Kevin Maney on managing predictive technologies: An interview by Bob Morris


Kevin Maney

In his own words….

I’ve had a long career as a journalist and author. Lately, I’ve added a new hat: I’ve joined VSA Partners as its Editorial Director. The plan is to marry business to big-think journalism in a way that hopefully helps both prosper. The first example of that is the book commissioned by IBM and co-authored by me, Steve Hamm and Jeff O’Brien — Making the World Work Better.

My latest book, co-authored with Vivek Ranadivé, is The Two-Second Advantage: How We Succeed by Anticipating the Future…Just Enough (September, 2011).

Last year, I had another book out: Trade-Off: Why Some Things Catch On, and Others Don’t. The hardcover was published in the fall of 2009 by Broadway Books; the paperback, in August 2010.

I contribute occasionally to Fortune, The Atlantic, Fast Company and other magazines. I had been a contributing editor at the ill-fated Condé Nast Portfolio, joining the magazine prior to its launch in 2007 and hanging on until its demise in April 2009.

Before all this, I worked at USA Today for 22 years, much of it as the newspaper’s technology columnist. The job gave me the privilege of interviewing most of the biggest names in the industry. Here and there, I end up on television and radio. I’ve appeared on PBS, NPR, CNBC, and other media outlets, and I’ve frequently been a keynote speaker and on-stage interviewer at events and conferences.

On the music side, in 2008 I worked with a group of terrific Bay Area musicians and recorded a CD of songs of wry commentary about business and technology. It’s called “Privacy,” by Kevin Maney & His Briefs. You can actually buy it on iTunes. I’ve also played in a DC-area band, Not Dead Yet, which at the moment is dormant, if not actually dead. My shining moment was getting my song “Found It On Google” played on Mitch Albom’s radio show.

I graduated from Rutgers University, grew up in Binghamton, N.Y., and now live outside Washington, DC, while spending a lot of time in New York.

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Morris: Before discussing The Two-Second Advantage, a few general questions. First, of all the people with whom you have been closely associated, which has had the greatest influence on your personal development? How so?

Maney: Over the very long run, I guess it’s been my brothers. I’m the oldest of three, and the next one is Dave, and then Scott. (I also have a stepbrother, Mark.) Dave, Scott and I have always been close, but it’s more than that. I think our opinions of each other carry great weight, and that’s pushed each of us to be better people, be more ambitious, be wittier, raise better kids, and whole lot of other things like that. And it’s a supportive competitiveness. We’ve always boosted each other, and at times even done business together. Right now, I’m working at a firm, VSA Partners, that Scott introduced me to, and playing a role in  Dave’s start-up, Economaney. Fortunately for me, I’m the least smart and savvy of the three of us, so I think I get to learn more from them than they do from me.

Morris: On your professional development?

Maney: There are two people. When I was 25, Hal Ritter just became editor of USA Today’s Money section, and he hired me. I think I was his first hire. I’d say we had a respectful but sometimes contentious relationship. He could be a hard guy to work for — demanding and harsh. But he was also maybe the smartest editor I ever worked for. He knew his audience and drove us to write for it with clear, lean prose. He taught me to have standards and never settle for less, and to have the discipline to always think of the reader. I worked for Hal for the first decade of my career. Whatever kind of writer I am today, it’s because of those 10 years. Hal is now an editor at the Associated Press. We nominally keep in touch.

The other important person is Jim Collins. While Hal taught me to pay attention to the details, Jim played a significant role in helping me think big and broadly. The two of us met well before Jim got famous for his books Built to Last and Good to Great. I was working on a story for USA Today, and talked to a publicist at Stanford, where Jim was a professor at the time, about it. The publicist told me that I should talk to Jim — that Jim was working on a book about a similar topic. That book ended up being Built to Last, but it was then a half-finished manuscript. Jim and I talked and hit it off. He sent me the manuscript, and I thought it was one of the most important business documents I’d ever read. When Built to Last was finally published, I jumped on it and wrote a cover story for USA Today, which in turn was the spark that sent the book up the bestseller list.

