There are so many exciting emerging technologies in supply chain and logistics today, but which ones will be the best fit for your company’s business strategy? Which technologies have the greatest potential to deliver the value you need, both in the near and long term? How do you prioritize investments in these technologies and roll them out successfully? Those are some of the questions I discussed with Ty Bordner, SVP of Marketing & Business Development at Amber Road, in a recent episode of Talking Logistics.
On the cusp of a revolution
There are so many emerging technologies out there that you get the sense we may be on the cusp of a revolution in supply chain management, so I began our conversation by asking Ty if he is seeing this. Ty agrees and says, “The biggest buzzword right now is digital transformation. We define this as creating a digital model that represents all of the functions that make up a company’s global supply chain, particularly execution processes. That’s no trivial thing, but once you’ve done that, you can better collaborate, automate and analyze your supply chain data, and that creates value. That value includes driving new efficiencies, mitigating risks and having the agility to react to micro-level and macro-level changes.
“So, yes, I do think we are on the cusp, but it won’t happen overnight. It takes time and investment.”
Where does blockchain fit?
Another big buzzword today, and the least understood new technology, is blockchain. There are a lot of opportunities in the global trade realm because of all the data, documents, financial transactions, and trading partners involved. I asked Ty where he sees blockchain fitting within supply chain management. “I think that’s still an open question,” explains Ty. “There are applications that do fit the blockchain model, like those focused on trading or exchanging assets between parties, and those assets can take many forms. An export license, for example, can be an asset, so is a container […] Ultimately, if all parties are winning and gaining value using a blockchain app, then those apps will survive and grow.”
Ty also discussed an underlying success factor for any blockchain application: “A lot of the blockchain apps out there, especially in the global supply chain world, their fuel is digital data. Once you’ve created the digital model and automated your global supply chain, you have robust transactional and master data that blockchain applications need to drive value by automating the exchange of data and documents between trading partners.” In short, blockchain applications need accurate, timely and comprehensive data or they are going to be “garbage-in, garbage-out” like any other application.
AI and Machine Learning
One area where venture capitalists are placing a lot of their investments is in artificial intelligence (AI) and machine learning. I asked Ty for his thoughts on this. “Because AI and machine learning are hot topics, every software company is conflating these technologies with the automation they are offering when it is really just a small subset of what they do,” notes Ty. “A classic example of machine learning is combining an historical perspective of the ingested data with other relevant information like weather to better predict the future, such as the ETA [estimated time of arrival] of a shipment.”
One of the problems is that the terms AI and machine learning are often used interchangeably when they are really quite different. Machine learning is actually just a subset of AI and many of the current predictive applications are being called AI when they are simply machine learning. Ty agrees, but points out, “AI is really a high bar that few, if any, applications are achieving today. While there are machine learning applications delivering value already, most companies aren’t even taking advantage of all of the automation possibilities available from their current enterprise applications.”
The Internet of Things (IoT)
The Internet of Things has been around for a while and encompasses many areas, so I asked Ty if there has been much progress with IoT in supply chain. “I think there has been,” he says. “In supply chain it is mainly about where is my shipment, what shape is it in, has it been tampered with, and so forth. IoT allows companies to collect more information faster than traditional EDI or even XML transactions. This ability to analyze real-time freight data is driving value.”
Big Data and Analytics
This need for companies to make smarter decisions faster leads to our next topic of Big Data. Are companies taking advantage of Big Data possibilities? Ty is skeptical. “Companies think they can go out and buy a Big Data tool and that will solve their problem. But it requires much more than that. First, you need the right data structure because transactional data doesn’t scale. Next, you have to have accurate, timely data as we discussed earlier. If you have those, then an application can help you analyze the data to create insights.”
What does the future hold for the application of these technologies in supply chain management? How should companies prioritize their investments and how can they successfully roll them out? Ty and I discussed these questions and more, so I encourage you to watch the full episode for all the details. Then keep the conversation going by posting a comment and adding your own thoughts and experiences.