Cut Excess Inventory, Unlock Cash Flow & Forecast Smarter with Alex Maibaum (#37)

In this episode, I sit down with Alex Maibaum, founder and CEO of Predictive Supply Chain Solutions, a cloud-based software and consulting firm that helps mid-size businesses forecast smarter, cut excess inventory, and unlock serious cash flow. Alex is a supply chain veteran who has operated inside high-growth, hyper-accelerating businesses and built his platform specifically because the right tool did not exist for the operators who needed it most.

This episode is a must-listen for any product-based business owner who is sitting on too much inventory, struggling with cash flow, or trying to get their sales, operations, and finance teams to actually communicate with each other.

We discuss:
– How Alex worked his way through sales, marketing, and warehouse floors early in his career and discovered that the biggest problem in most businesses is not a people problem, it is a data communication problem.
– The ping pong table analogy: why sales and marketing, operations, and finance are constantly fighting each other instead of rowing in the same direction, and how data visualization fixes it.
– Why inventory turns is the business metric that unlocks cash flow, and how converting inventory into cash faster means more capital to grow.
– The 80-20 rule applied to supply chain: why 90% of most businesses' revenue comes from 10% of their SKUs, and how SKU bloat is silently strangling cash flow.
– A four-step framework any business owner can build today using Shopify, Excel, and a 3PL report: establish a source of truth, consolidate purchasing, understand historical sales, and log future big commitments.
– How to use AI for demand planning and forecasting without creating a black box, why asking the model to write a wiki after every build is a game-changing practice, and how to validate AI outputs without being a data scientist.
– Why the black box problem is the biggest risk in AI-assisted supply chain work, and the practical technique Alex uses to keep every model transparent, auditable, and updatable.
– How to think about minimum order quantities, carrying costs, and opportunity cost when deciding which SKUs to keep, cut, or reorder.
– Real examples of businesses that locked in large retail orders with Walmart or Target without planning for them and suddenly found themselves out of stock for six months.
– Where AI is going in supply chain: why demand planning used to require PhD-level data scientists and now any operator can access the same capability.

Ready to work with Alex? Visit predictivescs.com.

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