We recently had the opportunity to sit down with Kevin Ziegler, Chief Technology Officer for Navix. With over 20 years of experience in technology and the leader of our technology and development teams, we wanted to get his perspective on technology, AI and what the future holds for the logistics industry.

Q. What are you seeing as the biggest technological advances in the logistics industry today? What impact are these technologies having on 3PLs and Freight Brokers?  

KZ: When I began in the logistics field over 20 years ago, technology was in its infancy – if you wanted to solve a problem, you likely needed to develop it yourself.  Now, I’m very excited about a number of technological advances that should provide enormous value to this industry including: 

• The hype of blockchain may have died a bit, I believe adoption of blockchain for contracts, and shipment tracking, will provide payment and document integrity to our field. 
• 5G and Satellite communications will drive a continually connected supply chain for visibility, tracking, and real-time communications anywhere in the world Autonomous vehicles haven’t come to fruition as once anticipated, however their usefulness in moving freight may prove to be the most useful.  Terminal to terminal routes are static, relatively free of complications, and are already proving to be a perfect entry point for autonomous vehicles.  Looking further ahead, autonomous vehicles and aerial drones have a lot of potential for final mile delivery. 
• Artificial Intelligence (AI) and Machine Learning (ML) advances are delivering their weight in gold for this industry.  There is so much data in the supply chain that can drive ML models to provide the AI capabilities for many areas.  At Navix, we use ML/AI for many aspects of identifying and extracting data from documents, automating formerly manual audit processes, and use it to automate some of our software development.  Other uses such as predictive pricing, understanding unstructured data (e.g., Email, documents, etc.) have huge potential for 3PLs and freight brokers.  
• Better utilizing the vast amounts of data.  The data that we have, and the data we’re continually generating, is so incredibly valuable as we learn how to use it better.  Realtime data exchanges help drive better outcomes, better use of historical data can help find efficiencies.  Ultimately the data we have will help supplement each of the points above to help drive better outcomes in our field. 

Q. You wrote an article recently on the power of real-time analytics. With tools available to provide this real-time insight, why is it that more companies have not adopted these technologies?  

KZ: I believe there are two broad reasons that real-time analytics haven’t been adopted widely in the logistics industry.  First, a lack of understanding how data-driven analytics can drive decisions and automation.  Second, for companies that have the vision, it can be difficult to implement and utilize real-time analytics systems due to high upfront costs, caused by fragmented or legacy systems that are difficult to connect. Additionally, the inability to implement change management, and lack of experienced staff to implement and maintain data analytics systems are some of the obstacles organizations are facing.

Q. AI is dominating headlines and has generated a lot of debate about governance and accessibility. What is your take on AI and what thoughts do you have about how businesses can use AI to spur growth? 

KZ: First and foremost, while I’m very bullish on Artificial Intelligence I do implore everyone to embrace AI with some caution. AI can make mistakes, tools within AI may be utilizing your sensitive data, and you need to have some governance within your organization on how AI may be utilized. 

After you’ve established some governance, I’d encourage you to experiment.  Start small, limit the scope for each use of AI, so you can easily measure your successes or failures.  Spend some time learning, training, or hiring the right people or partners to help you with your projects.  Focus on ethical usage of AI, ensure that AI systems are transparent, fair, and don’t perpetuate biases. An ethical approach to AI can be a significant selling point for customers and stakeholders. 

Often one of the biggest problems that organizations face on an AI project is not having high quality data to drive the AI needs. You may want to look at your data assets, and do some housekeeping, or make changes to your systems to start having the quality of data you’ll need to for AI success. 

Q. There is a misconception that AI and machine learning are new, and some are fearful of it taking their jobs.  What do you say to that? 

KZ: The recent buzz around Chat-GPT has certainly been dominating the headlines, and caused many to speculate this will replace jobs, and to a certain extent I believe it will.  We faced the same question in manufacturing with robots that have been built to perform one task well, and this replaced a repetitive human function.  We’ll see the same with AI, it will perform some specific tasks well, and this will replace some job functions.  We are at a stage right now where we tend to have high confidence in AI to perform a very specific task. These tasks are generally low value tasks that can reduce human involvement.  With that said, I don’t expect our workforce to be reduced because of AI, rather our people will focus on higher value tasks. 

Q. Navix is a rather unique solution and has produced some incredible benefits for our customers. What does the future hold for other ways Navix intends to help our customers?  

KZ: I’m so proud of the work my team has done to drive the successes we’re seeing in our industry, and I’m just as excited to see us improving on an amazing product.  One of the key drivers of success that we provide to our clients is improving their cash conversion cycle, which boils down to fixing audit exceptions quickly.  We will keep chipping away at more and more automation to continually reduce the time to fix exceptions.  

Some of the work to prevent audit exceptions is leading us to drive data capture, and decision making well before the invoice is received.  By helping our clients improve the accuracy of their data earlier in the shipment lifecycle, we can make even more strides to improving their cash conversion cycle. 

 Finally, we are developing a rich set of analytical tools that utilize data to drive better decisions, build machine learning models, and help our clients focus on the business of managing freight, without the mundane busy work of back-office operations. 

If you would like to learn more about Navix and how we are helping our customers reduce their DSO and scale profitably, you can contact us here. If you want to follow Kevin for more of his insights, you can connect with him on LinkedIn.