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About me: I'm an unrepentant generalist finding my way in a world of specialists. I started this blog to review books, but I now talk about topics ranging from management to cognition to social software.
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I’ve been a fan of Jane McGonigal for a few years now, and enjoyed playing her Cruel 2 B Kind game in the Come Out and Play festival two years ago. So when she said she was running another game in this year’s festival, I signed up.
The game ties into the Olympics in that it’s a “Lost Sport” that was allegedly banned in Ancient Greece. In cooperation with the Olympic Committee, Jane is running an entire alternative reality game around the sport. The linked wiki includes rules for the Lost Sport itself, aka “The Labyrinth”.
The idea is that a labyrinth is laid out (Jane used chalk yesterday, but string can also be used). A set of people stand on the lines of the labyrinth to form the walls. A blindfolded runner is placed in the center of the labyrinth, and has to make their way out as fast as possible. The wall can guide the runner by humming; in particular, the people ahead of the runner hum, and stop humming as the runner passes them, so the runner just runs in the direction of the hum.
While being in the wall might seem boring, it turned out there were several subtleties. For instance, realizing that the runner runs in the direction of the hum means that you need to stop humming before the runner gets to you, or they’ll run into you. Also, only hum when you have direct line-of-sight to the runner or they’ll run into the wall - the labyrinth has 180-degree corners which are very confusing if the wall doesn’t coordinate the humming. It helps to stick your head out into the middle of the walkway when humming so that the runner can run directly toward the hum.
The really fun bit is that there aren’t enough people to form the walls of the full labyrinth. So after the runner passes you, you have to get ahead of the runner to form the walls that don’t exist yet. Since the labyrinth is approximately circular, the best strategy we came up with was to have both sides of the labyrinth take a step outward, rather than trying to have the inner wall people squeeze through to form the outer wall. Towards the end, as the numbers dwindled, we didn’t even have enough people to do that, so things got pretty silly as the wall raced to try to stay ahead of the runner. We had one runner actually outrun the wall which left him very confused.
I like that the game is cooperative and competitive at the same time - each labyrinth is working with the runner to get faster times, but you can have multiple labyrinths competing against each other (we had four labyrinths side-by-side in Central Park yesterday, and Jane was in contact with other labyrinths in Paris, San Francisco and Tokyo, each competing for the best times). As an example of how the teamwork of the labyrinth really matters, one runner yesterday set a world record of under 14 seconds, and wanted to take another crack at beating that record at the end. We formed a labyrinth out of the remaining people, and it just didn’t work. Each of the four labyrinths had devised their own strategies, and we were bumping into each other and not being coordinated. Apparently, it had taken several runs for him to get that world record time as everybody learned where and when to hum and move.
I haven’t looked into the larger alternative reality game yet, but I really enjoyed the “Lost Sport”. I’ll keep an eye out for future labyrinth runs in New York.
On Monday night, I went to a talk by William Duggan, a Columbia business school professor who studies strategy, on a concept that he calls strategic intuition. Duggan has written a book on the subject, and has set up a blog to discuss the concept.
Duggan started by discussing the differences between expert intuition and strategic intuition. Expert intuition is built up by practice and familiarity with situations, of the sort described by Gary Klein in Sources of Power or Malcolm Gladwell in Blink. Expert intuition is using one’s built-up experience to instantly and unconsciously recognize the right thing to do in a familiar situation or its variants.
Duggan then differentiated strategic intuition by explaining that strategic intuition is the ability to recombine previous ideas into a wholly new pattern to address new situations. He uses von Clausewitz’s strategic primer, On War, to describe the process:
Clausewitz gives us four steps. First, you take in “examples from history†throughout your life and put them on the shelves of your brain. Study can help, by putting more there. Second comes “presence of mind,†where you free your brain of all preconceptions about what problem you’re solving and what solution might work. Third comes the flash of insight itself. Clausewitz called it coup d’oeil, which is French for “glance.†In a flash, a new combination of examples from history fly off the shelves of your brain and connect. Fourth comes “resolution,†or determination, where you not only say to yourself, “I see!â€, but also, “I’ll do it!â€
The rest of Duggan’s talk was describing different examples of strategic intuition, such as Napoleon’s strategy in a critical battle. He pointed out that none of these people invented something new - they just recombined previous elements in new ways. For instance, he described the Google guys as combining data mining techniques from their academic research, AltaVista’s search crawling, the idea of academic citations used as a ranking method, and Overture’s ad placement. Duggan gleefully used T.S. Eliot’s quote “Immature poets imitate, mature poets steal” to illustrate the value of looking out into the world to find the missing piece that might make all the difference.