Anyway, Jim and I became friends, and I can’t tell you the number of big, analyze-the-universe conversations he and I have had. I love the way he makes me think. His ideas about corporations had a huge impact on the way I analyzed Thomas Watson, Sr. in The Maverick and His Machine. I wouldn’t be the same kind of author if not for Jim’s friendship.

Morris: Years ago, was there a turning point (if not an epiphany) that set you on the career course you continue to follow? Please explain.

Maney: I knew I wanted to be a writer from as far back as I can remember. That was my talent. Lord knows it wasn’t math. If there was an epiphany, it came when I went to Rutgers and got involved in the journalism program. I reluctantly signed up for a journalism major, thinking I needed a fall-back way to make money should my career as a novelist fail to take off. As I started to try on journalism, including doing internships and working at the campus paper, I found I actually liked it. So I started to want to be a journalist.

And then there was another epiphany when I discovered the great old New York Times columnist Russell Baker. I realized there could be a way to be a newspaper journalist and write funny yarns in a column. Then I wanted to be Russell Baker. I kind of half achieved it — writing a column for USA Today that often involved funny yarns about technology.

Morris: To what extent has your formal education been invaluable to what you have since achieved thus far?

Maney: Well, with all due respect to Rutgers, I’m not sure the value of my time there was in what I learned academically. It was more about the fact that Rutgers introduced me to journalism and diverted my path into newspapers.

Morris: You are a serious musician. To what extent has your significant involvement with music proven to be highly valuable in ways and to any extent you had not anticipated? Please explain.

Maney: I’m not sure how much the word serious applies! I write songs like “Wouldn’t Want to Be Bill Gates” and “Little Tattoo and All Over Tan.” But I certainly have pursued music in general and songwriting in particular.

What’s it done for me? I think it’s become part of my personal brand — in a field where having a personal brand is an asset. It’s helped me stand out a bit in the minds of a lot of people in the tech industry. I’m that tech writer who gets on stage and plays funny tech songs. I wouldn’t want that to be all I’m known for, but it’s a bit of a differentiator.

Morris: In your opinion, what will be the single greatest challenge that business leaders (especially CEOs) will face during the 3-5 years?

Maney: This gets a bit into what I’m doing with my brother Dave. He and I and other people we’re working with believe that the disruptions and difficulties in the economy the past few years aren’t just a bump in the road — they’re part of a massive change in very big forces, brought on by the Internet, globalization, and the flood of data. It’s changing the very nature of what a company is, the nature of what a job is, the value that proximity has or doesn’t have. Economaney is kind of a new age think tank for tossing these ideas around and trying to make sense of them. All in all, the next three to five years are going to be among the most challenging in history to be a CEO in America — or for that matter, President of the country.

Morris: Here are a few questions about The Maverick and the Machine. In which specific ways was Thomas Watson, Sr. a “maverick”? So what?

Maney: The title reflects what I consider my biggest discovery about Watson: that he wasn’t a stiff old geezer but was in fact a risk-taking nut. If you think of the kinds of big bets Apple’s Steve Jobs has made the past decade — that’s what Watson did in IBM’s early years. He bet the company on going into information technology in the 1920s when there was no obvious market for information technology. In the Depression, he almost killed the company because he tried to keep it intact instead of cutting workers and closing factories — a decision that paid off when FDR signed the Social Security Act and created an information problem only an intact IBM could solve. Watson even bet on globalization before most U.S. CEOs knew how to find the rest of the world on a map.

Morris: However different he and his son Tom (Jr.) may have been in most respects, what did they share in common?

Maney: They were both combative, decisive, very sure of themselves, and willing to take risks based on instinct. To skip ahead a bit, they had developed a two-second advantage type of gut instinct about IBM and information technology. Both father and son also believed wholeheartedly that the greatest invention out of IBM was IBM, not a particular product. It’s a belief in corporate culture above all as a path to endurance.

