How to Build Organization-Wide Curiosity for Data and Analytics

We can espouse the benefits of a data-driven culture and the value of data literacy skills all we like. But if employees have no interest in exploring data, they’ll be very unlikely – and potentially even actively resist –  to use data in their decision-making processes. To fully benefit from the transformative power of data analytics and data storytelling, the onus is on businesses to help foster and continually refresh a curiosity for data in their employees. 

Many organizations are unknowingly stifling this curiosity in their relentless pursuit of efficiency. They want employees to maintain KPIs and stay on task, yet expect them to become data literate without the proper training or support structure. These are the missing elements that can foster the vital curiosity that leads to data exploration and experimentation.

Jeff Bezos famously dubbed this room for exploration as “wandering” in one of his shareholder letters, claiming that it is a vital counter-balance to efficiency and the secret of Amazon’s runaway success. He believes that some of the best discoveries in Amazon’s history culminated from non-linear wanderings through data and analytics when curious team members followed hunches off the beaten path.

There is no one tool or course to develop this organization-wide curiosity for data analytics. It takes several technical and cultural factors to create the kind of environment in which curiosity can lead to valuable data-led breakthroughs.

1. Improved data quality and accessibility – Every business has data, but few can say their data is accessible or usable for business users. If employees cannot access the data they need, or the data is of poor quality, then initial interest will lead to distrust or frustration that creates inaction or resistance.
2. Data literacy skills training – This does not mean a highly developed understanding of advanced statistics or data science. Data literacy is about developing the ability to read, understand and argue with the results of analytics platforms or processes to uncover insights both obvious and more hidden.
3. More intuitive tools – Thankfully, much of the work here has already been done for enterprises. Advances in AI and user experience mean that modern analytics tools are becoming more intuitive and adaptive to the needs of users. The ever increasing ease of use and augmenting the intelligence of users via analytics encourages users to experiment and explore.
4. Encourage exploration time – Organizations must leave room for the exploration of analytics if they want employees to succeed with data. Encouragement should come from senior leaders so that every layer of the organization understands the importance of analytics exploration to the enterprise culture and performance.
5. Celebrate breakthroughs – When a valuable insight is uncovered, it can be tempting to assign intention after the fact. However, insights developed while following an initial data-driven hunch should be celebrated and held up as examples of what is possible by using human imagination alongside data analysis.

Many leaders forget that a key component to building a data-driven culture is curiosity. When we develop this curiosity across the workforce, we can start building the vital connections between data analytics and powerful data storytelling.

About the author:

As the Global Head of Data Literacy at Qlik, I help individuals and organizations realize their data and analytical potential by strengthening their data literacy. If you’d like to learn more about creating a data-driven culture in your organization please feel free to contact me at [email protected].