depend on instructions from the AI control center to help them process orders, manage stock levels, and adjust routes in real time.
Muscle without the nerve center?
Without the connection to an AI control center, all that muscle power goes astray. This is the reality of many enterprise applications that operate with fragmented or stand alone AI capabilities, leaving them unable to adapt holistically in real time. Take, for instance, the pricing optimization in last-mile logistics: without AI, the TMS would rely on static, predefined variables such as distance or package size. This severely limits its ability to adjust its rates dynamically in response to fluctuating factors such as demand surges, fuel prices, or delivery urgency. Without AI, companies may either over-price and lose business to competitors, or underprice and adversely impact margins.
Last Mile Intelligence: Delivering Resilience to the Doorstep
The deep-embedded AI capabilities help your TMS breathe true resilience at the last mile. Table 1 illustrates the superior last-mile capabilities brought out by the AI control center.
| Last-mile Functions | Without AI | With AI |
| Route Optimization | Planner collates orders into a standalone database, uses historical data to determine routes, and communicates with dispatchers via email.
——- Often leads to suboptimal routes, higher lead times and fuel costs. |
AI dynamically analyzes traffic and weather patterns, and considers historical data to recommend optimal routes for dispatchers to review/approve.
———- Reduced delivery times, optimized fuel usage |
| Load Planning & Optimization (TL, LTL, Parcel, etc.) | Loads are assigned to trucks and lanes manually, which can result in inefficient load utilization.
——– Limited ability to match by carrier specialization or proximity. |
AI analyzes real-time carrier availability, equipment type, and historical performance to match the best carrier with the load.
———– Improved efficiency and fuel costs. |
Table 1: Enhanced Last-Mile Capabilities Enabled by the AI Control Center
In conclusion, to thrive in the face of ongoing disruptions like supply chain bottlenecks, economic instability, and unpredictable market demands, 3PLs and carriers must move beyond fragmented, standalone systems. Investing in a versatile nerve center—an AI-driven control hub—is the key to unlocking agility, adaptability, and real-time decision-making across your operations.
