One topic that was of interest to a number of people at MAPADOC Connections 2019 was the potential use of Artificial Intelligence (AI) in the supply chain. Since that discussion, I have looked around on the internet trying to understand where the biggest impact might be.
First, what is definition of artificial intelligence? It seems there is more than one definition out there.
Modern dictionary definitions
- AI is a sub-field of computer science and how machines can imitate human intelligence
English Oxford Living Dictionary
- The theory and development of computer systems able to perform tasks normally requiring human intelligence, such as visual perception, speech recognition, decision-making, and translation between languages.
- A branch of computer science dealing with the simulation of intelligent behavior in computers.
- The capability of a machine to imitate intelligent human behavior.
- Build systems that think exactly like humans do (“strong AI”)
- Just get systems to work without figuring out how human reasoning works (“weak AI”)
- Use human reasoning as a model but not necessarily the end goal
Adeel Najmi, Chief Product Officer at Symphony RetailAI, has a definition of machine learning that I like. “Learning occurs when a machine takes the output, observes the accuracy of the output, and updates its own model so that better outputs will occur. Any machine that does this is using machine learning. It does not matter if data science methods are used or not. It does not matter if neural networks or some other form of supervised or unsupervised learning technique is being used. It’s important not to get bogged down on the specific technique. What matter is if the machine is itself capable of learning and improving with experience.”
Bottom line, AI is using the power and speed of machines to gather data, compare and analyze it to understand and solve problems. Think of the great suggestions for additional products when purchasing items on line or, when Google just knows what you want to search for.
How can AI add value to the Supply Chain?
- Demand Planning – take Sage Inventory Advisor as an example. Inventory Advisor looks at your inventory balances and transactions to determine the ideal inventory balance for each SKU, optimal replenishment cycles based on usage, vendor performance and seasonality, and improves customer satisfaction by reducing stock outs of popular items. The more data, the more accurate the forecasts.
- E-commerce Fulfillment – autonomous mobile robots (AMR) are being used in warehouses to automate fulfillment. The AMRs are able to navigate around obstacles and do not require extensive infrastructure. They use “simultaneous localization and mapping (SLAM)” to build and update maps of the environment they work in.
- Increasing Consumer Spend – how many times have you purchased an item recommended by Amazon? Or, watched movies or TV shows similar to others you have watched on Netflix. Or, the most intrusive of all – search for an item on your phone and lo and behold, ads for that item show up on all of your various devices even if they are not and should not be connected!
There are a lot of opportunities for AI in the supply chain. The MAPADOC team will continue to noodle the idea around. Please reach out to me (Siobhan.Finders@MAPADOC.com) if you want to open a discussion.
Funny how when you start digging into things, more and more interesting articles appear. For example, this just popped up on my LinkedIn page –https://www.industryweek.com/talent/blue-collar-ai-can-solve-skills-gap. Hmmm, is my computer “learning” about what I am interested in?