I like the strategic intuition concept in general. I’ve experienced that flash of insight a few times; as I describe in my cognitive subroutines post, “I had one of those moments where I connected a bunch of ideas, and synapses lit up”. Strategic intuition also appeals to me in that it provides a useful role for a generalist; specialists excel at expert intuition, but only generalists can bring the wide-ranging set of ideas and freedom from preconceptions that are necessary for strategic intuition in Duggan’s model.
I am a bit skeptical of how well supported this model is. He claims it’s based off the intelligent memory hypothesis of how the brain works, which I assume is what is described by Hawkins in On Intelligence. I see how that would apply to expert intuition, which builds in common responses at lower layers of the neocortex, but it would seem to fall short in strategic intuition. This may be answered in his book, so I may have to pick that up at some point (after I’ve finished the ten books lying on my floor in various stages of completion).
I’m also skeptical of Duggan’s contention that this primarily happens in the mind of one person. He started the talk by asking people where they got their good ideas, and got answers like “in the shower”, “while running”, and “late at night” and used those answers to scoff at the value of typical group brainstorming sessions. I find this interesting, because I think by talking, and often get great ideas in conversation with others. If gathering a bunch of ideas into one’s brain is advantageous for strategic intuition, it would seem to be even better to combine the ideas across two or more brains. Thinking by myself often gets me stuck in ruts that I can’t escape (which makes me unable to achieve the “presence of mind” Duggan cites as being key), and talking to somebody else breaks me out of those ruts. It seemed like Duggan undervalues the role that conversation with others can play in strategic intuition (again, perhaps something he covers more in the book). I think this is one of the roles that a generalist plays - being able to combine ideas from multiple people to create flashes of insight that could not be conceived from within any one person.
Duggan’s concept of strategic intuition does help to answer a question I’ve been struggling with since watching a Malcolm Gladwell talk about what constitutes genius. In that talk, Gladwell differentiates between genius and expertise. Genius is just being flat-out smarter and seeing things others can’t. Gladwell uses the example of Michael Ventris, the man who was able to decipher the Linear B language in a couple years in his spare time, after others had spent decades trying to figure it out. Other examples would be people like Einstein or Tesla.
Gladwell contrasts genius with expertise by citing the “10,000 hour rule”, where he claims that it takes 10,000 hours (approximately 3 hours a day for 10 years) of deliberate practice to become a world-class expert at something. Gladwell finds it interesting that talent or genius has almost nothing to do with it - if you have the persistence to put in that 10,000 hours of deliberate practice, you will be an expert. He uses the interesting example of Roger Wiles proving Fermat’s Last Theorem - Wiles wasn’t a genius, and was not particularly gifted among mathematicians, but Gladwell observes that he was probably the first mathematician to just work at Fermat’s Last Theorem for 10,000 hours and he eventually cracked it. Another example would be somebody like Edison with his 99% perspiration quote.
The 10,000 hour rule really dismayed me when I first heard Gladwell speak about it partially because it makes so much sense. It takes that sort of dedicated repetition and practice to build up the unconscious machinery and cognitive subroutines to see beyond the basics. This applies in games like chess and tennis, where dedicated prodigies can become world-class competitors as teenagers (ten years after they start), as well as most careers. And the question that faced me was where I was spending my 10,000 hours.
Duggan’s talk gives me some hope in providing a new framework for the value a generalist might have. Strategic intuition is the ability to bring disparate elements together by seeing the world with a fresh perspective (what von Clausewitz called “presence of mind”), which is precisely the value I hope to achieve as a generalist. Rather than extend the limits of an existing field as an expert might do, it’s the ability to remix fields and combine them in new ways. I wonder if it’s possible to spend my 10,000 hours as a generalist, and, as Seth Godin put it, specialize in being a generalist. I guess we’ll find out.
