All of us are limited by what we can imagine. And that is often influenced by what we have seen or how we have worked in the past.
How do we develop a “what if” skillset? How can we let our imaginations develop the future of our businesses? And, how can we remove the limits to our understanding of what’s possible?
If all we can imagine is what we already know, the impact of Artificial Intelligence is limited to speeding up a process that we are already doing. Can we do better?
Imagine a Distribution company with many warehouses. It’s pretty common for each warehouse to maintain an inventory, using the traditional planning and thinking processes of a standard supply chain. There are exceptions of course, and I’m not here to provide a “cookie-cutter” solution, but to cause a shift in thinking so you can find your own solution.
Some companies have shifted to a centrally managed planning team. But often still limited by placing orders separately for each warehouse.
The ensuing results: 1. Personnel are still managing the warehouses separately, just doing it from a central location. 2. The transfer between warehouses still occurs, and it’s still chaotic. 3. Inventory balances are still fluctuating wildly, and the team is fully reactionary.
A solution that could make sense is to setup vendors to supply one warehouse and then use internal transfer processes to move inventory around the network. Consolidates supplier orders into larger orders shipping to one location. Central Distribution Center to Regional Warehouse to Local warehouse.
A follow on to that is to use any warehouse as a hub and all other warehouses as the spoke. Same functions as above, but not one fixed Central Distribution Center, but rather each regional warehouse can function as the CDC for certain parts.
And a follow on to that would be to make the “ship to” address flexible, so the supplier can ship to any warehouse as needed. Sometimes they ship to Chicago, sometimes Atlanta, and sometimes Seattle. And in turn each receiving warehouse becomes the source to supply any other warehouse. Constantly adapting to the current situation and trend.
What if we could determine the “ship to” address the day before it ships?
I believe this last step would be very hard for an individual to manage. But for A.I. this is now a possibility. Probably not even considered difficult.
Is anyone “rethinking” in this way? It can be hard to imagine what you haven’t done.
John Melbye, DDPP, DDDP, DDOP, DDLP
Become Demand Driven
