Building a Data Culture is not just an option. It’s business-critical.

When talking to clients about their analytics transformation, it soon becomes apparent that—despite large investments in analytics transformations and data literacy training—many feel they have reached a plateau in terms of data monetisation and value generation. Notwithstanding initial high expectations or promises, the magic appears to be gone. People often do not automatically act in line with new role expectations and interactions between the business and data office seem to be difficult. Employees do not always understand what is expected from them and lose interest in data and analytics. After a while, the business starts to develop passive resistance due to insufficient results.

Almost all these challenges boil down to the inability to establish and sustain a culture of data-driven decision-making. No matter how smartly designed, the best data and analytics strategies, programmes or initiatives are incomplete without a Data Culture to support them. Data Culture and analytics ROI are intertwined and interdependent. If companies hope to transform, they must begin to address the cultural obstacles. Behavioural and cultural change are increasingly being recognised as the biggest challenge to addressing the full potential of data and analytics transformations. However, many companies do not really know where to start.

In our interview with Sudaman Mohanchandralal, Chief Data Officer at Allianz Benelux, a recognised industry expert and thought leader in the area of data and analytics transformation, we explore the main challenges in becoming a data-driven organisation, discuss concrete strategies for companies to get better at building a data culture, and the tangible value that a data culture can bring.

Sudaman has 20+ years of professional experience in the world of data and analytics. He has a master in computer science, a prestigious degree in business administration along with super specialisation in business analytics, and has a distinguished career embracing data and analytics in banking and insurance. He describes his career as a triangle built on three core experiences: complex event processing, analytics, and financial data warehousing.