Morris: What leadership lessons can be learned from their strengths and weaknesses them?

Maney:  Well, the Watsons seem to have been right about the power of culture, endurance, and the value of taking big chances to leap ahead of competitors. Again, it’s what we have celebrated in Steve Jobs in our era.

The weaknesses, too, are similar — especially about succession. Such strong personalities tend to leave a void behind them. Certainly the people who took over IBM after the Watsons were smart and talented chief executives, and the people who follow Jobs will be similarly smart and talented. But they won’t have the same kind of instinct, or the confidence to take the same kind of chances. IBM succeeded for a long time after the Watsons on its own momentum. The same will happen at Apple post-Jobs. But that momentum eventually peters out.

Morris: With regard to Trade-Off, to what does the title refer?

Maney: Every purchasing decision involves a trade-off between what I call fidelity and convenience. Fidelity is the total experience of something — how great the experience is. Convenience is how easy it is to get something. A live concert is a high fidelity way to experience music; an MP3 file is a high convenience way to experience music. Depending on the situation, one or the other is probably pretty appealing. What’s not appealing is something that offers neither. A CD these days is not all that convenient, and it doesn’t bring enough fidelity to make you put up with that inconvenience. So, nobody buys CDs anymore.

Morris: Here’s a two-part question. What is the “strategic lens” to which Jim Collins refers in the Foreword? What is its greatest value of used properly?

Maney: Once you understand the whole “trade-off” concept, you can use it as a way to look at any industry or any company’s position vis-a-vis its competitors. It’s another way to understand a market, and see where the best opportunities lie.

Morris: What are the defining characteristics of “High Fidelity” and “High Convenience,” respectively? Which is more difficult to establish and then sustain? Why?

Maney: I briefly explained a bit of this earlier. High fidelity is a rich experience, and you’ll put up with terrible convenience to get it — maybe it’s high cost, waiting in line, jumping through hoops. High convenience is the opposite — it’s a commodity, but it’s cheap and easy and ubiquitous. A great exclusive boutique shop is high fidelity; Wal-Mart is high convenience. Both are hard to establish in their own way. The thing to remember about sustaining either is that you can’t sit still. Some other entity will always find a way to challenge your fidelity position or your convenience position.

Morris: Now please shift your attention to The Two-Second Advantage. When and why did you and Vivek Ranadivé decide to write it, and do so together?

Maney: Vivek had published a couple of books, and he had an idea for a new one. So one day we were in his conference room and he laid out  his idea about where technology was heading and how it was going to have to become predictive to deal with the onslaught of data heading our way.

That was just as I had finished Trade-Off, and I had been thinking about my next book, and the title — The Two-Second Advantage — in my head in fact was . Inspired by Jeff Hawkins’ book On Intelligence, I’d spent a lot of time thinking about how Jeff’s theories about predictiveness in everyone’s brains might apply to talented people. I’d started to explore a bit whether super talented people — at anything — were better and faster at predictions than everyone they were competing against.

The more Vivek talked, the more I thought that the way he was describing technology and the way I was describing talent were very similar, and possibly related. When I brought this up to him, he totally agreed, and we decided to put the ideas together and see where it took us. After a bit more research it was obvious it was taking us to an interesting place.

Morris: Were any head-snapping revelations throughout the process of producing the manuscript?

Maney: The head-snapping revelation really was when Vivek and I decided the two ideas were related. That was the a-ha moment. The research just bore it out.

Morris: To what extent (if any) does the book in final form differ from the one you originally envisioned? Please explain.

Maney: Once we had the idea and enough research to convince us we were right, the book I envisioned pretty much turned into the book as it is.

Morris: For those who have not as yet read The Two-Second Advantage, to what does the title refer?

