Thanks to the deafening buzz around data science and AI, enterprise leaders no longer doubt the transformative potential of this powerful duo. Yet, a striking statistic reveals a bigger leadership challenge: More than 57% of companies struggle to build a data-driven culture, according to Wavestone research. This indicates that in many cases, leaders believe in the power of data and are investing in AI, but their organizations still aren’t getting the real benefits.

Indeed, for many leaders, the challenge is not buying advanced analytics tools or building accurate technical solutions. The real hurdle is subtle yet much more important: fostering an environment within an organization where individuals instinctively turn to data anytime they must make a decision. This is the real meaning of being data driven or creating a data culture.

Building a Data-Driven Culture: Questions to Ask

Why is building a data-driven culture incredibly hard? Because it calls for a behavioral change across the organization. This work is neither easy nor quick. To better appreciate the scope of this challenge, let’s do a brief thought exercise. Take a moment to reflect on these questions:

How involved are your leaders in championing and directly following through on data-driven initiatives?

Do you know whether your internal stakeholders are all equipped and empowered to use data for all kinds of decisions, strategic or tactical?

Does your work environment make it easy for people to come together, collaborate with data, and support one another when they’re making decisions based on the insights?

Does everyone in the organization truly understand the benefits of using data, and are success stories regularly shared internally to inspire people to action?

If your answers to these questions are “I’m not sure” or “maybe,” you’re not alone. Most leaders assume in good faith that their organizations are on the right path. But they struggle when asked for concrete examples or data-backed evidence to support these gut-feeling assumptions.

The leaders’ dilemma becomes even more clear when you consider that the elements at the core of the four questions above — leadership intervention, data empowerment, collaboration, and value realization — are inherently qualitative. Most organizational metrics or operational KPIs don’t capture them today. Thus, leaders end up investing in and backing data initiatives despite having little visibility into their likely outcomes.

This is also why these leaders may be caught unawares when their organizations fail to become data driven, as evidenced by surveys such as the one noted above.

This article spotlights four areas leaders must focus on to build a data-driven culture, using real-world examples of how to make this journey fun, engaging, and relatable for employees.

How to Shape a Data-Driven Culture: Four Pieces

To build a truly data-driven culture, leaders must look beyond the traditional technical focus of AI journeys. The following four elements can bring about a behavioral change across organizations, putting data at the heart of decisions.

[Here is the first of four.]

1. Leadership Intervention

Organizational leaders must get actively involved in their strategic data and AI initiatives for the organization’s data-driven culture to take root. Since decision-making with data calls for a shift in the way people do their jobs, this needs active change management.

Unfortunately, executive-level owners often stop at funding the data initiatives and delegate the entire execution away.

Leaders can intervene by clearly stating why the company needs data and AI in the first place. They must own the outcomes of the initiatives and periodically check in to ensure that everyone considers data a part of their job — and not just the IT department’s or the data team’s responsibility.

Finally, leaders must walk the talk by actively and visibly using data and AI solutions — as part of their work, in meetings, and for organizational reviews. And they should foster an environment of curiosity to encourage employees to question processes, propose innovations, and take calculated risks to change the status quo.

Concept in Action: Rewarding Failures for ‘At Least Having Tried’

When DBS Bank embarked on its digitization journey, CEO Piyush Gupta made it a priority to build a culture that rewarded risk-taking and valued learning from failures. To spur innovation, he wanted to create safe spaces for employees to experiment, even at the risk of failure.

In a podcast, Gupta recounted a pivotal moment during the shift, when an experiment failed and there was regulatory pressure to punish the person responsible. But he intervened and pushed back, saying, “Not only am I not going to punish the person, I’m going to give them an award for at least having tried.”

Such an example of a leader walking the talk sends a powerful message throughout the organization. This kind of leadership behavior shows people that they can take calculated risks and it’s acceptable to fail as long as they try, learn, and adapt. By embracing a growth mindset and focusing on psychological safety, Gupta cultivated a culture where DBS employees feel empowered to innovate and take ownership.