The AI Supply Chain Manager: Issue 16

Our AI Supply Chain Manager for CPG is here 👇

Look at your P&L. COGS. There is so much flowing into this, and it all starts with making sure that every $ of COGS is maximizing the $ of revenue.

And it all starts with demand planning, and then supply planning.

But what’s next?

Well, if you have your plan, you have to actually execute it.

You know the PO you need to place? Great. TO is next. Now book your truck and make sure delivery is on time.

The real lever is not only to make an optimal plan, but to fully optimize it down to the last detail.

That means:

1. Picking the best carrier for future POs and transfers

2. Making sure you have the best raw materials at any time

3. Making sure you do not pay unnecessary coman premiums

Imagine a world with many Spherecast orbs interconnected – everyone working together to solve their gaps. Production slots are assigned optimally to every need, for every CPG brand.

Comans have visibility into the future, thus being able to source raw materials in time without overstocking.

Imagine a CPG network where everybody benefits from each other. This is comparative advantage applied to CPG - David Ricardo’s principle made real.

No more freight premiums, co-man surcharges, write-offs from mis-forecasted RMs, or cash trapped in the wrong warehouses.

Spherecast might be the answer you’re looking for.

Think about a world where:

• 100% of your POs are automated

• 100% of your TOs are automated

…while making sure 5% of your COGS is reduced by solving local inefficiencies
…while adding 10% of further COGS boost by optimizing global inefficiencies together

Think about solving the bullwhip by being part of a consortium.

One last thing I want you to think about:

Why is the procurement price of your finished good not the sum of its raw material prices?

…and what prevents the finished good price from converging to that sum?

See you next time!
-Leon