Mars, Five Below & Generac: Building Collaborative and Resilient Supply Chains With AI
As retailers and consumer goods companies face yet another year of supply chain disruption, whether from costly tariffs, weather uncertainty or changing consumer preferences, enterprises are increasingly looking to artificial intelligence to help navigate unpredictability and increase resiliency.
While the question of data quality comes to the forefront when building the foundation for AI supply chain investments, Andy Fox, senior director of analytics product organization at Mars Snacking, told attendees at Analytics Unite that the first thing that needs to be recognized is that data quality will never be perfect.
“The first thing that's really important is to build this culture around continuous improvement, data governance and data ownership so everyone from the supply chain operator to the supply chain practitioner to the data scientist who's making the most out of that data recognizes where that ownership is, and that any key stroke they’re doing becomes data. We need to take ownership because we're operating the supply chain of where that data goes.”
Panelists during the supply chain session also shared other factors to consider when deciding how to move forward with AI.
Data’s Role in Combating Disruption
Weather and tariffs are two things that can significantly impact the supply chain. For Neil Bhandar, vice president of IT, enterprise data, analytics and innovation for Generac — an energy technology and backup power solutions business — a weather-caused power outage creates an immediate need for a backup supply.
“Our inventory level, our supply chain preparedness and our customer service teams have to be prepared to respond,” Bhandar said, noting that the company must be able to connect data related to weather, utilities, consumers and demographics so service is restored quickly and accurately.
Kim Sussman, vice president of supply chain solutions for discount retailer Five Below, said the current tariff situation has also shone a light on the importance of having a data strategy and the right data architecture, giving retailers a better depth of understanding about their sourcing and their value chain.
The Build vs. Buy Equation
Don’t fall into the “fear of missing out” trap; avoid making decisions for fear of being left behind if you don’t adopt AI, Fox stressed. Understanding the specific problem that needs to be solved is the first step.
“This is going from saying, ‘I want to use AI in demand sensing’ to ‘I want to improve forecasting outcomes for my customers in different segments and be able to be responsive to demand trends.’ From there, we can start to have the build versus buy discussion,” he said.
Also read: Mars says it is on the cusp of bringing AI agents to its internal platform
Fox suggested scanning the marketplace to assess available solutions, while recognizing that off-the-shelf solutions potentially only put companies on par with their competitors.
AI Case Studies
Digital Twins
At Mars Snacking, an AI-powered digital twin allowed the company to get answers in seconds to questions that would have normally required months to explore, Fox said. It allowed the company to run thousands of scenarios to identify vulnerabilities it hadn’t yet considered around opening a new warehouse or changing its distribution network.
Talking to Data
Generac’s internal AI platform has enabled the company to have natural language conversations. “You can ask it questions like, ‘What were my sales last year?’ and ‘How is the power of the region being affected?’ We’ve uncovered so many new things through that natural language interaction with that data,” Bhandar said.
Training & Development
The technology has helped Five Below train hundreds of crew members at its five distribution centers. Not only has it made the process significantly faster and improved content quality, but it has also helped translate that content for non-English speakers, Sussmann said. AI also has the potential to help the company better model freight flow within the supply chain, she added.
