Solving Business Problems With Smarter Data Products with Manav Misra of Regions Bank
Manav Misra
Most data teams focus on building assets — only a few focus on making them useful. Manav Misra, Chief Data and Analytics Officer of Regions Bank, explores what it takes to make data genuinely useful in a complex enterprise. Manav shares lessons from academia, startups and enterprise leadership, walking us through how he applies a product mindset to drive real impact with data in the banking sector.
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In this episode, Manav Misra, Chief Data and Analytics Officer of Regions Bank, explains how a product mindset helps turn data into measurable business outcomes. He shares lessons from academia, startups and enterprise, and explains why starting from the point of consumption accelerates innovation.
Key Takeaways:
(02:25) Falling in love with AI led Manav from engineering to academia and beyond.
(06:16) Startups offer a faster learning curve for early career professionals.
(10:02) Start with the customer problem and keep solutions as simple as possible.
(15:04) A data product must be usable, measurable and deliver real impact.
(19:49) Manav added “analytics” to his title to highlight a focus on business impact.
(23:03) Data product partners bridge tech teams and business users to deliver real value.
(26:19) Starting from consumption ensures governance efforts stay focused and impactful.
(28:28) Federated governance builds ownership and relevance across teams.
Resources Mentioned:
The opinions expressed in the presentation are statements of the speaker’s opinion, are intended only for informational purposes, and are not formal opinions of, nor binding on Regions Bank, its parent company, Regions Financial Corporation and their subsidiaries, and any representation to the contrary is expressly disclaimed.
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Data Masters Podcast – Interview with Manav Misra, Chief Data and Analytics Officer at Regions Bank
Anthony: Welcome back to Data Masters. Today we’re diving into the complex and fascinating world of data in the banking industry—an area we haven’t specifically focused on before. Our guide for this exploration is Manav Misra, Chief Data and Analytics Officer at Regions Bank, one of the nation’s largest full-service banks.
Manav brings a wealth of experience, not just in banking, but also from academia, tech startups, and executive roles at large corporations. He’s passionate about a core idea: making data useful. We’ll explore his journey, how Regions Bank leverages data, his concept of “data products,” and why starting from the point of consumption is key to tackling data challenges.
Anthony: Manav, welcome to Data Masters.
Manav: Thank you, Anthony. It’s great to be here.
Manav’s Career Journey
Anthony: You’ve had a unique career path—starting as a professor at the Colorado School of Mines, co-founding several startups, and holding executive roles at CenturyLink before leading data and analytics at Regions. Can you walk us through that evolution and what each experience brought to your current role?
Manav: Sure. Going back to the beginning—I did my undergrad in engineering in India, then came to the U.S. for a PhD. I took a class in AI and was instantly hooked. I loved the idea of understanding the human brain and building systems with similar capabilities. That led me into academia, where I researched and taught AI.
But academia can be narrow—you become an expert in one thing. I wanted to apply my knowledge to real-world problems. Fortunately, academia allows for some entrepreneurial exploration, so I started dabbling in startups.
Eventually, I left academia and jumped fully into the startup world. AI was going through a “winter” at the time, but data was still very much alive. We built companies that helped customers leverage data.
From academia, I brought a deep understanding of AI. The startups taught me product thinking and customer focus—especially through a consulting-oriented startup. After that was acquired, I joined CenturyLink, a large company, where I learned how to work with stakeholders and navigate organizational dynamics.
I’ve been at Regions for almost seven years now—which is a long time for a Chief Data and Analytics Officer—and it’s been an exciting journey.
Advice for Early Career Professionals
Anthony: I was talking with a recent graduate who was wondering: Should I start at a big company or a startup? What advice would you give someone early in their career?
Manav: There’s no wrong answer, but I recommend starting with a startup. Yes, they can be chaotic and unstructured—but they’re tremendous learning environments. You get exposure to a wide range of tasks, and your survival depends on understanding and delivering for the customer.
The energy and diversity of work in startups provide a fantastic foundation. It’s a springboard to a richer professional experience.
Data’s Role in Manav’s Startups
Anthony: You’ve mentioned that data played a central role in your startups. Can you elaborate?
Manav: Absolutely. My first startup was an e-commerce company where I built recommendation engines. We used transaction and behavioral data to personalize experiences—early for that time.
The second was an enterprise software startup targeting large retail chains. Data was used to evaluate store performance and improve operations.
The third, started in 2009 post-financial crisis, aimed to help banks understand risk more deeply using emerging big data platforms like Hadoop, alongside machine learning and statistical models.
In all three, data was the foundation—even though the business problems differed.
The Value of Useful Data vs. Big Data
Anthony: That’s interesting because the industry often equates “more data” with “better.” But you emphasize useful data. Can you explain the contrast?
Manav: What I tell my teams is: Start with the customer problem. Whether that customer is an internal banker or a retail banking client, everything we build should solve a real problem.
Sometimes, small data is enough. Other times, large data sets are valuable—especially for machine learning and large language models. But the complexity should be hidden behind the scenes. Our job is to choose the right data, software, and models—guided by Occam’s Razor: keep it as simple as necessary.
Defining “Data Products” at Regions Bank
Anthony: You’ve popularized the term “data product” at Regions. How do you define it, and why did you champion it?
Manav: When I joined Regions in 2018, I needed a unifying concept. I wanted the business and my team to rally around something clear: end-to-end software solutions powered by data.
To business partners, a “product” is complete. It evolves, improves, has a roadmap, and is owned. That concept clicked. For my team, it moved us beyond “projects” that get handed off—toward ongoing ownership and improvement.
I coined the term “data product” to emphasize both the product mindset and the centrality of data. While others now use the term differently, our definition is: a complete, user-ready, measurable solution that solves a specific business problem.
Measuring Value and Quality in Data Products
Anthony: So how do you measure quality and impact?
Manav: We created a role called data product partner—essentially a product manager. They focus on customer needs, usage metrics, and business impact.
For every data product, we build a business case. The outcomes may be revenue generation, cost savings, or risk reduction. We track those KPIs quarterly and report them to business stakeholders.
Shifting Away from Source-Based Governance
Anthony: You’ve spoken about how many data leaders start by trying to “fix the data” at the source. You took a different approach. Why?
Manav: Yes—when I joined, I was asked to “fix the data.” But that’s a never-ending task if you start at the source. You’ll spend years organizing data without delivering value.
Instead, I focused on driving value first. We began with consumption: What does the business need? What decisions are they making? Then we worked backward to source, governance, and quality—only for what was needed.
Of course, if there’s a regulatory need, we start at the source. But most of the time, consumption-first creates faster feedback loops, more innovation, and better alignment with business needs.
Data Governance as a Partnership
Anthony: You also mentioned setting up a federated governance model. Can you describe that?
Manav: We established a network of Group Data Officers—people embedded in business units who own or use data. They partner with us to ensure governance and quality.
Because they see how the data is used—in data products, analytics, reporting—they’re more invested in its quality. It becomes a partnership, not a control function.
Closing Thoughts
Anthony: Manav, I really appreciate the time today. What stands out is how you’ve brought academic depth and product-focused startup energy into a large bank—creating a culture of innovation grounded in delivering real business value through data products.
Manav: Thank you, Anthony. It’s been a pleasure. I hope this is helpful for listeners thinking about the role of data and analytics in their organizations.