097 - Why Regions Bank’s CDAO, Manav Misra, Implemented a Product-Oriented Approach to Designing Data Products

Today, I chat with Manav Misra, Chief Data and Analytics Officer at Regions Bank. I begin by asking Manav what it was like to come in and implement a user-focused mentality at Regions, driven by his experience in the software industry. Manav details his approach, which included developing a new data product partner role and using effective communication to gradually gain trust and cooperation from all the players on his team.    Manav then talks about how, over time, he solidified a formal framework for his team to be trained to use this approach and how his hiring is influenced by a product orientation. We also discuss his definition of data product at Regions, which I find to be one of the best I’ve heard to date. Today, Region Bank’s data products are delivering tens of millions of dollars in additional revenue to the bank. Given those results, I also dig into the role of design and designers to better understand who is actually doing the designing of Regions’ data products to make them so successful. Later, I ask Manav what it’s like when designers and data professionals work on the same team and how UX and data visualization design are handled at the bank.    Towards the end, Manav shares what he has learned from his time at Regions and what he would implement in a new organization if starting over. He also expounds on the importance of empowering his team to ask customers the right questions and how a true client/stakeholder partnership has led to Manav’s most successful data products.   Highlights / Skip to:   Brief history of decision science and how it influenced the way data science and analytics work has been done (and unfortunately still is in many orgs) (1:47) Manav’s philosophy and methods for changing the data science culture at Regions Bank to being product and user-driven (5:19) Manav talks about the size of his team and the data product role within the team as well as what he had to do to convince leadership to buy in to the necessity of the data product partner role (10:54) Quantifying and measuring the value of data products at Regions and some of his results (which include tens of millions of dollars in additional revenue) (13:05) What’s a “data product” at Regions? Manav shares his definition (13:44) Who does the designing of data products at Regions? (17:00) The challenges and benefits of having a team comprised of both designers and data scientists (20:10) Lessons Manav has learned from building his team and culture at Regions (23:09) How Manav coaches his team and gives them the confidence to ask the right questions (27:17) How true partnership has led to Manav’s most successful data products (31:46)   Quotes from Today’s Episode Re: how traditional, non-product oriented enterprises do data work: “As younger people come out of data science programs…that [old] culture is changing. The folks coming into this world now are looking to make an impact and then they want to see what this can do in the real world.” — Manav    On the role of the Data Product Partner: “We brought in people that had both business knowledge as well as the technical knowledge, so with a combination of both they could talk to the ‘Internal customers,’ of our data products, but they could also talk to the data scientists and our developers and communicate in both directions in order to form that bridge between the two.” — Manav   “There are products that are delivering tens of millions of dollars in terms of additional revenue, or stopping fraud, or any of those kinds of things that the products are designed to address, they’re delivering and over-delivering on the business cases that we created.” — Manav    “The way we define a data product is this: an end-to-end software solution to a problem that the business has. It leverages data and advanced analytics heavily in order to deliver that solution.” — Manav    “The deployment and operationalization is simply part of the solution. They are not something that we do after;