I’ve been out of touch for a bit (I officially graduated from Columbia as evidenced by the happy cap’n'gown icon to the left, then ran off to California to marry my sister off and see some friends afterwards, and then was struck down by a bug from all the excitement), but it’s time to get back into the blogging habit. But we’ll ease back into it with a less serious post.
I’ve been thinking about the difference between New York and the Bay Area, partially because I just visited California and everybody asked me what I thought of New York, and partially because I’m starting to try to figure out where I want to end up long-term. It’s also a relevant topic on teh Intarweb, as Paul Graham wrote an essay comparing various cities, with a focus on New York vs. San Francisco vs. Boston. So I’m going to over-generalize wildly with my takes on the various cities, since those are the three cities I have experience with as an adult.
My typical response when asked what New York is like is to comment that everybody who comes to New York does so to rule the world. They may be in finance or art or fashion or media or theater, but they come to New York to be the best in the world at what they do. There is a palpable energy and ambition about New Yorkers and everything moves faster here as a result. It’s an exhausting environment of people who work hard and then play hard by staying out all night enjoying the nightlife available only in New York.
Another thing I’ve noticed about New Yorkers is that they tend to play the finite game they are given. While they want to be the best, they tend to define “the best” in terms of the industry/field as it currently exists. So they work their way up through the ranks, and look for chances for their big break. This playing within the system tends to promote a competitive zero-sum attitude, as there is a limited amount of attention in any field, and if I have the attention, you don’t. New Yorkers love working out ways to game the rules and beat the system (as evidenced by lengthy discussions about apartment searches), but tend not to question the rules themselves. Some people are working on this, including Charlie with nextNY (who has his own scathing response defending New York), but it’s a lot of inertia to overcome.
In contrast, I think the Bay Area culture tends to be more laid-back. People come to California to chill out rather than to rule the world. This isn’t to say that Bay Area folks don’t work hard, but I know very few people in California who work the 14-hour days that many New Yorkers do. Bay Area’ers do their jobs and do them well, but also spend more time enjoying other pursuits, especially the great parks available in the Bay Area (psst: for those about to give me specific examples of relaxed New Yorkers or driven Bay Area’ers, remember that I’m overgeneralizing wildly).
I also think the Bay Area culture tends to be more collaborative, partially as a result of being more innovative. There are lots of ideas in the world, and lots of ways in which everybody can succeed. People in the Bay Area aren’t working within a system which can only crown a few winners - they are each working on their own thing, so there’s no direct competition (well, except for human resources). This promotes a more non-zero-sum attitude towards the world, one where people can look for ways to help everybody win. When presented with a system, people in the Bay Area look for ways to change the rules rather than beat the system. I’m not sure why that is, whether it’s the strong startup culture, or the liberal Berkeley political heritage that questioned the system, but I feel like more people there are playing the infinite game.
To take a specific example of this dichotomy, several teachers in the Columbia program said “If you don’t learn to play golf, you’re never going to move up in the world.” It’s just taken as an axiom that to move up the corporate ranks, golf courses are the place to do it because that’s where the power brokers are. In the Bay Area, my friends at Squid Labs tell me that “kite surfing is the new golf”, because all the young tech CEOs love this crazy intense sport, including the Google founders.
I also disagree with Graham that Boston is about ideas. Boston is about tradition. Boston is America’s oldest city, and families have lived there for generations. This pervasive sense of history, where you walk by Revolutionary War sites on a daily basis, creates a degree of conservatism, not in a political sense, but in the sense that people are bound by the way things are. I think that’s one of the reasons startups have not been as successful in Boston - the people who would break tradition in that way just don’t fit in, as they have to overcome more inertia both socially and resource-wise. Rather than fight that inertia, they move to California instead, where there is no history to overcome and everybody’s on equal terms as newcomers.
I agree with Graham that the culture of academia which pervades Cambridge values smart people and ideas, but it values the way things are done more. For instance, tenure seems to be a completely broken system that doesn’t reward the best ideas or the best people, instead rewarding those that don’t rock the boat. Professors don’t like new ideas that might threaten their academic turf; as several people have quipped: “Academic politics are vicious precisely because the stakes are so low”.
