The ever-expanding field of artificial intelligence (AI) is leaving an indelible mark on every industry, logistics included. In its Logistics Trends Radar report, DHL identified AI and machine learning (a subset of AI) as key technologies driving logistics innovation. With its ability to rapidly make sense of massive data sets and automate operational processes, AI is transforming the movement of goods and creating competitive advantages for business supply chains across the globe.
For shippers, AI tools consistently deliver an array of benefits from improving efficiency and productivity to saving you dollars throughout your logistics operations.
Here are 3 Ways AI is Transforming Logistics Management
1. Predictive Logistics
With its ability to gather and analyze thousands of disparate data points, AI can help you solve a problem you don’t know is there. Combining data from historical events, current environment, and future expectations, AI enables businesses to shift from reactive to proactive decision making. With AI technology, shippers can manage disruptions (like weather), reduce downtime, and effectively plan and budget their logistics spend and operations. More impactful than dealing with disruptions, AI-enabled logistics platforms allow organizations to drive efficiency and profitability from daily operations.
At GlobalTranz, we help companies track financial forecasts, pace and flow of production, and order processing. These data points, combined with deep insights into carrier capacity and performance, allow companies to answer questions like, “How many more orders can we service within budget for a given set of lanes? or How much can we increase manufacturing without going over our freight budget?”
2. Optimization Events
AI is being used to make faster and smarter decisions that optimize carrier selection, rating, routing and quality control processes. The abundance of data, sophisticated algorithms, and dynamic business rules helps move shipments from point A to point B, C, and D, using the most efficient, fastest route. In the past, it could have taken up to six months to thoroughly understand the unique features (best- and worst-case transit time, the impact of weather and other factors) of specific routes. Today, analytics based on AI can examine large sets of data in seconds and create simulations that match shipper demand with carrier behaviors like capacity, service capabilities and backhaul opportunities to determine the best combinations of carriers and lanes for delivering loads.
3. Recommendation Engines
In logistics management, many repetitive tasks can be made more efficient through automation. Using AI computing techniques, like machine learning and natural language processing, we can teach systems to recognize patterns in data, and based on its findings, issue a recommendation or action. Over time, self-learning enables logistics solutions like GTZconnect to continuously improve operating algorithms and deliver more informed suggestions that help shippers automate logistics decisions and increase the efficiency of business processes.
For example, at GlobalTranz, we use the concept of ‘AI everywhere’ in our GTZconnect platform to integrate user, carrier, shipper, historical and predictive data to route inbound inquiries to the best customer support representative equipped to handle a question or issue. We also incorporate real-time information on weather, seasonality, traffic, and other data inputs to recommend the best solution for each shipment. Rather than spending hours on repetitive tasks, AI enables businesses and their employees to focus their time on higher-value projects that help transform and grow their businesses.
How to Leverage the Power of AI in Your Logistics Operations
As companies continue to emphasize the impact logistics has on earnings and customer loyalty, they increasingly turn to innovative technology and automation for practical solutions. Logistics leaders should equip their business and teams with technology, like GlobalTranz’s no-cost TMS platform, which centralizes freight data, integrates business systems data, and leverages AI, machine learning and predictive analytics to create operational efficiencies and make better business decisions.