One day I was sitting at my desk at work. I had just assisted a customer with a rental car and explained how I would take care of their medical bills after the car accident they just had. It felt amazing to help someone in their time of need, however I could not neglect a feeling deep in my mind that I knew I was capable of contributing on a larger scale.

Ever since I started working in corporate America, I have been intrigued by the sheer amount of information that crossed my desk every single day. Every phone call, every email, every transaction was an exchange or an acquisition of new information. As an individual contributor for a major insurance carrier, I utilized this data to resolve claims, but I knew it had to be stored someplace else and used for some greater purpose.

What a pity if it just sat in the database, taking up space.

I first dipped my toes into the field of analytics in 2015. State Farm was looking to fill forecaster positions in their workforce management unit. I was already quite tech-savvy and curious, so I applied for the role. I got in. The task was simple – find out how many claim handlers were needed on the phones for every 15 minute interval of the day; to create weekly schedules for 300+ individual contributors in a call center. So I jumped right in, loading pages and pages of data from the telephony system – E-Gain. I’d export the CSV files and plug them into Excel. From there I’d run my calculations and generate the forecasts and dashboards for the management team.

I would make myself available to the leadership team for any real-time troubleshooting. I would dig in to the task queues for the various departments and run reports to determine who was meeting service level objectives. Maybe one team was behind on their estimates, and another team had capacity to help. If there were mass training sessions or holidays coming up, I would adjust the forecasts accordingly. Once a month I would check my work by comparing the forecasted staffing requirements versus the actual figures. My forecasts were close, 90%+ accuracy.

I loved what I was doing. I was making an impact, and improving the efficiency of the company and increasing customer service levels. This was my gig.

A year later the position was abruptly relocated across the country, and I returned to my desk as an individual contributor. Of course I volunteered for as many data related projects as I could, but they were few and far between. In 2018, I decided I was going to change my career trajectory. I looked at my skills, goals, and interests. I knew my heart was in analytics, and I signed up for a graduate certification at the prestigious Emory University. That was only the beginning of my journey… to be continued.