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The Mathematical Corporation: Where Machine Intelligence and Human Ingenuity Achieve the Impossible Hardcover – June 6, 2017
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"Shrewd corporate executives are realigning their organizations to harness the burgeoning power of cyberintelligence. ... Nonetheless, both corporate executives and government leaders still need inquisitive and creative humans ... A lucid overview of the management principles rapidly moving that world forward."―Booklist (starred review)
"Much has been written recently about the ability to reach better decisions by application of big data. However, Josh Sullivan and Angela Zutavern take us a step beyond by introducing The Mathematical Corporation. Leaders of mathematical corporations combine data analytics with the mathematical intelligence of machines and their own creativity to enhance the quality of current and future decisions. A must read for leaders striving to stay contemporary in a rapidly evolving world."―Larry Bossidy, retired chairman and CEO of Honeywell, co-author of Execution: The Discipline of Getting Things Done and Confronting Reality
"In this interesting and accessible book, Sullivan and Zutavern challenge us to reconsider assumptions about machines 'taking over,' relegating the human factor to a bygone era. Their hopeful alternative scenario for the future instead clearly shows the importance of leaders and employees who work creatively in symbiosis with machines to achieve greater productivity, better innovation and higher profits."―Amy Webb, founder and CEO of the Future Today Institute and author of The Signals are Talking
"Josh Sullivan and Angela Zutavern offer a riveting account of the explosive new combination of machine intelligence and executive imagination. Company managers are solving stubborn problems as never before in areas as diverse as health, mobility and security, and The Mathematical Corporation is a compelling call for the digital mastery of market complexity-now."―Michael Useem, professor of management, Wharton School of the University of Pennsylvania and co-author of Fortune Makers: The Leaders Creating China's Great Global Companies
About the Author
Dr. Josh Sullivan is senior vice president at Booz Allen Hamilton and one of the world's leading experts in data science and machine intelligence.
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What Sullivan and Zutavern characterize as “the cost-effective answer in their book.
Readers will appreciate the provision of mini-case studies of several mathematical corporations that 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 U.S. Census Bureau. All have made highly innovative use of analytics, artificial intelligence, and big data (including smart data). Yes, these are all large organizations but the lessons learned from their initiatives can be of substantial value to leaders in almost any other organization, whatever its size and nature may be.
Sullivan and Zutavern provide an Afterword that is more forward-thinking than most. They concede, “many problems that seemed intractable are not. Solutions that seemed out of the question are not.” I agree. In a world that has become more volatile, more uncertain, more complex, and more ambiguous than at any prior time that I can remember, an observation by Oliver Wendell Holmes more than a century ago seems uniquely relevant: “I would not give a fig for simplicity this side of complexity but I would give my life for simplicity on the other side of complexity. Alan Perlis agrees: “Simplicity does not precede complexity, it follows it.”
Josh Sullivan and Angela Zutavern review key principles that will guide and inform efforts by increasingly more capable humans and machine, working in collaboration: complexity is a boon, not a burden; the machine works better than the gut; machine models top mental models; solutions don’t require logic; create value by giving it away; break through without experience; and perfect launches lose to imperfect ones. Perhaps channeling Albert Einstein, they urge us think about the mathematical corporation as simply as possible…but no simpler.
When scientists perform regressions and correlations, much may be gleaned from the analysis. More importantly, outliers are identified for further analysis and refinement of the basic rule structures. In addition, machines identify organic patterns, clusters, classifications and unique sequences. Traditional mathematics, operations research and statistics are useful for minimizing, maximizing, optimizing, graphing, profiling and performing logical comparisons based upon truth table statements. Mass data may be represented in multi-plane linear algebra matrices in order to organize the data optimally for a computer analysis.
In artificial intelligence, much can be learned from polling the experts. As the pool of experts is expanded, more refined rule structures are developed based upon the expansion of the knowledge data base. In addition, more refined judgments are arrived at as more observations are made. For instance, engineers derive an MTBF (mean time between failures) based upon significant observations and testing of key component parts. Ultimately, an ideal replacement time period is developed so that expensive component part breakdowns can be avoided.
Artificial intelligence is helpful in reducing expensive processes of search. Ideally, an algorithm can arrive at optimal alternatives by using an advanced search engine to identify the best available choices based upon analyzing specific data bases for pre-defined criteria.
Machine learning will be critical for interplanetary travel. Once space flights arrive onto another planet, robots will begin to analyze the air, soil, moisture and pictures of the surrounding terra firma. This data will provide vital profiles so that engineers can design machines, building materials, pre-packaged food and spacesuits to accommodate astronauts on future missions.
Overall, "The Mathematical Corporation..." by Sullivan and Zutavern is an important strategic management planning tool for thinking outside the proverbial box. There is an extensive section of authoritative research notes at the end of the book.
In reading this, I was reminded of "The Machine" from Person of Interest, but the real Machine hasn't been built by one Mr. Finch. It's continually being built by all of us every day. The benefits are exciting to imagine. The leaders who will excel are those who ask great questions, impossible questions, mysterious questions. That resonates with me! Questions, here we come!