How Unilever's FIFA Product Plan Came to Life With AI, Data, Digital Twin Tech
Over the years, Unilever has stepped up its supply chain to meet ever-shortening demand cycles for consumer brands.
Where months were once the acceptable timeline to meet demand, it's now merely hours. As a result, the company has shored up its predictive capabilities while at the same time optimizing its supply chain production cycle.
It has reduced its concept-to-pilot timelines to 12 weeks and is building more predictive customer operations and stronger digital capabilities across its teams, according to Vicky Cuthbert, chief product supply chain officer for Unilever's personal care business.
In a company blog post, Cuthbert shared details about Unilever's ongoing investment in its people, AI and digital technologies to improve decision-making, respond to demand faster, and elevate customer and consumer experiences.
"We have created a tech ecosystem that’s allowing us to identify potential disruption early, assess scenarios and make faster, better-informed decisions that help us stay future-fit," said Cuthbert.
An example of this is the company's sponsorship of the FIFA World Cup, for which Unilever activated 35 brands with 180 limited-edition products across more than 120 countries and millions of retail locations.
"When we know what products each brand is promoting, we need to ensure the material sourcing, manufacturing and logistics capacity is in place to produce and deliver them," said Cuthbert. "Once the production plan is in place, the focus shifts to execution: getting the right products to the right retailers, at the right time — in many cases in display executions."
For the tournament, this included hundreds of thousands of small "mom and pop" stores along with major retail customers.
Following the extensive marketing push, which was activated on social media, in stores, out-of-home and on TV with more than 50,000 creators globally, the company had to be prepared for a demand spike at any time. This meant keeping a close watch on which winners' products it would have to quickly produce.
Unilever's factory in Raeford, N.C., played a critical role in producing items for the FIFA campaign, using digital twins — computer simulations of manufacturing processes — to optimize the planning and production of personal care products, resulting in a 20% reduction in waste and a 10% uplift in capacity.
The company pairs AI with advanced analytics. One example is its Forecast Engine Utility, which combines machine learning and data science to generate a 104-week forecast every week across more than 5 million product-customer combinations in 40 operating markets.
"Data and AI enable us to process much more information than would possible manually, significantly improving the accuracy of our forecasting and scenario planning, as well as optimizing logistics routes," said Cuthbert.
Manufacturing will only continue to become increasingly predictive and scenario-based, according to Cuthbert. She said Unilever is rolling out more than 40 AI-enabled digital twins across its network over the next 18 months to help teams identify issues earlier, simulate scenarios faster and make smarter decisions.
"The biggest opportunity isn’t just deploying AI," she emphasized, "it’s fundamentally redesigning our underlying processes so people and AI can work together effectively."
