Meet a Data Scientist: Q&A with Margaret Potter | Calabrio

Meet a Data Scientist: Q&A with Margaret Potter

 In Calabrio News

I sat down recently with Calabrio’s Margaret Potter, data scientist, to discuss the importance of data science and analytics to business. In this Q&A, Margaret shares her unorthodox journey to becoming Calabrio’s resident “math lady,” and why the people behind the tools are still the cornerstone of success when it comes to analytics.

Q: Tell me a little bit about your background. Anything unexpected?
Margaret Potter, data scientist at Calabrio

Margaret: I came to data science pretty late. I worked as an architectural drafter, and I loved solving spatial problems and working with clients who were remodeling their homes.

I went back to school to study mathematics after the market crashed to become a math teacher. Becoming a data scientist wasn’t on my mind, and I never expected to love it so much. Every day I have problems to solve, and every day I’m trying to help real people improve their businesses. In some ways, it’s a lot like my previous work.

Q: What first interested you about data analytics?

Margaret: I started with the development team that works on Calabrio Workforce Management (WFM). We began talking about the potential uses for all of the data that gets collected in WFM. We would come up with a really cool idea, and then someone would eventually say, “Yes, but that’s really analytics, not WFM.”

It made me hungry to work on those problems.

Q: Why is data analytics an important field?

Margaret: For a long time, statistical tools have been used to describe and interpret past events. Data analytics in its current state is about so much more. We’re using it to predict things.

Sure, forecasting is about predicting, but it’s usually about predicting how much of a resource we need, like contact center staff. We’ve been doing that for a long time and we’ll continue to do that.

Analytics is different. We’re using analytics to predict things that can affect how we do business. For example, in Calabrio Analytics we can predict call evaluation scores. Instead of just scoring a random sample of calls, we score all the calls, and an evaluator then scores a small random sample to verify the auto-scoring. That way evaluators can concentrate on problem calls. This is a fundamental change in how that evaluator approaches his or her work; it’s a change in process.

That’s the other thing that I love about data analytics—it has the potential to make each of us more effective at our work—more relevant.  We help businesses take customer interaction data, find patterns in the data, and use those patterns to better understand their customers. Ultimately, we want our customers to find ways to use their data to make their businesses better—to create more efficient workplaces with satisfied customers and engaged employees.

Q: What’s one misunderstanding someone has had about your role?

Margaret: People seem to think that because I love math and working with data that I’m not a people-person. I love interacting with people, and I’m fascinated by human behavior. Part of what we do at Calabrio is to ask questions about human behavior (usually agent or customer behavior) and then look to the data for an answer. I love connecting my nerdy, math side to my human side. That’s one of those things that brings me joy in my work.

One more thing about analytics in general. Analytics isn’t hocus pocus. We use known, reliable predictive models (machine learning models) and some more traditional statistical models.

Q: What’s your favorite part of a new project?

Margaret: I love the trajectory of a project. First, we’re in the dark and everything is poorly defined. By hashing it out, the team gives a project a sense of direction. Then we start exploring the data trying to figure out things like, “Are we right?” and “Can this really work?” Once we’ve done that, we get to work on the next problem—how can we put this in the product so that it’s actually useful to people? Watching a project move from something shapeless and nebulous to something well-defined and useful is very rewarding.

Q: What does a business stand to gain from investing in analytics? What could they lose out on if they didn’t?

Margaret: A business leader who decides to forgo data analytics isn’t empty-handed; they can still make decisions informed by years of experience. That’s valuable and shouldn’t be overlooked.

Your competitors have access to the same tools that you do—both the information from years of experience and the information that can be extracted from customer data. Ignoring one of those tools could leave you at a competitive disadvantage.

Analytics will never replace people, but it will make people better at their jobs. With analytics tools, business leaders now have access to solid data on which to base their decisions, rather than hunches. Don’t ignore your business expertise, but make sure you supplement it with insights from the data you are already collecting.

Q: What’s one tip you might give a business about how to approach advanced analytics?

Margaret: Don’t expect to solve all of your problems at once. Start by tackling one problem (or question) and then using the insight you gain from analyzing your data to make a change. Try to choose something simple that will give everyone a chance to see how it works and why it’s valuable.

Change is hard, so set yourself up for success. By starting with small projects, you can begin to incorporate analytics as a natural part of your business process. After a while, it will become a habit and you’ll start asking analytics questions about everything.

Q: When you aren’t working with data, what do you like to do in your free time?

Margaret: I love to walk, which is good because I like cooking and eating good food. I also like to take road trips and see places I’ve never been before.

 

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