There are many age-old challenges in trucking, warehousing, and freight management. Material moves through a myriad of transport modes, carriers, facilities, and channels within supply chains.
As it turns out, the efficient movement of data associated with these transactions is now as important as the movement of the materials. The data matters because it matters to key stakeholders in the supply chain.
And yes, the data is crucial because we have demonstrated definitively, that there’s “gold to be mined” in that data. Within the data lies the opportunities to tame many of these generational challenges, and I am proud to say that Penske Logistics and the supply chain industry are making swift progress down this important path.
Without getting too deep into the technical, here are a few paths that are delivering results today or showing promise in the immediate future:
Empowering and Involving People
AI is an incredible tool, but people are the bedrock of making things happen.
Supply chain activity is comprised of seemingly countless transactions all managed by supervisors and logistics managers who have really busy jobs. These folks do not have the time to sift through vast amounts of data to draw inferences, so we use AI to help do that for them.
Using specially designed algorithms, we detect situations that may detect trouble brewing with whatever processes or movements they are managing. We arm our supervisors with this information.
They then engage with associates and customers to validate if, in fact, any anomaly we detected in the data is something that must be acted upon, and if so, they can correct it.
Along the way, we are making a significant impact solving some of the typical supply chain problems I have been referring to like losing talent, dealing with underutilized assets or understanding the right freight rate to pay on a shipment.
AI and Yard Management
With winter coming, the days grow shorter and navigating football field-sized yards full of trailers gets difficult. Who really wants to be out doing a yard check on a freezing cold, rainy or even a sweltering day, trying to identify damage to equipment or the whereabouts of a trailer?
It turns out that AI can help turn images into data and much more. This enables our staff to tend to other responsibilities and helps them do more in a less taxing manner.
I could go on with more short-term examples, but you are likely seeing a common theme here. It enables our front-line leaders, who manage truck drivers, forklift operators and load planners, to be better, faster and more efficient. We are excited about making their jobs easier so they can concentrate on critical things like nurturing talent, increasing safety and delivering high-quality customer service.
3PLs and Shippers Are Looking Ahead
Supply chains have become increasingly complex and challenging for companies to manage. With intricate networks spanning multiple countries and continents, companies must navigate a myriad of factors, including fluctuating demand, logistics, regulatory compliance, unforeseen disruptions and multiple vendors, suppliers and logistics providers across modes.
AI is poised to transform the way 3PLs and shippers approach supply chain management, offering unprecedented efficiency, agility and resilience. At its core, AI encompasses a broad range of technologies, including machine learning (ML), natural language processing, computer vision and robotics, all of which are designed to mimic human intelligence and decision-making capabilities at an accelerated rate.
By harnessing the power of vast data sets and algorithms, AI can help us identify patterns, make predictions and optimize processes in ways that surpass human capabilities. One of the most significant advantages of AI in supply chain management is its ability to enhance demand forecasting.
Accurate demand forecasting is crucial for companies to align their production, inventory and distribution strategies with customer needs. AI algorithms can analyze historical sales data, market trends, consumer behavior patterns and external factors, such as weather and economic conditions, to generate highly accurate demand forecasts. This not only reduces excess inventory and stockouts but enables shippers to respond swiftly to changing market conditions or disruptions.
Transportation and Logistics Heading to the Next Level
AI is already helping to revolutionize transportation and logistics operations. By leveraging ML algorithms and real-time data from sensors, GPS and telematics tracking and traffic patterns, AI can optimize routing and scheduling, minimizing transportation costs and delivery times.
Additionally, AI-powered predictive maintenance can anticipate equipment failures and schedule preemptive repairs for trucks, forklifts and material handling equipment, reducing downtime and ensuring smooth and efficient operations.
A great and real-world example of this is the newest innovation at Penske Truck Leasing with its introduction of Catalyst AI™ – an industry-first AI platform set to revolutionize fleet management that delivers real-time insight into fleet performance.
Catalyst AI marks a pivotal shift away from traditional industry benchmarks, empowering fleet managers with actionable intelligence to optimize fleet performance using dynamic comparative data around their fleets. It’s also a tool we’re using at Penske Logistics to further improve our fleet operations.
Inventory and Warehouse Management Gets a Lot Smarter
Warehouses and distribution centers used to be thought of as simply big boxes to hold inventory. However, today, with technology and the addition of AI and automation, they are so much more than that.
In the realm of inventory management, AI can work wonders by optimizing stock levels and SKUs across multiple warehouses and distribution centers. By analyzing demand patterns, lead times and supplier performance, AI can also recommend optimal inventory levels, minimizing the risk of overstocking or stockouts.
Further, AI-powered warehouse automation, including robotic picking and sorting systems, can significantly improve efficiency and accuracy, reducing labor costs and errors. Supply chain risk management is another area where AI can provide invaluable insights. By monitoring global events, weather patterns, political instability and supplier performance, AI can identify potential disruptions and recommend mitigation strategies.
Predictive analytics can also help companies anticipate and prepare for potential supply chain risks, ensuring business continuity and resilience. Moreover, AI can streamline procurement processes by automating tasks, such as supplier evaluation, contract negotiation and spend analysis.
Natural language processing (NLP) can analyze vast amounts of unstructured data, such as supplier contracts and performance reviews, to identify potential risks, cost-saving opportunities and areas for improvement.
Beyond operational efficiencies, AI can also help drive sustainability initiatives within global supply chains. By optimizing transportation routes, reducing waste and identifying opportunities for resource conservation, AI can help companies minimize their environmental footprint and contribute to a more sustainable future. However, the successful implementation of AI in supply chain management is not without its challenges.
Data Matters
As mentioned previously, data quality and availability are critical for AI algorithms to function effectively. Companies must ensure that their data is accurate, consistent, and comprehensive, which may require significant investments in data management infrastructure and processes.
Additionally, the integration of AI systems with existing supply chain management software and processes can be complex and time-consuming. Companies must carefully plan and execute their AI implementation strategies, ensuring seamless integration and user adoption. Ethical considerations, such as data privacy, algorithmic bias and transparency, must also be addressed.
As AI systems become more prevalent in decision-making processes, it is crucial to ensure that they are fair, unbiased and transparent, adhering to ethical principles and regulatory guidelines.
Despite these challenges, the potential benefits of AI in global supply chain management are too significant to ignore. Companies that embrace AI early and effectively will gain a competitive advantage, enabling them to respond rapidly to market changes, optimize operations and drive sustainable growth.
As we move into the future, the role of AI in supply chain management will only continue to grow. With advancements in technologies, such as edge computing, 5G networks and the Internet of Things (IoT), AI systems will become even more powerful, enabling real-time decision-making and seamless integration across the entire supply chain ecosystem.
Back to the Question About AI
Getting back to my original AI discussion with a dinner companion, my answer was yes. At Penske, we are calm and confident about AI and its possibilities. We are investing in it, and it is making us and our people better at what we do.
AI is poised to help revolutionize global supply chain management, offering unprecedented efficiency, agility and resilience for 3PLs and shippers. Until next time, Bon Appetit!
By Andy Moses
Bob Costello 
Tim Denoyer
John Langley
Mark Baxa 
Nate Springer 