Kellogg + Noodle.ai
This year Kellogg, the leading producer of nutritious, trusted food brands, is on track to realize millions of dollars in value from their use of the Inventory Flow system of intelligence from Noodle.ai.
The Challenge
The COVID-19 pandemic forced Kellogg to essentially turn off their existing demand forecasting system because it was so wildly inaccurate. Even prior to the pandemic, they had a bias towards carrying too much inventory, which impacted margins by driving up inventory holding costs, working capital, and product obsolescence costs.
On the technology side, Kellogg was challenged by multiple data silos leading to different versions of the truth; legacy systems in data centers; and long deployment times. Planners were faced with ever-increasing product obsolescence costs and potential OTIF penalties.
The Solution
Starting during the 2020 pandemic, when there was extreme volatility in demand, Kellogg first deployed Inventory Flow with three of its brands—Cheez-its, Corn Flakes, and Frosted Flakes. After success with these brands, Kellogg extended the Noodle.ai platform across their entire North American portfolio.
With Inventory Flow, Kellogg got the right products to the right locations – keeping food flowing at a critical time when consumers were struggling to cope with the pandemic. For the first time, Kellogg planners could proactively make highly targeted inventory deployment decisions with prioritized recommendations.
All planners shared one dashboard with every risk measured in dollars, described in probability, explained in root causes, and simulated with actionable workflows – ensuring everyone had what they needed to prevent errors, and able to seamlessly collaborate.
The Benefits
In just three months, Kellogg saw 3X ROI in just 12 weeks, even amid the pandemic. With Inventory Flow, Kellogg significantly:
- Reduced excess inventory.
- Improved fill rates.
- Reduced costs.
Kellogg was able to turn supply chain chaos into flow because Inventory Flow can:
- Inject AI-generated corrective actions into existing systems, automatically resolving millions of imbalances between supply and demand.
- Translate risk predictions to dollar terms, called Value at Risk (VAR), to make the most critical issues easily visible to planners.
- Quickly adjust deployment allocations, shipment expedites, and production schedule changes.
- Track the value of the mitigated risks and capture what portion was a direct result of taking the recommended action.
