Eric Falkenmayer, Senior Manager of Demand Planning at Not Your Mother's Hair Care, joined Garrett Long on a recent webinar hosted by Consumer Goods Technology.

During the discussion, Eric shared his views on where planning is heading for this high growth brand, and how purpose built AI from Omnifold will play a critical role in their future. Topics discussed include demand planning, IBP processes and how better forecasts will help with sustainability goals.

Annie Anthony, Director of Operations at Caliwater, joined Omnifold’s CMO Garrett Long on the Innovation Stage at CSCMP’s Edge conference in 2025.

During the discussion, Annie shared her journey to change Caliwater’s planning process from spreadsheet chaos to an AI-powered growth engine. Listen in and hear some of her greatest challenges and where they are headed after partnering with Omnifold.

We've written elsewhere about why common tools like spreadsheets fail at demand planning. The short version: they force you to collapse complexity into averages, freeze assumptions at the moment you enter them, and can't model the millions of potential scenarios in modern supply chains.

This piece focuses on what happens downstream when forecasts break down, with real stories from the supply chain teams we've worked with.

We've seen this story dozens of times during our conversations with prospects: a demand planner opens Excel, updates last month's numbers, tweaks a few assumptions, and calls it a forecast. 

If that describes your current process, this piece will explain why even the most sophisticated spreadsheet is fundamentally inadequate for modern demand planning – and what actually works instead.

Anthropic created an LLM agent to run a vending machine in their San Francisco office. This is one of the simplest operations possible: buy products, manage inventory, set prices, talk to customers and try to turn a profit. After the month-long experiment, Anthropic concluded that their agent “made too many mistakes to run the shop successfully”. Specifically, their agent lacked basic business sense, hallucinated critical information, and failed to learn from its mistakes

Demand Forecasting is a hard problem. It’s tempting to think a tool like ChatGPT could make a planner’s life easier.

In reality, a chat interface powered by LLMs (Large Language Models) is not built to solve this problem. It uses the wrong training data, wrong training methods and won’t provide proactive, adaptive intelligence.

When your product sales are growing rapidly, it's great news for the business – but a tough challenge for demand planners.

With Omnifold, you can plan and re-plan instantly, using a self-improving model that understands the complexities of your operations and forecasts down to the finest level of granularity.

Maggie is a growth marketer at ACME. She wakes up to an email from ACME’s CMO:

“Our biggest competitor just announced huge price cuts across the board. 

I will get you 10% more budget for the rest of the month…but you’ll need to guarantee to me that this will hit our numbers. 

Please prepare a proposal for our exec review later today…