Book Review: The Mathematical Corporation by Josh Sullivan and Angela Zutavern

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As a data scientist, I know first hand how today’s enterprise has some catching up to do with engaging the mathematical foundations for capitalizing on an ever-increasing volume of data assets. All the leading technologies that help companies gain insights from data are fundamentally based on mathematics – big data, data science, machine learning, AI and deep learning. It’s not that the C-suite needs to firmly understand these foundations, but the mindset needs to change from a purely “gut feeling” to a more empirical approach towards decision making. This is why a new title is so important: “The Mathematical Corporation – Where Machine Intelligence and Human Ingenuity Achieve the Impossible,” by Josh Sullivan and Angela Zutavern. Sullivan and Zutavern are, respectively, senior vice president and vice president of Booz Allen Hamilton.

We are at an important inflection point in history that will transform business competition at least as dramatically as the quality revolution of the 1980s or the emergence of the Internet age in the 1990s. The most powerful weapon in an enterprise’s competitive arsenal today is the alliance between the mathematical smarts of machines and the imaginative human intellect of visionary leaders. Together they make the mathematical corporation, the business model of the future. With rare exception,  a superior machine in collaboration with a superior human will outperform a superior machine or a superior human working alone. It is also true that there are certain tasks that a superior machine cannot do or do better than can a superior human and vice versa.

Mathematical corporations–the organizations that will master the future–will out compete high-flying rivals by merging the best of human ingenuity with machine intelligence. While smart machines are weapon number one for organizations, leaders are still the drivers of breakthroughs. Only they can ask crucial questions to capitalize on business opportunities newly discovered in vast data lakes. This dynamic combination will make possible the fulfillment of missions that once seemed out of reach, even impossible to attain. The book offers a profoundly optimistic vision for a new phase in business, and a playbook for how smart companies can manage the essential combination of human and machine.

Understanding how to work with data, and how to use oceans of data to our benefit equates to business survival skills, regardless of industry. Our fascination with data, in the form of  big data, data science and machine learning, has reached a threshold signalling a new era, changing the way we approach and run a business on a daily basis. The Mathematical Corporation shows leaders in many fields how to break free from outdated perspectives with the requisite technology and devise key strategies for making the “impossible” possible. The winners will be the ones who have prepared for this revolution.

I especially appreciated the threaded discussion of various mini-case studies throughout the book that highlight organizations that are in the process of becoming mathematical corporations including – Bloomberg LP, Ford Motor Company, GlaxoSmithKline, InterContinental Hotels Group, Merck, and Tesla as well as the Center for Prevention of Genocide, Federal Aviation Administration, U.S. Army, and the U.S. Census Bureau. All have made highly innovative use of big data, analytics, and AI. These are all large organizations, however the lessons learned from their initiatives can be of substantial value to leaders in almost any other organization, whatever its size.

I would recommend this book to any exec working for pretty much any organization on Earth. The principles provided herein, coupled with real-life examples will serve to lead the hand of managers currently sitting on the fence with respect to adopting analytical approaches toward acquiring competitive advantage. Good read!

Contributed by Daniel D. Gutierrez, Managing Editor and Resident Data Scientist for insideBIGDATA. In addition to being a tech journalist, Daniel also is a practicing data scientist, author, educator and sits on a number of advisory boards for various start-up companies. 


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