Tom Weir, Chief Operating Officer for CSafe Global discusses why it has taken so long for AI to come to the cold chain industry and what it means now that it’s arrived.
Artificial Intelligence (AI) has been a discussion topic since before many of us were born. Granted initially it seemed to be limited to science fiction books and movies, but it has very quickly become a reality. Whether it’s Siri, Cortana, Google Assistant, Alexa, navigation systems with traffic updates and re-routing suggestions, mobile banking, online search suggestions, social media photo tagging … most of us are using some form of AI every day. But it hasn’t made an entrance into the cold chain until now.
Why did it take so long? And what changed to make it viable? Both are good questions and the answers come down to complexity. Historically, the cold chain portion of the pharmaceutical market was relatively easy to plan for. There were a handful of manufacturers shipping product to relatively pre-defined locations. That has changed in recent years. With new innovations in pharmaceuticals and biologics, the market is growing. Not only are we seeing growth in the number of companies manufacturing pharmaceuticals, but we’re seeing them expand their geographic reach as they’re able to get approval to manufacture and distribute their therapies in more countries.
To add even more complexity, we must contend with more customs clearance processes, government trade restrictions, political disruptions, natural disasters and now, a pandemic. Predicting where and when a container might be needed with all of these variables is more than any basic computer software or human brain can handle. Which is where AI finally comes into the picture for cold chain. Forecasting container needs has become critical to ensuring that the cold chain remains efficient and cost effective.
The million-dollar question is, “Does it work?” And I can tell you the answer is yes. The operations team at CSafe implemented an AI lease forecasting system last fall and we realized benefits quickly. The changes we’re making as a result of the forecast information aren’t revolutionary, but we would never have had the ability to make them without this system.
For instance, because we can predict when and where containers will be needed weeks in advance, we can use alternate modes of transport to get them there. It may take longer, but it’s more cost effective and we have the time. If on the other hand, the goal is speed to deliver a container urgently, to the tool adjusts to find the best route based on time spent en route, at customs, etc. This has allowed us to meet every lease request we’ve received even during a pandemic that has severely challenged the supply chain.
Your next question is undoubtedly, “How does it benefit the customer?” Very similarly.
- The containers they need are available where and when they want them – every time.
- Customers may see reduced lease prices and fees with creative container movement.
- Difficult, one-way drops are now possible.
- Long-term lease customers can look for recommendations to optimize their internal logistics.
It’s absolutely a win/win scenario for all involved.
Of course, the system is new to us and to the cold chain industry as a whole so we are still tweaking, improving and learning how we optimize the system for even better results. But we are thrilled that this latest investment in innovation for the cold chain is paying off even better than expected.