Seeking the Best Data and Analytics Leaders for Your Financial-services Business? Here’s What to Keep in Mind

It’s an uncertain time in financial services, with widespread news about distressed banks. The costly turmoil highlights the importance of getting data and analytics right in businesses in this space. Specifically, investing strategically in data/analytics talent should pay off in terms of creating lower-risk paths to profitability and avoidance of worst-case scenarios; in line with this, we’re seeing businesses across sectors creating and hiring for roles like chief data and analytics and chief AI officers. This is especially important in financial services, because of the strong regulatory component to data in this industry, which has led to sharp focus on promoting effective data governance in the recent past.

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Now, as most established banks and other financial institutions have created solid data ecosystems and governance systems, they are turning to building out their data strategies, monetizing data, and using data/analysis to craft their overarching business strategies, in service of future-proofing their business. That is, with the data and analytics building blocks in place, businesses are continuing to ensure compliance—playing defense—while looking to drive greater value with data and analytics talent and systems, or moving to play more offense.

In this context it’s critical to find, hire, and support the best-possible leaders for data and analytics, whether your Chief Data Officer, Head of Data Strategy, or any other. Our recent survey shows that nearly 80% of data/analytics roles in any sector today are less than five years old, including top-level positions and further down, and that 68% of top data/analytics execs report to the CEO. Both stats suggest the importance of these roles, and how critical it is to optimize hiring for them. We offer insights and practical tips for getting it right.

Are You Looking to Play Defense or Offense?

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Both defense and offense matter when thinking about your approach to data and analytics leadership.

As noted above, defense is about managing risk and compliance; offense is using data and data science to generate revenue and profit, largely via cutting-edge, AI-driven technologies. Most businesses will have a mix of objectives, since both defense and offense are important. Many retail banks and other consumer-focused financial businesses (wide-ranging fintechs), for example, are moving from defensive to offensive posture, and could consider seeking talent outside of financial services to craft and implement innovative data-driven strategies.

Data/analytics leaders at consumer-tech businesses like Google, Amazon, and Meta, for instance, will be adept at dealing with large volumes of consumer data and delivering such strategies, and may be worth a look for fresh perspectives and ideas. For example, we have helped bring in new retail financial services data leaders for large businesses from the ad-exchange industry, given their strong focus on marketing to retail customers and their experience tackling the complex problem of serving up ads to customers in real-time through an optimized bidding engine with billions of inputs per second.

On the other hand, more institutional, B2B financial businesses tend to look for existing industry expertise, including rising in-house leaders. For example, you may have a strong internal pipeline of candidates, such as those who report to the Chief Data/Analytics Officer. But when bringing in such a direct report from outside, look for those with the right profile to take over the C-level role in the future. That means identifying not only candidates who have risen within a singular function in data (e.g., data governance, data science) but who have worn multiple hats, are versatile, and can evolve with the business. Specifically, the data leader of the future should understand how to monetize data to understand your customers (segmentation), helping to launch new products around data, and have a proven track record of telling a compelling, data/analytics-driven story to business stakeholders to drive meaningful change.

Think Beyond Technical Skills—and Position Leaders for Success

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To continue the reasoning from above, technical data/analytics skills remain critical, whether for creating analysis strategies and data reports, identifying and hiring strong data science team members, or other functions. But strong data/analytics leaders are increasingly expected to translate the so-whats of analysis and work with business areas to get things done, such as new, large-scale analytics-driven marketing campaigns. That means you want to look for softer skills like communication, creativity, influence, business savvy, collaboration, all of which support a broad ability to take an offensive mindset with data/analysis and wield it as a business/value driver

Moreover, when bringing in a new data/analytics leader, be thoughtful about positioning them for success. Expose them to as many stakeholders as possible early on and follow up with them and their teammates to see how things are working (or not working). It’s also critical to be patient: don’t just assume a new leader will start producing results right away. They may take time to get up to speed, understand the industry (and its jargon, regulations, compliance)—if coming from outside—and grow their team and its initiatives from the ground-up. That means transformation is unlikely to happen in the first six to 12 months. Plan for it to take closer to 18 to 36 months.

We hope the ideas here help you navigate the opportunities and challenges presented by data/analytics within financial services today. We’ve seen many businesses drive large value with the right hires in this space, and can help you do the same.