Now is a challenging and expensive time in transportation, as shipping demand increases and capacity tightens across the freight sector.

In 2021, domestic shipping rates for road and rail transportation were up 23% from the year prior and are continuing to creep upward in the first half of 2022. High prices and even higher demand since the onset of the pandemic have also led to an increase in service failures. U.S. trucking company failures nearly tripled in the first year of the pandemic and remain a pervasive challenge for shippers, third-party logistics (3PL) companies, carriers and consumers. 

A service failure occurs anytime a customer receives a delivery late or not at all. With quick turnaround times and an abundance of external factors to consider, there are countless ways that things can go awry when transporting goods, including inclement weather, mechanical issues, labor shortages and dock capacity constraints. 

The consequences of service failures vary in severity but affect everyone in the supply chain. For 3PLs, service failures poorly impact customer satisfaction and relationships. The same goes for shippers, who end up with upset consumers because their product wasn’t delivered as promised. Carriers, too, are subject to penalties for service failures, and risk losing future business. On the consignee side, consequences can range from irritation to production-line shutdowns, where employees are sent home because a part needed to run the line wasn’t delivered on time. 

In an attempt to maintain customer satisfaction, costs and productivity, many shippers and consignees are instituting “must arrive by” deadlines, which exact severe penalties when timelines aren’t met. On-time performance is key in today’s transportation climate, and it’s imperative that shippers have a toolkit that sets them up for success. 

The manual planning that worked in the past simply won’t cut it in today’s landscape. The amount of real-time data from multiple sources needed to optimize operations and move product quickly requires advanced, artificial intelligence-enabled technology. Enter predictive analytics. 

Predictive analytics utilizes data, statistics and modeling techniques to inform shippers about potential risks before they become problems, improving visibility, informing decisions and yielding better results. Though there are dozens of ways predictive analytics can be applied to prevent service failures, following are some of the technology’s key capabilities.

Provides insight into market trends. With the cost of transportation at a record high, it’s vital to be able to look at what’s happening in the market and understand trends in real time. Predictive analytics simultaneously gathers and evaluates data from thousands of sources, recognizes directions in the market, and determines ways to lower costs. 

Predictive analytics garners a holistic understanding of where capacity is tightening and loosening, to determine where rates will be rising or falling up to a week in advance. That data might inform how a company can lower its shipping costs by moving product on different days of the week or by using an alternative route (i.e., utilizing interim points or consolidations). The technology can also perform multimodal optimization and compare carrier contracts to see which carriers could supply the most value at the lowest cost. 

Provides flexible labor and volume planning. Predictive analytics gives invaluable insight into the workflow and timeline of the supply chain, to help shippers conduct accurate labor and volume planning on a daily basis. Say a shipper gets several purchase orders into its warehouse management system (WMS) on a Monday that need to be picked and delivered by Wednesday. As that information enters the WMS, the shipper can use predictive analytics to understand if it needs to staff up or down for the next few days. The same goes for dock scheduling and capacity scheduling. 

Predicts and prepares for equipment failure. Trucks break down or require maintenance all the time, but it’s nearly impossible to determine the real-time health of each truck in a fleet without advanced analytics. Equipment-failure analytics can help prevent vehicle failures while they’re out on the road. By gathering data on how recently maintenance has been done on a truck (such as the last brake or tire change) and the condition of parts when they came off the truck, shippers can predict the lifespan of a component and plan proactive maintenance accordingly. In short, predictive analytics takes prior service records and part examinations and turns them into prescriptive, actionable insight. 

Streamlines operations. A transportation management system (TMS) with built-in predictive analytics can alert operations teams when a service failure is likely to occur. The technology can analyze current or incoming inclement weather, traffic or road closures to predict that a carrier will be late to complete a delivery, and give operations teams a chance to pivot. Advanced analytics also takes historical data, such as past carrier performance within a specific area, into account. Armed with this additional context, operations teams can make smarter decisions when it comes to carrier selection to prevent future service failures. 

By providing shippers with invaluable insight into market trends, labor forecasting, equipment failures and operational variables, predictive analytics helps shippers reduce service failures, cut costs and improve customer satisfaction. When it comes to implementing the advanced technology, more and more shippers are partnering with trusted 3PLs who have a firm handle on how best to use the AI-enabled analytics to drive business success. Drawing on predictive analytics with a strong partner will be key to driving more agile supply chains and preventing service failures in today’s challenging freight landscape.

Todd Bucher is senior director, transportation technology at Kenco Group Inc.