Randy Bean’s primer on data-driven leadership, Fail Fast, Learn Faster: Lessons in Data-Driven Leadership in an Age of Disruption, Big Data, and AI, provides several benefits to accountants and data analysts who read it. Ongoing changes to data management processes and culture increase organizations’ need for adoption of disruptive technologies such as data analytics and AI to remain competitive. These technologies are growing in the rate of their evolution and impact on companies of all sizes. These changes enhance organizations’ need for robust data governance and an emphasis on ethics.


Bean provides a rundown of both cautionary tales and positive case studies of both large and small to midsized companies managing and analyzing data more effectively. The author offers lists with recommended steps, elements of developing a strong data-driven strategy, and the “10 Commandments of Data-driven Transformation” (the title of Chapter 10).


Take one of Bean’s key success factors: developing a data culture. He writes that professionals need a purposeful mindset and a way of managing data that permeates all organizational levels. Tone at the top is necessary but not sufficient. The bad news is that there are no shortcuts to creating and implementing a data culture and outlining a corresponding road map. That said, it’s well worth the necessary time and effort.


What business leaders need to become data-driven isn’t a one-off project but rather a new, integrated approach to parsing decision-useful information, hence the term “data culture.” The entire staff must grow to appreciate the value of data assets to buy into the effort necessary to customize the four key strategic planning areas Bean lays out: data strategy, data governance, data management, and change management and adoption.


Bean’s advice for aspiring data-driven leaders to enhance their organization’s success is simple: Start with low-hanging fruit—log quick wins to develop trust in the outputs of data analysis and provide support for the executives leading the process of organizational transformation.


Readers will appreciate the disciplined and thorough approach Bean brings to his insightful, futuristic, high-level guidance. The examples present data management models for teams to emulate and talking points to persuade the organization’s leaders to set off on this data-driven road together. I recommend this book to students and professionals looking for a reliable guide to help their organization undergo a mindful and meaningful metamorphosis into a data-driven culture.

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