How Can Data Leaders Balance Innovation and Compliance? Insights from Taylor Culver

Data leaders face a unique double challenge of balancing defensive and offensive data strategies. While data leaders in regulated industries like finance must safeguard data defense (instilling practices focused on compliance, risk management, and data security/privacy), the rise of AI poses a key question: How can they innovate? Offensive data strategies, by contrast, are aimed at driving innovation and competitive advantage with data.

Offensive strategies unlock data's potential for insights and business value, but defensive strategies are essential for managing risk and ensuring compliance with industry-specific regulations. Data leaders must adeptly navigate this dilemma, fostering a culture of responsible data usage and ethics while still enabling data-driven innovation across the organization.

As data consultant Taylor Culver reflects, being a data leader is an exceptionally challenging role. “It was probably one of the most isolating and frustrating roles I've ever had in my professional career,” he shares. “And I think the data leadership role is harder than being an entrepreneur as far as I'm concerned. And people say entrepreneurship is hard, and it is very, very hard, but being a data leader is even harder."

In this blog, we’ll uncover key insights from Taylor Culver’s recent Data Radicals episode, exploring how data leaders can walk the tightrope of innovation and compliance while delivering business value. 

Implementing data governance without stifling innovation

Data governance is essential for regulated industries to manage risk and ensure compliance. However, governance practices should not stifle innovation. As stated in Balancing Innovation and Governance: The CDO's Dilemma, "Balancing these numerous responsibilities requires constant collaboration with other executives, honing a delicate balance between data innovation, security, and privacy protection."

Governance should focus on providing clear policies and guidelines, not enforcement. As Culver explains, “The opportunity for driving efficiencies out of banks is in the billions, right? So they're trying to figure out how to do that, but they cannot let go of that risk side.”

Culver emphasizes that Chief Data Officers (CDOs) must take a bold approach to data governance. “A CDO has a different challenge. When they come in, they have to immediately go on the offense, which is, 'This is the data strategy. This is my job. This is what we do. This is what we don’t do. Here are our metrics for success. If you don’t like this, please fire me because this is going to be a giant waste of everyone’s time if we continue down this path.' And those are hard conversations executives need to have."

By establishing structured frameworks and clear strategies upfront, CDOs can foster innovation while ensuring compliance, creating a balance between driving business value and managing risk.

The value of communication for data leaders

For data leaders, effective communication with business executives and other stakeholders is paramount. As Culver highlights, “This is the biggest kind of value add we see with our customers: data leaders need to get out of their seats and go talk to people and formalize the way that they're engaging with people. No different than a salesperson does. So no different than a salesperson calls 100 people a day. Data leaders should be talking to people all day long.”

This proactive engagement involves understanding the problems stakeholders are trying to solve, not just addressing surface-level complaints about data quality. Culver advises, “What they need to be talking to them about is what their problems are. And not to set up some gripe session about, 'Oh, this data sucks,' but, 'Hey, what are you trying to solve for? What matters to you?'”

Intent matters greatly in these interactions. “It comes down to intent, right? Do you genuinely wanna help people in your business solve problems with data? Do you genuinely want to grow? Do you genuinely recognize that there's not a magic bullet to doing this? Those are the data leaders who will be successful despite facing adversity.”

Over time, these conversations can surface valuable use cases. By engaging with different teams, data leaders can identify diverse needs across departments, which can then be aligned to specific projects. These projects, in turn, become the foundation for effective data governance initiatives.

Data as a reporting vs. transformational function

One of the fundamental challenges data leaders face is bridging the gap between seeing data as a reporting function and leveraging it as a transformational asset. According to Culver, many senior executives still view data as a tool for generating reports rather than a strategic enabler for innovation.

"You cannot be a policeman," Culver notes. "A data leader, when they go out to the business saying, 'You have to do this. You have to do this documentation,' the person's gonna wanna stab you in the back the second he leaves the room. It's like bringing me work without solving a problem. Thank you. Let’s never work together again."

Instead, Culver explains that data leaders must adopt a value-based approach. “Within financial institutions, they need to change the way that they work with the business, which is, ‘Hey, my hands are tied here. I have to do this because the regulators wanna do this, so I need this from you.’ But at the same time, ‘Hey, I also wanna help you solve problems.’ And that’s a tightrope to walk.”

Organizations that embrace data as a transformative asset go beyond analytics to use data for decision-making, product development, and innovation. This shift requires a top-down commitment from leadership, robust data strategies, and investments in talent and technology to unlock the full potential of data.

Managing expectations in the age of AI

According to Culver, the buzz around AI is blinding. “It’s funny,” he laughs, “where data leaders need the most help with AI is getting the C-suite off their back about finding use cases to use AI.” At some point, those lofty expectations need to be grounded in reality.

"I think there's a lot of big talk around AI and, while I think it's very interesting, I think the hardest thing for data leaders to do is kind of reset expectations around...Here's the ROI [of this AI case] – is this compelling?" he says.

Very few enterprises today have the foundations in place to support successful AI initiatives. Responsible AI must prioritize privacy and ethical considerations alongside business value – and this requires a hefty investment few firms are keen to take on.

Conclusion

The role of data leaders has never been more critical—or more complex. Balancing innovation with compliance, managing executive expectations around data and AI, and shifting perceptions of data from a reporting function to a transformational one are just some of the challenges leaders face.

As Taylor Culver emphasizes, success requires more than technical expertise. Strong communication, cross-departmental collaboration, and a commitment to fostering a culture of responsible data usage are essential. For organizations ready to embrace these principles, the opportunities for growth and innovation are boundless.

Listen to the full conversation with Taylor.