Maney: The “two-second advantage” is more metaphorical. It’s about that idea that talented people can predict with great accuracy what’s about to happen just a tiny bit ahead of their competitors. It might be two seconds ahead, or two hundredths of a second, or two days. Napoleon on an eighteenth century battlefield had something more like a two-day advantage. Wayne Gretzky in a hockey game was probably a second ahead of everyone else on the ice.

Morris: Please explain the reference to “just enough” in the subtitle.

Maney: Gretzky’s talent doesn’t come from studying everything he’s experienced in hockey and making long-term game plans. It comes from constantly taking in all the data that’s happening in the moment on the ice, and instantly generating constant predictions based on super-efficient mental models he’s built in his head. So we’re saying that technology has to work more like Gretzky. Now companies tend to mine gigantic databases for insights into what might happen six months from now. That might always be valuable, but we’re saying there’s a different kind of value — and a competitive edge — in processing ongoing streams of data through a software model that can quickly and constantly make predictions about, say, whether a certain customer is going to defect, or an aircraft is going to run into trouble.

Morris: You and Vivek suggest that when “natural wiring” and hard work are forged together through a singular combination of circumstances, it is possible for many (most?) people to develop a “more predictive brain.” Please explain.

Maney: I’d rephrase that a bit. Some people seem to have extreme natural wiring — a talent that seems to come out of nowhere. Like a music savant or prodigy. The uplifting news, though, is that many talented people don’t have such natural wiring — but they forge a talent through thousands of hours of what’s known as deliberate practice or deliberate performance. Anybody can develop a certain amount of talent at something. However, the supremely talented — the superstars — are people who have married a gift of brain wiring to those thousands of hours of practice, usually in favorable circumstances.

Morris: In the book you discuss a number of people whose brains have exceptional predictive talent. They include Wayne Gretzky, Eduard Schmieder, Stephen Wiltshire, Mo Rocca, Earle Whitmore, Thomas Menino, Joe Lovano, and Jose Cordero. However different they may be in most respects, what specific capabilities do they share in common?

Maney: Through those thousands of hours of practice, they have “chunked” detailed information into speedy mental models that can process what’s going on and in a flash make highly accurate predictions about what’s about to happen. Comedian Rocca can see the moment to land a funny comment coming in slow motion. Lovano knows how the music will sound just before he plays it. In a word, this is what we call instinct.

Morris: What is “chunking” and how can it be beneficial?

Maney: Chunking is the ability of the brain to learn from data you take in, without having to go back and access or think about all that data every time. As a kid learning how to ride a bike, for instance, you have to think about everything you’re doing. You’re brain is taking in all that data, and constantly putting it together, seeing patterns, and chunking them together at a higher level. So eventually, when you get on a bike, your brain doesn’t have to think about how to ride a bike anymore. You’ve chunked bike riding. Which is much more efficient than having to think about bike riding every time.

So chunking makes our brains more efficient. The more you can chunk something, the faster and easier you can process it. Wayne Gretzky had chunked hockey like no one before or since. Talented people have supremely chunked whatever they become talented at doing.

Morris: What is the relevance of Mihaly Csikszentmihalyi’s concept of “flow” to achieving a two-second advantage?

Maney: It’s a version of what we’re describing. When someone is in a state of flow, that person’s brain is not thinking about anything — it’s just processing things through chunks at a total instinct level. Athletes in a state of flow describe knowing what will happen just before it does — knowing how a defender will react to a certain move an instant before doing it. Of course, if you know what will happen, you can succeed at doing it, so an athlete in flow has a stand-out game.

Morris: Here’s a statement that caught my eye: “newborn babies are basically savants.” How so?

Maney: Babies have not yet chunked anything. They aren’t doing any high level thinking. All they’re doing is sucking in all the data they experience in the world around them, and remembering it, raw. It’s basically what extreme savants have happen in their brains. One we wrote about, Stephen Wiltshire, could take a helicopter ride over a city, and then draw the landscape perfectly. But he couldn’t do much of any high-level thinking. His brain was like a recording machine, but it didn’t chunk much. Our brains seem to have the power to do one or the other — record and remember every detail, or chunk it to higher level concepts and forget the details. We can’t seem to do both. The fact that you could not fly over a city and remember every detail is not something to worry about. Our brains are great at knowing what to forget. We actually have to teach computers to do the same.

