Leading in Analytics: The Seven Critical Tasks for Executives to Master in the Age of Big Data

Over the past two decades, analytics has evolved from a niche technology to a critical business dimension. This presents a challenge and an opportunity for non-technical leaders. If we want to remain competitive in the digital age, we must learn to effectively lead analytics initiatives to success, even if we don't understand everything that's going on under the hood. Leading in Analytics offers a concrete strategy for doing just that, helping readers understand how to maximize their influence in complex data-driven projects.

From a business perspective, becoming analytics-savvy makes good sense. Today's leading companies in the area of analytics have documented millions and even billions in savings and increased market opportunities directly traceable to insights generated from data analytics. The goal of this book is to enable readers to extract value from analytics investment by setting initiatives up for success.

Even if we do everything right as leaders, some of our analytics projects will still fail--even the majority, if we believe the latest statistics. But we can dramatically improve our odds of success by following professional best practices and learning from the accumulated wisdom of big data experts. This book draws together contributions and knowledge from experts in data science, analytics leadership, business intelligence, and technology leadership. The result is a solid set of theories, strategies, and techniques that will boost the value of any analytics investment.

In Leading in Analytics, CEOs and other leaders will gain the knowledge and skills they need to take advantage of the potential of analytics by supporting the entire organization in maintaining an analytics orientation. Not everyone needs to be a coder, but data literacy is a must for today's business leaders. This book supports business leaders in engaging with analytics best practices, supporting technical and non-technical team members toward long-term analytics growth and success.

Over the past two decades, analytics has evolved from a niche technology to a critical business dimension. This presents a challenge and an opportunity for non-technical leaders. If we want to remain competitive in the digital age, we must learn to effectively lead analytics initiatives to success, even if we don’t understand everything that’s going on under the hood. Leading in Analytics offers a concrete strategy for doing just that, helping readers understand how to maximize their influence in complex data-driven projects.

From a business perspective, becoming analytics-savvy makes good sense. Today’s leading companies in the area of analytics have documented millions and even billions in savings and increased market opportunities directly traceable to insights generated from data analytics. The goal of this book is to enable readers to extract value from analytics investment by setting initiatives up for success.

Even if we do everything right as leaders, some of our analytics projects will still fail—even the majority, if we believe the latest statistics. But we can dramatically improve our odds of success by following professional best practices and learning from the accumulated wisdom of big data experts. This book draws together contributions and knowledge from experts in data science, analytics leadership, business intelligence, and technology leadership. The result is a solid set of theories, strategies, and techniques that will boost the value of any analytics investment.

In Leading in Analytics, CEOs and other leaders will gain the knowledge and skills they need to take advantage of the potential of analytics by supporting the entire organization in maintaining an analytics orientation. Not everyone needs to be a coder, but data literacy is a must for today’s business leaders. This book supports business leaders in engaging with analytics best practices, supporting technical and non-technical team members toward long-term analytics growth and success.