The Great #GrapeNuts Supply Shortage: AI to the Rescue
Artificial intelligence could have prevented the great Grape-Nuts shortage.
In these trying times, many of our beloved brands have seen incredible sales growth – and are now hard to find on shelves (oh no!). A situation that has personally caught my attention is a frenzy raging in grocery aisles ten months into the pandemic – Grape-Nuts is in short supply until the Spring. Twitter is aflutter with the trending hashtag #grapenuts, along with #pandemichoarding and #covidstockpiling. Venerable news outlets like the New York Times, USA Today and CNN.com are buzzing about this shortage. It’s #GrapeNutGate!
How could this happen?
“Supply-chain constraints and higher demand for the cereal amid the pandemic have led to shortages of the product,” Kristin DeRock, Grape-Nuts brand manager for the cereal company Post Consumer Brands, said in a statement on Friday.
“Grape-Nuts is made using a proprietary technology and a production process that isn’t easily replicated, which has made it more difficult to shift production to meet demand during this time,” she said, without elaborating on that technology or process. She said that the company was working “to get Grape-Nuts fully back on store shelves, which we expect to be this spring.”
-New York Times, 1.29.21
What Could Be
Simply put, true AI-powered advanced planning systems can help get ahead of the traditional supply chain questions: What do customers want to buy? How can I get existing inventory to the right place at the right time? Where do I need to manufacture something different? Unfortunately, existing technologies have limitations that are crucial in times of great volatility and uncertainty – navigating between seeing the big picture to all of the 1000s of micro decisions made every day in a supply chain.
AI driven systems offer completely new capabilities to address toughest parts:
- Understanding patterns – After the chaos of March, patterns emerged of products behaving irregularly in similar ways – some initially spiking products rapidly returned to old patterns while others were off the charts with shelves bare. Many companies struggled to diagnose the situation with little idea of where demand was headed.
- Conquering complexity – AI can be used to predict true demand and supply by understanding the inter-relationships between sales, supply, and out of stocks. Most critically, providing insight into where in the midst of 1000s of potential decisions are the smaller set of critical ones.
- Getting ahead of the game – The ability to predict issues in the next 12 weeks and take an AI-recommended action allows teams to get ahead of the game instead of just reacting to stock outs when they happen.
In the midst of volatile demand and uncertain supply, these capabilities are essential to maintain a smooth flow of material and product throughout the supply chain. The old brute force approaches have not worked, so how do we know AI-driven systems can make a difference? We have CPG customers getting 3x ROI within months with AI, driven by improved fill rates, inventory reductions and fewer expedites. We are proud of the role we are playing to keep food on the shelves throughout these challenging times.
The term “supply chain” has gained a ton of general awareness during this pandemic starting with food and critical items like pharmaceuticals, and more recently with the vaccine supply chain. Now, the #GrapeNutGate supply chain has further elevated it to the public consciousness. At Noodle.ai, we’re hard at work, on a mission to ensure every company on the planet is using our AI products, so supply chain stories stop being about customer disappointment, but instead, customer delight.
Request a demo of Noodle.ai’s Athena Supply Chain AI Suite to avoid your own #GrapeNutGate.
- Why ServiceNow and Honeywell Invested in Noodle.ai To Solve the Global Supply Chain Crisis
- Beyond Control Towers – Supply Chain Command Centers
- How AI Helps Supply Chain Leaders Navigate a Turbulent New World: 3 Experts, 3 Perspectives
- Supernovae to Customer Success: A Data Science Journey
- How to Get Actionable Answers to Yield and Defective Production Issues Finally — and for Real