rooted in data and analytics and have leveraged new data-driven business models to disrupt and transform traditional industries such as retail, media, and travel. For innovative firms such as these, data brings speed, agility, and the ability to fail fast, learn from experience, and execute smarter.
Data is also transforming traditional businesses across many industries. From industrial systems to financial services, from media to healthcare delivery, from drug discovery to government services, from national security to professional sports, data is driving critical decision-making. The opportunity to deploy data and analytics has accelerated the speed at which companies can enter new markets, with new solutions, and quickly challenge or displace traditional competitors and market leaders.
Nearly all leading companies now state somewhere in their annual reports and business mission statements that data is a critical business asset, that they are striving to become data-driven in their analysis and thinking, that they are deeply engaged in forging a data culture at all levels of their organization, and that they view data as a basis for innovation and competition in the global marketplace. The Big Data revolution is here to stay.
Fail Fast, Learn Faster is a history and a chronicle of this Big Data revolution and its impact, as organizations strive to become data-driven. It represents a synthesis of developments and themes that have arisen with the ascendance of data over the course of the past two decades. In addressing these themes and questions, this book seeks to tackle one of the most disruptive dynamics facing leading corporations, government agencies, and social institutions today.
Progress does not come easily. This book describes how firms are using data to establish themselves as leaders as they innovate in their businesses and disrupt traditional markets, and how working with and using data becomes part of an organization's fundamental DNA. One aim of this book is to provide a window into the challenges that organizations face when they attempt to develop a data culture.
Executives and business leaders must ask themselves critical questions. Why should this matter to you? What can you learn from the experiences of others? How can you be successful in leading the data-driven charge? How do you avoid the pitfalls? How do you overcome the challenges? What does data-driven leadership mean? How do you reach your destination?
This book serves as a guide to understanding the evolution of data in the context of a changing world, where technology breakthroughs, the rise of consumer-driven services and self-service, and changing customer demographics are driving broader social and cultural implications. This is a story of how businesses have struggled to undertake corporate data transformation initiatives, and how they have sought to become data-driven.
Big Data is characterized by change and new approaches. Organizations are seeking to understand and appreciate how they can begin to derive value from the advanced application of data and analytics. There are many benefits to data-driven decision-making, including greater accuracy, precision, efficiency, and responsibility in the use of data.
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A central premise of Fail Fast, Learn Faster is that individuals and organizations learn through experience, and experience entails trial and error. “Ever tried. Ever failed. No matter. Try again. Fail again. Fail better.” This quote, from the twentieth-century Irish novelist, poet, and avant-garde playwright Samuel Beckett, offers a metaphor for data-driven change and the resulting disruption and innovation it is unleashing in an age of Big Data and AI.
One of the ways in which Big Data has helped fuel rapid innovation is through faster iterative learning – fail fast, learn faster, execute smarter. This book aims to educate organizations by providing a glimpse into paths taken, lessons learned, pitfalls to avoid, and realistic guidance on the steps, as well as the time horizon that it takes to develop a data-driven culture.
Paul Saffo, technology forecaster and managing director of San Francisco-based Discern Analytics, has observed, “Failure is the foundation of innovation.”5 In the world of data and analytics, corporations have long been bound by approaches that are costly and time-consuming, and that have hamstrung some of their more innovative ambitions.
John Bottega, one of the first executives to assume the role of chief data officer, holding this position at CitiGroup, the Federal Reserve Bank of New York, and Bank of America, comments, “Failure is informative. Even with imperfect data, business analysts can gain insight and knowledge with respect to the viability of an approach or hypothesis.”6
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Fail Fast, Learn Faster is the story of how data is impacting businesses and enabling companies that use it well to improve performance, drive efficiency, gain competitive advantage, and disrupt traditional ways of doing business. The great leaders and innovators in using data have transformed entire industries and now stand among the most highly valued and capitalized businesses in the world today, and in world history.
The book represents a summation of this period of change and the resulting transformation and leadership required to achieve success. The narrative is presented as a broad, historical, and cultural perspective on the rise of data-driven decision-making over three decades, and its impact across businesses and industries stretching into all corners of society.
Most stories are about people, and that is true here as well. At the heart of this story are the cultural and human aspects of business transformation that so often prevent data initiatives from gaining organizational traction. What are the challenges and barriers to achieving business success? What are the opportunities? What is at stake? Why do some organizations succeed, where others fail? How can organizations learn from failure to succeed?
In writing this book, my intent is to speak to a broad audience of general readers, corporate executives, students of the topic, and laymen, as well as industry practitioners who are working on the front lines of data every day. I have attempted to tell this story in plain and understandable language to the greatest extent possible, using examples that simplify complex business and technology trends and cut through the acronyms and technical jargon that too often make technical topics unintelligible to business executives and to the general reader.
In doing so, I draw upon themes and case studies developed over two decades of advising Fortune 1000 companies and sharing their stories and challenges in columns and articles that I have published in Forbes, the Wall Street Journal, MIT Sloan Management Review, and Harvard Business Review.
I am grateful to these publications for providing a venue for these perspectives and for permitting me to draw upon these highly illustrative examples in this work.
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Fail Fast, Learn Faster is intended to teach and to show, so that leaders and practitioners of the present and future can learn from the experience of their predecessors, from both their successes and failures.
Part historical analysis, part roadmap for the future, part manifesto for change, and part how-to manual, illustrating approaches that work and practices to avoid, this book aspires to take a long-term view in the context of the ongoing transformation of companies and industries.
I have attempted to provide insight and perspective, gleaned over time through trial and error, failure, and learning from experience, into the opportunities and challenges that organizations face each day. I hope that you will learn from the examples of industry leaders like American Express, Amazon, Capital One, Mastercard, and others.
Today's companies confront great opportunities
