This is a story about failure. But it’s not what you think. It’s a tale about someone putting themselves in the middle of problems while embracing the worst outcomes and turning them into the best solutions.
This is Will Cooper’s story and what makes Cooper exceptional (a word he’ll not enjoy reading) is his ability to strip all pretense away from things that are broken. But he doesn’t stop there.
He’ll dig. And he’ll dig deeper than you.
He’ll ask basic questions, pushed by a voice inside telling him that his conclusions still may be wrong, propelling a manic cycle of not wanting to stop and always questioning whatever is found.
But that’s what failure can do. It has a way of forming unusual relationships, skewing perspectives and eroding confidence. Because if that’s all you work on (failure) that’s often all you feel.
“It’s exhausting,” Cooper admits. “I’m just never really sure and it frustrates the heck out of me when things don’t work.”
This all may come across as bleak, but Cooper doesn’t see it that way. After all, 20-year decorated careers are rarely carved from misery.
It’s Cooper’s level of commitment, combined with an inherent drive for understanding, that has built John Deere’s electronics analysis lab at Intelligent Solution Group-Fargo’s facility in North Dakota, and benefitted those who have come to expect an industry-leading level of quality in our products. It’s also what earned Cooper a 2021 Physics of Electronics Materials Fellow Award from John Deere.
For nearly two decades he’s painstakingly worked to limit parts failure. His “test until it fails” approach allows him to study breakdowns in materials and execution and prevent them from reaching customers.
Fargo’s facility is built for this, a lab coat assembly line of electronic components—from circuit boards to resistors to capacitors. It is here that the brains of John Deere’s software are born.
He is given much credit for his work on Deere’s vision processing unit (VPU) which helped in the development of See & Spray™—the industry’s first spot-spraying solution that uses machine learning to distinguish between green weeds on fallow ground.
For Cooper, advanced engineering manager, the curiosity to understand how things worked, or didn’t, and how people sorted through facts, or didn’t, has always intrigued him.
“I’ve always thought of it as ‘what the heck is going on here? How does it work? Why does it work that way?’” Cooper said. “And I’m interested in how people’s minds work. I’m not necessarily interested in that person over there, but in general I’m often just very curious about why people believe the stuff they believe.”
With all the questions came the quest to get to the answers. But it wasn’t just the first answer Cooper was searching for. He wanted the next answer and the next answer and the next. To him, there really wasn’t a final answer.
That, he said, can lead to new problems.
“I used to really not get things done. I would never finish them because I would just get into this, ‘How do I do this better?’ phase, instead of finishing it and then going back to it.”
For a man who has spent much of his career “always worried that I’ve got it completely wrong” you can imagine how it went when he learned he won a Fellow Award from the company.
“I guess I’m more appreciative now—maybe that’s the right word—than I was originally,” he said. “I’m still not comfortable with it. I’ll never be comfortable with it because I still seriously have imposter syndrome. I am more appreciative of the fact that a lot of people must think I did something right somewhere along the line.”