Cereal manufacturer General Mills is embracing generative artificial intelligence (AI) at multiple levels throughout its organisation. In addition to rolling out generative AI chatbots in the form of MillsChat in February, the company is leaning into using the technology to transform its supply chain and procurement functions.
The company has been an especially enthusiastic adopter of the technology. In many ways, this isn’t very surprising. General Mills and companies like it are reliant on far-flung agricultural supply chains. First, the years-long war in Ukraine has destabilised one of the world’s biggest bread baskets. The war is conspiring with the consistently worsening effects of the climate crisis to make life especially challenging.
As a result, General Mills is throwing itself headfirst into an AI-centric transformation, pursuing efficiencies and added visibility.
From episodic to dynamic procurement
By combining enhanced data sets within General Mills’ procurement function, Paul Gallagher, General Mills’ chief supply chain officer said in a recent episode of The Gartner Supply Chain Podcast that a pilot program managed to realise more than 30% waste reduction in areas where the data has been implemented. As a result, the program is being rolled out across more areas of General Mills’ procurement and supply chain process.
“Historically, we would have rotated through cycles of category should-cost productivity models with potentially missing or delaying savings,” said Gallagher. “Our new reality is that we see this always-on approach driving incremental value, and the ability to react faster [when] we get supplier disruptions or market dynamics change.”
The technology—an AI solution called ELF developed partially by controversial data analytics company Palantir—was initially deployed in General Mills’ U.S. human foods business. The division experimenting with ELF reportedly handles approximately 3,000 orders each day. Over the course of the six month trial, ELF made roughly 400 suggestions to the human foods team. According to Gahhagher, 70% of these suggestions were accepted automatically. The resulting efficiency and productivity gains are, he claims, leading to daily benefits worth tens of thousands of dollars.
“What we’re seeing is that we’re moving from a world where people make those decisions supported by machines to one where the machines make most of the decisions that are guided by people,” Gallagher enthuses. He adds that “this intelligent execution at scale is where we’re seeing the benefits come through to our supply chain.”
Generative AI taking a bite out of the world’s biggest FMCG supply chains
General Mills isn’t the only organisation turning to generative AI in the hope of radically enhancing their supply chain.
Last year, Mars announced plans to explore a wide variety of generative AI applications. “Artificial intelligence has enormous potential to help companies become more efficient and productive and to work at unprecedented scales and speed,’’ a company spokesperson said in an interview with CGT. Mars is already using AI to predict whether cats and dogs could develop chronic kidney disease. It’s also using the technology to help sequence pet genomes to provide individualised nutrition and care. And, of course, AI is helping unlock efficiencies in Mars’ manufacturing operations through digital twin technology.
Colgate-Palmolive is using generative AI as a way to generate internal e-learning documents and automate marketing content creation. Nestle is just one of several large FMCG companies leveraging a generative AI platform called Tastewise. Along with Mars and Campbell’s, among others, it’s using the platform to provide consumer feedback insights and generate recommendations on everything from procurement to product development.
- AI in Supply Chain
- Sourcing & Procurement
