More and more supply chain leaders are considering incorporating artificial intelligence (AI) into their businesses, but remain skeptical. It’s because they’ve gotten too many sales calls where companies say AI can change the world and magically do all kinds of things.
It turns out it’s easy to sell on the hype, but it’s harder to get results. AI is not a crystal ball, but it can be a powerful tool for organizations along the supply chain. Whether it’s deciding what to keep in stock or absorbing the shocks that are sure to happen, here’s how flexible AI can help you achieve your business goals.
Provide advanced warnings
Our brains can only handle a limited amount of information. It is not our fault; that’s just how we’re wired. We are struggling to make a decision that involves more than 4 to 5 factors. And, because the global supply chain is so complex, managers often have to consider more factors than that.
For example, suppose a customer has 40,000 SKUs and five purchasing managers. This means that each person managed just under 10,000 SKUs each. There is no way they can pay attention to everyone.
A well-trained AI system, however, can handle this level of detail. He can see that a shipment was stuck in customs for three days when it was supposed to clear customs in eight hours. And, he can inform the purchasing manager of the problem and the risk of missing the delivery date. Rather than being caught off guard later after the delivery date, managers can be given a 3-4 day warning to take proactive action.
Decide what to keep in stock
The past 18 months have put unprecedented pressure on businesses to manage supply and demand. Shipments are overwhelmed and supply shortages are everywhere.
The industry has seen this problem arise with an automotive retail group focused on a particular type of service, with other competitors trying to get the same market. The question they were faced with was, we know some products are going to be out of stock, so which ones do we drop?
Using AI models, they were able to double down on the main product and leave everything else in stock. The idea was related to the importance of customer loyalty. They turned scarcity into an opportunity by focusing on the commodities that people loved, and they were the ones who kept them coming back.
Define a new balance
Before the pandemic, the toilet paper market was fairly stable. But no one, not even AI, could have predicted how demand would increase in those early days. However, where AI can come in handy is in determining what future scenarios might look like and, based on your best guess, what would be the best decision for your business.
By examining the “what ifs,” even the seemingly unlikely ones, AI can strike a new balance and help organizations make smarter decisions when the unthinkable happens. In the case of toilet tissue makers, AI can examine whether it makes sense to re-equip everything in the process or re-equip the 20% needed to meet initial demand with the expectation that everything else will return to a baseline level. .
When things are going well, most business supply chains are in fairly stable condition. You can sell 5,000 units one month, 5,500 the next, and 4,500 after, but it’s usually pretty predictable.
The challenge facing the supply chain is that all of this collapses when shocks occur. All well-controlled just-in-time production systems are in chaos. The result is that companies fall back into manual decision making. They go into triage mode and start guessing to find the right next step. But people aren’t good at making thousands of interconnected decisions on the fly, and that’s where automated systems can step in and help stabilize the ship.
An AI horror story from the supply chain world comes when a consulting group told a global logistics company that AI was working overnight and could tell them where each package was going to be, where each trailer was going to be, down to the minute, during the day.
This is ludicrous, of course, as it shows a complete lack of understanding of the supply chain industry, where conditions change by the minute. If someone makes themselves sick or even takes a bathroom break that was not factored into the AI model, the entire model breaks down.
A more flexible approach can be taken, however, by updating these AI predictions as often as every 15 minutes. It’s the type of AI that learns on the job and adapts accordingly. It is not so much a look to the future as a dynamic tool that reacts minute by minute.
To get the most out of any AI tool, businesses need to put their strategy first. Leaders need to agree on what they’re trying to achieve, and then apply AI to help them achieve that goal. Rather than focusing on which package arrives at which scanner at a specific time, focus on reducing overall costs and increasing operational efficiency. If you set yourself a higher level goal and focus on the opportunities, you will often get better results than trying to get everything perfect.