Data, once considered a mere byproduct of business operations, has now become a significant driver of innovation, productivity, and success in the modern business landscape. Data-driven organizations, according to McKinsey, can increase their EBITDA by up to 25%, and the majority of the top 10 innovative companies in the world are data-driven firms. This compelling statistic has led to a situation where 83% of CEOs want a data-driven organization, 87% of CXOs prioritize becoming an intelligent enterprise, and 74% require data in decision-making.

However, becoming data-driven is not without its challenges. Only 8% of organisations successfully scale analytics to extract value from their data, while spending trillions on data exploitation. Just 24% of respondents believed their organization was data-driven in the past year, a decline from 37.8% the year before, and only 29.2% reported achieving transformational business outcomes^.

These sobering statistics highlight the need for a strong Data Culture within organizations. But what is Data Culture?

The Concept of Data Culture

The collective attitudes and actions of those who respect, support, and promote the use of data to enhance decision-making are referred to as the “data culture.” It’s about integrating data into the operational, mindset, and identity fabric of an organization. A strong Data Culture isn’t merely about having data or technology; it’s about the entire organization—regardless of department or role—making decisions based on data rather than intuition.

Building a robust Data Culture is crucial to becoming truly data driven. However, it requires laying the foundation on several cornerstones.

The Ten Cornerstones of Data Culture

• Strategic Alignment: Ensuring your data strategy aligns with your overall business objectives is crucial. It’s all about keeping your eyes on the prize.
• Self-Serve Analytics & Automation: Empower your teams with the tools to explore data themselves and automate repetitive tasks. It’s like a DIY kit for data analysis, with a robot assistant for the monotonous tasks.
• Data Foundations: Just like a strong foundation is necessary for a building, robust data infrastructure is crucial for your organization.
• Data and Analytics Capability Building: Upskill your teams. Think of it as a gym membership, but instead of building muscles, you’re building data and analytics skills.
• Data Democratization: Open the doors of the data kingdom to everyone, not just the data wizards.
• Experimentation: Encourage teams to try new things with data, learn from successes, and most importantly, from failures.
• Data Literacy: Everyone in your organization needs to speak ‘data’. It’s a language of numbers and graphs that everyone should understand.
• Quick Wins: Identify and execute projects that can show immediate results to build momentum.
• Data Storytelling: Use data to tell compelling stories that can guide decisions.
• ROI Mindset: Be a smart investor. Always consider what return you’re going to get from your data projects.

The Intersection of Data Culture and Technology

Technology alone cannot solve your data culture issue—it’ll only amplify it. Without a good data culture, you’ll end up with a bloated tech stack and an inability to prove the value of your analytics tools. Your analytics projects need to have a strong change management aspect, which is a huge part of all engagements.

Evalueserve’s change mantra illustrates this well. It includes understanding the impact of change on stakeholders, planning for change, implementing change to minimize impact, effectively communicating change, and facilitating change adoption through handholding. Important aspects of change management include empathy in design, documentation, conducting immersive workshops, and offering extended support, including certified change managers.

A strong data culture, when coupled with the right technology, scales your efforts, and leads to substantial business outcomes. An excellent example of this is one of our clients in the Logistics sector. Their centralized analytics team built and deployed an AI model that predicted customer churn in the coming three months and triggered health checks for high-risk accounts. This resulted in a remarkable 13% improvement in customer retention. Within a year, they expanded into two more pilots, introducing Customer Lifetime Value as a core metric to guide both strategic and tactical decisions, leading to a significant impact on revenue. Propelled by these successful pilots, they escalated the organization’s commitment to data science, resulting in a comprehensive, data-driven revenue expansion program.

The “ChatGPT Effect”

The rapid rise of advanced AI tools, particularly generative models like ChatGPT, signals a dramatic cultural shift towards data and AI-driven approaches. Within an incredibly short timeframe, ChatGPT reached a milestone of 100 million users, setting a new record in technology adoption rates. This staggering adoption rate is not just a testament to the capabilities of the tool, but a powerful indicator that people – both within and outside of business contexts – are increasingly leaning towards AI-powered solutions to drive their activities. From individual users leveraging the tool for creative writing and learning, to businesses employing it to enhance customer service and automate tasks, the wide-scale adoption of ChatGPT underscores the growing willingness to incorporate data and AI into everyday processes. This trend presents compelling evidence that our culture is progressively embracing data-driven decision-making and AI tools, and it’s a strong signal that organizations need to follow suit to stay competitive.

The Final Word

The journey to becoming a data-driven organization is a challenging one, filled with potential pitfalls. However, the rewards of success are enormous. Cultivating a robust Data Culture within your organization is an investment that will yield substantial dividends in the form of improved decision-making, increased innovation, and greater business success. It’s time for your organization to embark on this journey. Embrace the data revolution and let the power of data drive your business to new heights.

This article is written by a member of the AIM Leaders Council. AIM Leaders Council is an invitation-only forum of senior executives in the Data Science and Analytics industry. To check if you are eligible for a membership, please fill out the form here.

Swapnil is the global head of Evalueserve’s Analytics practice. He has 15+ years of experience leading end-to-end design and development of sophisticated analytics solutions across diverse industry segments—including BFSI, retail and CPG, industrial goods, logistics and distribution, technology, and life sciences. He has built a multi-disciplinary team of domain SME’s, data architects, data engineers, data scientists, and technology experts.