We’ve landed reusable rockets. We’ve built cars that drive themselves through city streets. We’ve developed AI systems that can write, reason, and generate in ways that seemed like science fiction a decade ago.
And yet, U.S. manufacturers are sitting on the same inventory-to-sales ratio they had in 1995.
Let that sink in for a moment.
While SpaceX was busy reinventing aerospace from first principles, and while autonomous vehicles were learning to navigate the chaos of urban traffic, supply chain professionals were largely running the same material planning logic codified by IBM engineers back in the early 1970s. The technology stack got fancier. The underlying assumptions didn’t.
This is the trillion-dollar problem nobody wants to talk about — and it’s exactly what Erik Bush, EVP of Internal Operations at Algo, set out to unpack in The Trillion Dollar Forecast, Algo’s ongoing webinar series on the fundamental forces limiting supply chain performance around the globe.
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The ERP Promise That Wasn’t
Cast your mind back to the late 90s. Companies were desperate to modernize. Y2K was looming. Legacy systems were creaking under the weight of the internet era. And in walked the ERP vendors with a compelling offer: one database, fully maintained, infinitely configurable, Y2K compliant.
The business case practically wrote itself.
What followed were multi-year, multi-million dollar implementations that — in case after case — failed to move the needle on the metrics that actually mattered: inventory turns and service levels. Bush watched this play out firsthand during his time as VP of Operations at IBM’s consulting division:
“Three, four years go by, they’re still not live. They spent tens of millions dollars more than they expected to and at the end of the day when it finally goes live, the needle doesn’t move — inventory turns don’t improve, service levels don’t improve.”
Why? Because these projects were framed as IT problems, not business performance problems. As Bush recalls, a CIO told him directly during one such migration: “This isn’t a business project — this is an IT project.”
The supply chain was an afterthought. The CIO was happy. The results weren’t.
Wally Leisure, VP of Business Development at Algo, saw the same dynamic from inside industry:
“Supply chain was just kind of a checkbox, but we were way down on who needed to be talked to in the organization about how to run the business. It was always financially pointed.”
And the ERP vendors weren’t incentivized to challenge the underlying logic. They were incentivized to sell licenses. So they packaged up decades-old MRP methodology in modern UX and called it innovation.
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The Flaw at the Foundation
MRP — Material Requirements Planning — is a seductively logical concept. Know what your customers are going to want. Work backwards through your lead times. Buy, build, and ship accordingly. Everything lines up perfectly.
Except it doesn’t. It can’t. Because MRP is built on two assumptions that simply do not hold in the real world.
The first: that your forecast is accurate. At a category level, maybe. At the item level — the level that actually drives purchase orders — forecast accuracy routinely falls to 50–60%. Every planning cycle, you’re feeding a flawed signal into a system designed to treat that signal as truth.
The second: that supply will behave as planned. Bush puts it plainly:
“It also assumes that there’s not going to be any variation, that every supply order we issue arrives on time and in the proper quantity, every manufacturing order we create gets completed in the proper quality. And we know how brittle of a concept or an assumption that is.”
When you build an entire planning architecture on flawed assumptions, you don’t get better outcomes — you get institutionalized chaos. The famous bullwhip effect, amplified at every tier of your supply chain.
First Principles, Applied to Supply Chain
Elon Musk talks extensively about first principles thinking: stripping a problem down until you hit only absolute truths, then rebuilding the solution from there. It’s how SpaceX concluded that landing and reusing a booster rocket was the key to transforming the cost equation for space travel. Bush sees a direct parallel for supply chain:
“If we could find a way to hold enough stock that we were sure that we would always have the material available, then we could pace to the actual demands that come in and we wouldn’t have to be so reliant on a forecast that’s inherently inaccurate.”
This isn’t a new idea. Taiichi Ohno figured this out in Toyota’s production system decades ago. Kanban loops. Visible signals. Pace replenishment to actual demand, not forecasted demand.
The modern evolution of this thinking — Demand Driven MRP — has been producing results across industries. Companies adopting it are seeing inventory turns improve, service levels improve, and critically, a planning process operators can actually understand and trust rather than a black box generating an endless list of expedite alerts.
The Opportunity Is Enormous
U.S. manufacturers alone are sitting on roughly $1 trillion in inventory. Bush frames the stakes simply:
“If we could free up ten percent of that, it would release a hundred billion dollars that could do something more important for us than collecting dust.”
The technology exists. The methodology is proven. The case studies are accumulating. What’s missing is the willingness to challenge the assumption that this is just how supply chain works. As Bush puts it:
“You have to challenge the assumptions that are holding you back and have the courage of your convictions to move in a better direction.”
The same courage that landed a rocket on a drone ship in the middle of the ocean is available to supply chain leaders willing to ask: what if we started from scratch?
This is the first in a four-part series. The next session goes deeper into the diagnostics — peeling back the assumptions behind conventional forecasting and quantifying the damage they cause.
Watch The Trillion Dollar Forecast webinar series here →