Morris: Frankly, I have (at best) a fuzzy understanding of the issues that involve artificial intelligence (AI) versus human intelligence. In your opinion, which of those issues are most important? Why?

Maney: AI uses a complex set of rules — algorithms — to get to a conclusion. A computer has to calculate its way through all those rules, and that takes a lot of processing. So AI works best when a small computer is using it on a small problem — your car’s anti-lock brakes are based on AI. Or you need to use a giant computer on a big problem — like IBM using a room-size machine to compete against humans on Jeopardy in 2011.

The brain doesn’t work that way.

Morris: In your opinion, which connections thus far between neuroscience and computer science have proven to be most significant? Why?

Maney: Computer science is just beginning to learn from neuroscience. We’re starting to see a handful of academics identify themselves as “computational neuroscientists.” They’re using the brain to find new ways to make computers operate, and using computers to learn about the brain. It’s people like Rajesh Rao at the University of Washington, who is experimenting with robots that learn how to navigate around a room roughly the way a baby might.

Morris: In your opinion, which connections yet too be completed will prove to be most important? Why?

Maney: Eventually, we need to have computers that work differently from the way they do today and have for the past 60-plus years. We’re capturing and generating increasingly massive amounts of data, but we can’t make computers that keep up with it. One of the most promising solutions is to make computers that work more the way brains work.

Morris: On Page 123, you observe, “Predictive, talented systems will be built around the idea that a little bit of the right in formation just ahead of time can be more valuable than a boatload of information later.” Which companies are now working on that and what do preliminary results seem to indicate?

Maney: Companies are beginning to experiment with real-time, predictive technology that borrows some ideas from the way our brains work. Sam’s Club, for instance, uses the data it has about its members to be able to predict, with scary accuracy, what each customer is likely to buy next — and then offer coupons on those items to that customer. Caesars Entertainment — the big casino company — is using it to predict in real time, as things are happening, what’s going to make a particular customer satisfied. If one guy gets mad every time he loses $200, the casino might know that he’s about to lose his 200th dollar, and instantly offer him a free meal at the buffet

Morris: How specifically can the two-second advantage help to create a better world?

Maney: The promise is that by becoming instantly and constantly predictive, it could solve some pretty difficult problems. Toward the end of the book, we detail how we think the Federal Reserve could use it to constantly adjust the economy. These kinds of systems might do a better job predicting terrorism attempts. There’s one example of an experimental system that can help save the lives of premature babies by constantly watching their vital signs and predicting when they’re about to have a problem.

Morris: How specifically can increasingly smarter machines help people to be come smarter?

Maney: As researchers like the computational neuroscientists do their work, or as others like Henry Markram of the Blue Brain project use computers to make models of brains, we learn more about how human brains work. And that leads us to ideas about how to make human brains work better.

Morris: Let’s say that someone carefully reads and then carefully re-reads The Two-Second Advantage. That person “gets it” in terms of what must be done to develop predictive talent. Where to begin?

Maney: Begin with what we do when raising children. Some of what we’re learning suggests a balance between exposing children to new things, yet giving them a chance to repeatedly experience something they enjoy, which builds “chunks” of information in their brains. Some good news, though, is that we’re also learning that adults can learn to be talented at something if they engage in what scientists call deliberate practice or deliberate performance.

Morris: Which question had you hoped to be asked during this interview – but weren’t – and what is your response to it?

Maney: I suppose you didn’t ask what I’m doing next. I won’t go too much into it now, but I will say that it’s taking me to India, which is going to play a gigantic role in where the world economy goes next.

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Kevin Maney cordially invites you to check out the resources at these websites:

Kevin ManeyIn his own words….


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