We all know big data is one of the singular biggest forces impacting all industries as we enter the next era of work. And that is perhaps no truer than in the logistics space.

In fact, the Council of Supply Chain Management Professionals recently completed a study (dive in more here) that found that:

  • 98% of third-party logistics firms and 93% of shippers believe data-driven decision-making is essential to supply chain activities
  • 86% of logistics firms and 81% of shippers expect analysis to become a core competency of supply chain organizations
  • 71% of firms believe that big data improves process quality and performance

Though the study is new, the concept of data as a core underpinning of logistics operational excellence is not all that new.

The logistics space has always been a high-pressure industry — with a hyper focus on moving faster without sacrificing quality, automating manual toil, and eradicating waste and inefficiency every step of the way. And, in recent years, the industry has faced newfound pressures like COVID, climate change, the labor shortage, and growing technical talent gaps… making a high-pressured industry even more taxed.

Related Read: From AI Naïve to AI Aware

Today, logistics companies face a host of new challenges, like the need to…

Drive greater real-time visibility into their operations

Streamline the collection of data from an ever-growing number of sources

Navigate the information overload, context switching and data deluge

Solve problems by integrating technology and automation solutions, instead of simply adding headcount

Operationalize and drive efficiency through workflow optimization and automation (more on that here)

That’s why data is getting so much attention within the logistics space as of late. Logistics leaders are looking at ways to embrace artificial intelligence and advanced analytics solutions at a pace that is far greater than ever before because the cost savings and revenue gains are simply too grand.

Intentional Approach to Data

Let’s examine three specific examples of where an intentional approach to data, automation and advanced analytics can have an immediate impact on financial health and organizational efficiency.

  1. Demurrage Charges: With the average detention and demurrage costs at ports around the globe at $664 for 2022, this is one of the first places to examine when it comes to data application. As an example, by adding automation that checks emails for incoming demurrage notices from carriers and scans web portals for charges, logistics companies can alert their teams in real time and automatically write the charge and relevant details to a spreadsheet so that people can see the charges that are outstanding. When this happens, action can then be taken immediately. The ability to identify the truck that needs to be moved right then saves a substantial amount of money. For our recent client, the automation pathway we suggested for them saved them upwards of $11 million!
  2. Freight Auction Bidding & Pricing: Let’s say the average logistics companies receives about 15,000 bid requests a year. If you look back at just the last 3 years of data, you’ll see that you’re sitting on an incredible amount of historical data that can be leveraged to increase velocity of bid response, reduce manual effort involved, and optimize price for higher profit margin. An “alert-bot” can search sites where bids are submitted, ensuring that a logistics company can respond to all available and suitable bids in a timely manner. By performing a full analysis on your current data around bids won and lost and then building a tool to model historical data — won/loss and profit margin along with factors like load size and type, hazmat status, weather variables, weight & count, travel distance, and number of stops — you’ll immediately uncover intelligent bidding parameters to be used when a bid is proposed, thereby uncovering ways to enhance and optimize profit.
  3. Carrier Contract Automation: Automation can be particularly powerful when it comes to speeding up the process around contract bid proposals. A quick but powerful way to automate this process is to add automation to the contract process to automatically detect a request for bid when emailed to a shared email box. Then, a template would be generated with values pre-populated from the bid response email. The contract bid team would then be alerted and would review the template, making changes if necessary. This could all happen inside of a lightweight custom application. And just like that, the team could bid on a far larger number of contracts than they are currently. In addition, the same data analysis used to tune the bid response can be used to search the eligible population of driver/operators and select the one best positioned to fulfill the contract.

From getting more sophisticated with data management and control to leveraging AI/ML models, there is no shortage of ways that logistics companies can more intentionally depend on analytics to drive their operations forward. But the biggest shift in the industry today requires us to stop thinking about adding people to solve our problems, and instead pinpoint ways to leverage tools, automation, and advanced analytics to move faster and smarter.

We are in the era of speed, self-service, automation, and digitization. And that means we have to get more honest about the parts in our workflows and processes where the manual headaches of yesterday are deeply preventing us from moving forward tomorrow.

Want to talk directly with Walter about some top ways automation may benefit your team? Click here to shoot him an email directly.