At the heart of Minnesota, Olufunmilayo Ogunwole is transforming supply chain operations at one of America’s largest farmer-owned cooperatives. A quiet revolution is underway, not driven by fanfare, but by the precise, forward-thinking work of a Nigerian-born data scientist reshaping how the agribusiness giant sees, senses, and steers its logistics systems.
Since joining the firm in late 2023, Ogunwole has become one of the analytical engine behind sweeping operational changes from improving operational visibility and automating repetitive task. Her approach isn’t just technical, it’s transformational.
“In supply chains, data isn’t just numbers. It’s signals,” she explains during a walk-through of the analytics lab she now leads. “The challenge is recognizing the signal early enough to act.”
A systems engineer by training and a strategist by instinct, Ogunwole arrived with more than a decade of hands-on experience navigating the messy realities of warehouses, freight corridors, and supply disruptions. From handwritten ledgers in Lagos to coordinating cross-border shipments in Europe, her journey has always been about turning chaos into clarity.
“You gain a healthy respect for broken systems when you’ve worked inside them,” she says. “That’s where my obsession with fixing things began.”
Olufunmilayo’s career began far from code and cloud platforms. Instead, it was grounded in the lived frustrations of delayed deliveries and paper-based inventory tracking. By the time she earned a Master’s in Supply Chain Management from the University of Minnesota, she had already witnessed the human cost of inefficiency in lost revenue and livelihoods.
Upon joining the Minnesota-based cooperative, Ogunwole immediately rolled out robotic process automation (RPA) to streamline repetitive tasks like reporting, data extraction, and scheduling. Then she developed custom workflow applications using Microsoft’s Power Platform—ushering in faster, more agile operations and real-time decision dashboards that now reveal vulnerabilities before they escalate.
But for Ogunwole, automation was only the beginning.
She contributed to supply chain visibility by building interactive dashboards, advanced and efficient semantic models, attended and unattended robots with platforms like Snowflake, SQL, UIPath and Dataiku. Her work connected disparate datasets—from inventory, trade, operations and logistics to weather and supplier behavior—into a unified ecosystem.
“She’s not just deploying tools,” said a colleague. “She’s shifting the mindset—from reacting to anticipating.”
Her impact also runs deeper than analytics. Ogunwole is bridging more than systems; she’s bridging people. Developers, analysts, and warehouse staff now collaborate in the same room, walking through predictive models in plain language. She advocates for tech that reflects on-the-ground realities, not just elegant theory.
“Elegant systems that confuse the end user? That’s a failure,” she says. “Data should reflect people, not alienate them.”
She also champions a human-centered approach to automation, mentoring junior analysts and early-career professionals. Her philosophy is simple but powerful: automation shouldn’t replace people; it should free them to think, solve, and create.
Her long-term vision is bold yet practical: to help transition the organization from a reactive, break-fix supply model to an intelligent, self-correcting network, one that senses disruptions early, adapts in real time, and continuously learns from itself.
“Technology moves fast,” she says, eyes on the dashboard lighting up beside her. “But transformation? That’s about clarity, not speed.”
In a business that moves billions in grain, fuel, and agriculture across continents, the most meaningful innovations don’t always make noise. They unfold in silence, in strategy, in models, in carefully written code that prevents tomorrow’s failures before they surface.
And sometimes, they come from a Lagos-born technologist like Olufunmilayo, quietly helping America’s supply chain see farther, and act faster than ever before.
