Building a Data-Informed Culture: Smart decisions start with data, but don’t end there

We often hear about being “data-driven”. It’s become a badge of honor, a sign that we’re making smart decisions. But the truth is, being data-driven isn’t always the best answer. If we rely too much on data alone, we can end up making the wrong calls.

Data as a Compass, not a Map

Data is incredibly valuable. It provides insights, reveals patterns, and helps us make informed choices. But it’s not perfect. Data doesn’t tell the full story; it lacks context, nuance, and the human touch. It’s a compass pointing us in a direction, not a detailed map showing every obstacle along the way.

A strong example of using data as a signal but leaning on intuition and context for decision-making is how Facebook developed the Like button. Originally called the ‘Awesome button’, the idea went through many iterations and internal debate. Early data didn’t show clear engagement lifts, and there was hesitation, especially from leadership, about whether it would encourage shallow interaction. But the team believed in its potential for expressing quick, lightweight support. They trusted their intuition and social observations, not just the metrics. A data scientist provided supporting data to show that a Like button wouldn’t reduce the number of comments on a post. In fact, it increased the number of comments because Likes would boost popular posts in the News Feed, giving them more visibility. This was the turning point; the data didn’t make the decision, but it validated the team’s intuition.

Eventually, with thoughtful iteration, the button launched and became a defining feature of the platform. Over time, the Like button became one of the most iconic and influential elements of Facebook. It succeeded not because the data guaranteed it would, but because the team gave room for the idea to grow through intuition and incremental learning.

In one of my past experiences, we faced a case where a component on the home screen had very low engagement. But instead of jumping to the conclusion that users didn’t like it and removing it right away, we saw it as a signal, not a verdict. We believed there was room for improvement. So we ran experiments, gathered more data, and explored what worked and what didn’t. This helped us better understand user behavior and guided us in making thoughtful changes to improve the experience.

Democratizing Data Access

For a truly data-informed culture, access to data shouldn’t be a privilege reserved for a select few people. Everyone in the organization should have the ability to access and interpret data relevant to their work. This democratization fosters a sense of ownership and encourages proactive decision-making.

Airbnb recognized this early on. They built an internal “Data University” to educate employees across all departments on how to understand and use data effectively. By empowering their team with knowledge and access, they cultivated a culture where data-informed decisions are the norm.

Trust as the Default

Of course, with greater access comes greater responsibility. But instead of implementing restrictive controls, organizations should start from a place of trust. Educate employees on the importance of data security and privacy, and make it clear that access to data is a privilege that comes with responsibilities.

This approach not only fosters a positive culture but also encourages employees to take ownership of their decisions. When people feel trusted, they’re more likely to act responsibly and make thoughtful choices.

Balancing Accessibility with Security

While openness is necessary, it’s just as important to protect sensitive information, such as customer emails, personal identifiers (ex: ID numbers or phone numbers), payment details, and internal business metrics. To strike the right balance between access and security, organizations should follow a few key best practices:

• Access Control: Set clear rules on who can see what for sensitive information. Use role-based access so people only access data that’s relevant to their job. This reduces the risk of accidental misuse or leaks.
• Data Encryption: Encrypt data both when it’s stored and when it’s being shared or moved. This ensures that even if someone gets unauthorized access, they won’t be able to read or use the information.
• Audit Trails: Keep logs of who accessed what data, when, and why. Regularly review these logs to spot any unusual behavior or misuse early. It also helps build accountability and transparency across the organization.

By putting these practices in place, teams can keep data secure while still making it easy for people to use the information they need to do their best work.

Cultivating a Data-Informed Mindset

Creating a data-informed culture isn’t just about giving people dashboards or running reports. It starts with how teams think. Encourage everyone to use data as a starting point, not the final answer. That means being curious, asking the right questions, and being open to changing course when new insights come in.

Leaders need to set the tone. That could be as simple as saying, “Show me what you’ve learned from the data”, or sharing decisions that were improved through digging deeper into the numbers. Make it normal to mix numbers with real-world context, product instincts, and user feedback.

The best cultures treat data as a partner in decision-making, not the boss. When teams are taught to think this way, they don’t just follow the data, they work with it to find the best path forward.

Conclusion

Data becomes powerful when it’s paired with human judgment, real-world context. When teams have access to the right data, feel trusted to use it wisely, and follow clear security practices, they can make smarter decisions without being boxed.

The goal isn’t to chase metrics, it’s to build a culture where data supports good thinking. Let’s use data as a helpful guide, not the only voice in the room.