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Episode Info:

Michael Mina is a business analytics and data science professional who has a proven record of creating solutions in banking, consulting, insurance, healthcare management, and academia. Currently, he is a VP of Decision Science and Analytics at PNC Bank as well as an Adjunct Professor of Analytics at Cleveland State University. He joins the podcast today to compare and contrast decision science and data science and discuss how analytics improve customer experience in the financial sector.

Michael has not yet found universally accepted definitions of “data science” or “decision science,” but he shares his perspective of what exactly they mean. He talks about where these sciences fit into the four segments of analytics. Michael further illustrates these terms by telling us about an exercise he plans to give his students.

To help professionals bridge the gap between what they see in data versus what they need to explain to their team members who aren’t as proficient, Michael says to focus on what the end users are after. He lists questions to ask ourselves to help with this before giving more presentation tips to allow for better comprehension.

Being involved in several misadventures throughout his career, Michael describes one in which he built a data mart without telling his manager, and another in which a company was $12,000,000 out of balance. He discusses what he has learned from these experiences and expresses that sometimes not every problem is even worth fixing.

Customer journey analytics is a growing area that Michael is excited about heading into 2020. He speaks to the importance of customer experience and explains the usefulness of Net Promotor Score. We also hear about the prospect of linking key performance indicators to the customer experience.

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