Different Career Paths Reach Common Ground

Earlier this spring, I received an invitation to chair a panel entitled “How Artificial Intelligence Improves the Call Center” at the SpeechTEK 2019 Conference in Washington, D.C. [1]. This was a surprise, because: (a) my knowledge of artificial intelligence is pretty thin, and (b) although I had once been active in the world of call center operations, I have been out of that game for quite a while.  

When I reached out to conference chair James Larson, he informed me that Dan Coyer from West Corporation had nominated me for this role. This too was surprising; although we have been casually connected on Facebook for several years, I had not actually seen or spoken with my college classmate Dan in decades. Intrigued, I decided to accept this unexpected invitation.

Both Dan and I grew up in northern Minnesota, and had met soon after arriving at school in the fall of 1982. While we had not been close friends, our paths crossed frequently during our time together on the bucolic St. Olaf College campus in the small Minnesota town of Northfield, famously known for “cows, colleges and contentment” [2]. Upon graduating, however, I lost track of Dan for a very long time. At SpeechTEK, we finally had a chance to catch up after more than 30 years. As we talked over drinks, it seemed remarkable that we had ended up there together, for we had taken incredibly different journeys since leaving school. 

Different Journeys

At St. Olaf, I studied math and economics, while Dan was a pre-med student majoring in religion who also spent two semesters studying in Asia while investing much of his time on campus training in the dance studio. After graduation, Dan apprenticed with the San Francisco Ballet Company while I was studying operations research just down the road at Stanford. But while I have been rooted in the Bay Area working on mathematical models ever since grad school, Dan’s geographic and professional trajectory has been far more interesting.

After leaving the Bay Area, he spent several years in Alaska (working as a field researcher for the State of Alaska, serving as a scientific diver on research vessels, and managing commercial fisheries for sustainable harvests), returned to Minnesota (where he had been an executive assistant and a business analyst while also working toward an MBA), spent a sabbatical in India, and then lived in Green Bay, Wis., for many years (where he had managed a retail store and was a top-performing telephone salesperson). Most recently, he had been living in Tampa and working remotely as part of a global team. 

Points of Commonality

There were also some points of commonality. We found that we had both been involved in call centers in the same year (Dan through a temp job that led to his first role as a data analyst and me as a consultant working on call forecasting and agent scheduling); that we had both taught ourselves Microsoft Access to capture and analyze data in the mid 1990s; and that we had both been exposed to quality management and six sigma methods (Dan became a certified Six Sigma Black Belt and Project Manager while working for American Express in Minneapolis). Both of us had a wide-eyed curiosity about machine learning, and both of us were now part of the world of business analytics and data science, which is what ultimately led us to this conference.

For the past several years, Dan has been a senior analyst within the Center for Data Science at West Corporation, a large global firm that provides its clients with a variety of communications services, including call center outsourcing. In this role, Dan is involved in developing a system to provide call center agents with real-time coaching that is customized based on data captured during the same phone call; this was the work he presented during our panel session a SpeechTEK. In particular, he noted that several of West’s clients were providing their customers with low-differentiation products and/or services, and as such the quality of service was a very important element of the customer value proposition. Improving that service experience through real-time agent coaching was therefore a very big deal.

Afterward, Dan told me more about his role within West’s Center for Data Science. “My job is to keep our project pipeline full by evangelizing to internal customers, identifying processes that can be improved, translating business problems into technical problems, helping to liberate and democratize the available data, and creating compelling data visualizations,” he explained. “There are lots of people in my group with academic backgrounds like yours, and I really appreciate the high quality standards that they have. I’ve learned a lot from working with them.”

Lessons Learned

In turn, I learned a lot from the time I spent with Dan. First of all, it had quickly become clear to me how valuable it is to have someone with such a unique background as part of a data science team, for his life experience had given him a much different perspective than those of us with only traditional technical training. In particular, his front-line sales and customer service experience makes him a far more credible advocate for data-driven decision-making with managers and executives who have operational responsibilities. Sadly, I doubt that I would have been wise enough to recognize the value of someone like Dan back when I was leading an analytics consulting group, though I definitely do now. My sense is that there are still too many technical team leaders – and faculty members -–who do not appreciate this.

Secondly, I marvel at the creativity, courage, tenacity and resilience that he has demonstrated over the course of his career. Dan’s journey reminds me of a favorite quote from Scott Hartley’s wonderful book, “The Fuzzie and the Techie: Why the Liberal Arts Will Rule the Digital World” [3]: “We are doing a disservice to our young people by telling them that life is a straight path.” Dan’s success is a strong testament to the liberal arts promise that the real value of education is in learning to learn. Stuck for far too long in my engineering and b-school bubbles, this was a much needed reminder for me.

Finally, Dan’s story made me think of Jarno Duursma’s keynote presentation at the SpeechTEK conference, provocatively titled “Algorithms in, Humans Out?” [4]. After describing the breadth and speed of advances in algorithmic decision-making, Duursma described how important it is that we develop our own sense of being human – particularly empathy, compassion, warmth and affection – in order to overcome the many potential drawbacks of our increasing dependency on such systems. And the more we step outside of the world of technology – and my sense is that few people in the world of data science have had a richer set of personal and professional experiences than Dan Coyer – the more wisdom we will have to help us develop these uniquely human capabilities.

References

1. http://www.speechtek.com/2019/
2. https://www.nytimes.com/1986/08/03/travel/cows-colleges-and-contentment.html
3. https://www.goodreads.com/book/show/30971649-the-fuzzy-and-the-techie
4. https://speechtek.brightcovegallery.com/detail/videos/speechtek-2019-keynotes-sessions/video/6032546829001/opening-keynote:-algorithms-in-humans-out?autoStart=true