Featuring: Ryan Carbone (Director of Support & Product Implementation at Inventory Optimizer)
Craig Barnell (Director of Customer Insights at Inventory Optimizer; COO at Fishers Finery)

Every product has an origin story. For Inventory Optimizer, it started with one spreadsheet, a growing brand, and a simple goal: never run out of stock again.

In this episode, Ryan and Craig share how that spreadsheet evolved into a full AI forecasting platform that now helps eCommerce brands stay in stock, cut excess inventory, and scale smarter.

Here’s how Inventory Optimizer began, the challenges it solved, and how it continues to shape smarter forecasting today.

The challenge

When Fishers Finery launched in 2013, the brand grew quickly, reaching $1M in sales by mid-2014 and $2.3M by year’s end.

That kind of growth sounds great, but it created major inventory headaches. Different suppliers, long lead times, and uneven product demand made it nearly impossible to stay in stock.

“We had hundreds of SKUs moving at different rates,” Craig explains. “There was no easy way to predict what we’d run out of or what would sit on the shelf.”

The team built a massive spreadsheet filled with VLOOKUPs, ARIMA models, and custom API pulls from Amazon Seller Central. It worked for a while, but it was slow, fragile, and couldn’t keep up with a business moving that fast.

The solution

After testing more than two dozen forecasting tools, the team found a small QuickBooks App Store program called Stockade. They acquired it, rebranded it to ForecastRx, and started developing something better.

Over time, that evolved into Inventory Optimizer, a platform built on proven forecasting methods combined with AI to make predictions faster, smarter, and more scalable.

“We didn’t set out to build software,” Ryan says. “We just needed a way to stop guessing and to actually trust our data.”

The results

What started as a spreadsheet experiment turned into a platform delivering measurable results:

  • 93%+ forecast accuracy across 4,000 SKUs
  • Dynamic re-forecasting that updates daily when needed
  • Smarter FBA replenishment through Restock AMZ, combining FBA and MCF demand
  • Scalability from 10 to 200,000 SKUs using the same forecasting engine

“Forecasts that used to take a full day now run in hours and with higher accuracy,” Craig says.

What’s next

The team continues to layer in automation and real-time data to make forecasting even smarter.

“We’re connecting more data points every year, including marketing signals, traffic, and conversion trends,” Ryan explains. “The goal is to make forecasting proactive instead of reactive.”

Takeaway

Inventory Optimizer was built out of necessity, by a brand trying to keep up with its own success. Today, it helps sellers forecast confidently, stay in stock across every channel, and free up capital to grow.

Watch the episode or schedule a demo to see how smarter forecasting drives profit.