LEARN BY TRIAL AND ERROR
Jaime Petkanics was a basic Excel user when she started her f irst job out of coll ege. As a recr uiter for J PMorgan Chase, data analysis wasn’t one of the required skills.
However, a few months in, she was asked to build an Excel model t hat would track and report the success rates of campus recruiting efforts. “I was totally out of my element,” she admits. “Excel is not a core part of a recruiter’s job. I was focused on hiring people – that’s what I was being measured on.” But Jaime had an interest in analysis and wanted to prove herself as a newcomer.
She started by learning as much as possible on her own. She found tutorials on Google and watched instructional videos on YouTube. But she still struggled. “When I got stuck, I would ask bankers.
They build models every day, so I was able to leverage my connections and f ind people who had the right skills,” she says.
Over the course of two weeks, Jaime developed the model. “I didn’t get it perfect the f irst time.
There were mistakes in the formulas and people found errors,” she says. But she continued to ref ine it, and because of her success, others asked her to take on similar projects. “Once people knew that I could pull data together quickly – and make sense of it – I started to get a lot of requests.”
Jaime admits t his t r i al- and- error approach wasn’t the most effective way to learn Excel, but given the immediacy of the need, it was necessary. By the time she left the job almost three years l ater, Excel and data analytics were strengths that helped her land her next position.