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Case Studies from The Mathematical Corporation

The capabilities of the mathematical corporation extend beyond mining big data, analytics, and artificial intelligence—pursuits that have spurred organizations to focus narrowly on answering known questions by querying specific, often proprietary, piles of data.

Instead, the mathematical corporation plumbs a universe of data to uncover new patterns and insights. By doing so, they discover the questions they should be asking and find solutions that might not have occurred to them otherwise. The mathematical corporation can predict and shape the future because it is forward-facing and breaks through the darkness of past constraints. 

Examples of organizations becoming mathematical corporations through this process include:

  • Ford Motor Company CEO Mark Fields steered the company away from customer surveys (based on a sampling of reality) and toward the collection and analysis of sensor-collected data from all customers (capturing actual customer behavior). The result is actionable insight into everything from mobility, customer experience, and valued features to safety, emissions, and fuel economy.
  • InterContinental Hotels Group One of the largest hotel chains in the world, with 11 brands and nearly 5000 hotels—used machine intelligence to review 18 million records to identify and predict complex customer behavior, allowing them to individually tailor their customer rewards programs.
  • GlaxoSmithKline The company partnered with health information start-up Epidemico to trawl Facebook and Twitter for mentions of adverse side effects. Social media mentions of adverse events in 1 year prompted the recall of one GSK product—and exceeded all those in the Food and Drug Administration database since its inception in 1968.
  • Merck Merk optimized its vaccine yields by conducting a large-scale integration and analysis of 5 terabytes of data using 15 billion calculations and more than 5.5 million batch-to-batch comparisons. This allowed them to pinpoint the true culprits behind discarded batches in the manufacturing process.
  • U.S. Census Bureau Implementing an innovative data-science-driven mobile application for the 2020 census, the bureau will reduce costs and eliminate thousands of hours of travel by enumerators.
  • Tesla Tesla’s vehicles include software that aids customers’ limited self-driving. Another set of software, with no effect on the car, records all driver behavior so Tesla can accumulate the data to build future full-service self-driving capability. Whereas it took Google 6 years to gather a million miles of actual self-driving car data, Tesla’s 70,000 cars produce a million miles of driver data every 10 hours. Who will succeed first in using the data for the next breakthrough?
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About The Mathematical Corporation

Where Machine Intelligence and Human Ingenuity Achieve the Impossible

The emergence of today’s machine age is a once-in-a-decade breaking point that will transform business competition at least as dramatically as the quality revolution of the 1980s or the dawn of the internet age of the 1990s.

The Mathematical Corporation: Where Machine Intelligence and Human Ingenuity Achieve the Impossible (PublicAffairs; June 6, 2017), by Booz Allen artificial intelligence experts Joshua Sullivan and Angela Zutavern, is the first book to show business leaders how to compete in this new era: by combining the mathematical smarts of machines with the intellect of visionary leaders.

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For Media Inquiries:

Joseph Campbell
703-377-4422
Campbell_Joseph@bah.com

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