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Top Takeaways from The Mathematical Corporation

If the past was about analytics and big data, the future is about the big mind of the mathematical corporation. Big mind comes from combining the mathematical smarts of machines with your own imaginative human intellect. It requires the following shifts in thinking:

  • Consider complexity a boon, not a burden Complexity in the way systems work is like the complexity inherent in finding gold-bearing mineral deposits—it’s only a barrier to extracting value if you don’t know how to mine for results. Otherwise, it’s treasure. If you construct a parallel digital world, you can manufacture value where there was once none. JOOL Health, a Michigan based advanced health and technology company, did this using learning algorithms that create and dispense wisdom about preventive health care.
  • Acknowledge that the machine works better than the gut Intuition has served leaders well (and still does) principally because the mind absorbs and understands more detail and substance than we consciously know. But with every passing day, the machine is catching up. So, when do you trust a decision to your gut? And when to data? Bias, politics, wishful thinking, and the previous night’s office party distort your view. But as the machine more comprehensively reflects the real world, its biases dissipate (unlike yours). When InterContinental Hotels Group pitches a new offer to loyalty club members, marketers devise the content, but the computer chooses which individual gets which offer. This partnership generates a successful program.
  • Accept that machine models top mental models This is a corollary to the last one. The world of leadership has hit an inflection point. As useful as mental models are, machine models now outstrip human performance in about half of portfolio of cognitive tasks. You should, by all means, remain skeptical of machine thinking and take a “trust but verify” approach, but in the near future you’ll beat the models less often except in the realms of imagination, creativity, problem-solving, and some kinds of reasoning. Just consider: Google now hires people with the help of algorithms.
  • Don’t expect solutions to require logic We’re all used to reasoning our way to solutions: If we do X, that will cause Y, and then we’ll get Z. In the parallel digital world, discoveries often happen in the reverse order: The machine identifies the solution before we know why it solves the problem—solution before causation instead of causation before solution.
  • Create value by giving it away Sharing data sets, and sharing open-source code, can spur innovation. You may forfeit proprietary research results if you share, but you acquire abundant creativity via crowdsourcing. The global population of data scientists, collectively, knows much more than your own team. That’s why GlaxoSmithKline and other drug companies are opening up the raw, patient-level, clinical-trial data for others to use. The release of data accelerates everyone’s research—and reduces the waste of duplicated effort.
  • Look outside your industry to create algorithms Having an experienced expert in your line of work still counts big in coming up with good solutions. But for the person who applies the algorithm to data, having no experience at all in the area might work just as well having a subject matter expert on hand. That’s why Booz Allen data scientists, who know comparatively little about genocide compared with the people at the Simon-Skjodt Center for the Prevention of Genocide, could create an algorithm that predicts the occurrence of genocide slightly better than experts with decades of experience.
  • Prioritize imperfection and experimentation Whether you’re developing a new product or crafting a new strategy, you can’t improve the odds by insisting your people “do it right the first time.” Finding the breakthrough solutions flows from experimentation, not premeditation. Ford Motor Company kicked off its digital businesses in 2015 with 25 experiments, low-cost tests around the world of everything from shared vans to alternative friends-and-family leasing options. Ford is winnowing the results into businesses that work.
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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 (Public Affairs; 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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