I was trying to think of what the Midwest is about, as that’s where I grew up. I think the Midwest might be about community and, more specifically, family. I haven’t thought about it as much, as I’m extremely unlikely to move back there, but that feels right. Midwesterners are about having a family, creating a good life for your kids, helping out the neighbors, supporting the local teams, etc.
Now that I’ve found a way to offend people from every place I’ve lived, my over-generalized summary is that New Yorkers want to rule the world, where Bay Area’ers want to change the world. It’s not scientific at all, but it’s a topic I’ve been thinking about as I try to figure out where I fit in best, and where I want to end up in the long term. Comments definitely appreciated about both my observations and where I might fit.
As those of you who follow my other feeds know, I’ve taken up playing ultimate frisbee again with the Manhattan Ultimate league. While the main benefit is getting back into shape after two years of class-induced neglect, I also really enjoy playing ultimate because of the philosophy baked into the rules of the game.
If you’re not familiar with ultimate, the rules are pretty simple. On a field with two end zones, two teams of seven line up, one on each end line. One team starts the point by throwing the disc to the other. The disc can only be advanced by throwing to a teammate - once you catch the disc, you can’t continue running, and must hold a pivot foot stationary. If a pass is not completed, the other team takes over going the other way. Score by catching a pass in the end zone.
These rules make ultimate a truly team-oriented sport. An individual player can’t take over the game single-handedly, the way they do in basketball or football or baseball, because every pass involves two players. The way for an individual player to excel is to make their teammates better. When they don’t have the disc, they can help their teammates by getting wide open, or by rescuing poorly thrown passes with great catches. Once they catch the disc, their teammates don’t have to get as open because a good thrower will put it right into their hands away from the defender.
The best teams use everybody on the field, creating spacing with different people going in different directions. For instance, because I’m tall and relatively fast, I often run downfield routes, where my teammates can just put the disc up high and expect me to either out-run or out-jump my defender. Other teammates who have more agility dart in and out with underneath routes. Players who have good throwing skills hang back to give their teammates an easy throw when they get in trouble. You need a good mix of skills on the field working together to achieve success.
What’s interesting to me is the management lessons that can be learned from ultimate frisbee. Different sports lend themselves to different management practices. Football is a typical hierarchy, with a coach and a quarterback leading the troops in precision maneuvers. Basketball is like a design firm, with individual superstars able to freelance their way to excellence. I think ultimate frisbee is a great model for understanding the distributed management style necessary for knowledge workers, where everybody has their own expertise to contribute.
Like the good ultimate player, good managers of knowledge workers make their employees and coworkers look good by setting things up to be easy for them. They know their coworkers’ strengths and weaknesses and find ways to accentuate the strengths and minimize the weaknesses (like me running deep in ultimate where I can use my height and speed, without worrying as much about my weaker throwing skills). They don’t need to take credit for themselves, because they know that the team being more successful is credit enough. Returning to my current non-zero-sum theme, they realize that “growing the pie” of success will reward them far more than trying to grab a bigger share of credit for the existing “pie”.
Bad managers, on the other hand, are playing the zero-sum game, trying to make themselves look good at the expense of their employees. They are the ones who take personal credit for anything their group does, but makes sure to blame mistakes on their employees. The ultimate frisbee equivalent would be prima donnas who, while having superior skills, yell at their teammates about making mistakes, and making them miserable. Soon enough, their teammates stop caring and stop running as hard, and the prima donna has created a self-fulfilling prophecy of bad teammates.
Another interesting parallel between ultimate and management is that it takes time for teams to jell. While it’s fun to play pickup games in ultimate where you choose sides and go, teams improve immeasurably by playing together and learning each other’s tendencies. You learn which routes people like to run, which throws your teammates have (which influences which routes you run when they have the disc), how to cover for each other on defense, etc. And each team and each combination of players is different - in this league, our team has actually been suffering from having too many subs for each game, as the team can’t quite settle into a rhythm because each point has a different combination of players.
A good manager needs the same sort of time to make their team most efficient. It takes time to learn how different team members think, how best to work with them and persuade them. Building a team is a long process, as each person needs to develop trust and respect for their teammates, and find a role for themselves within the team, a place where they can specialize in a way that plays to their strengths. Following Katzenbach’s formula, they must also develop a common group purpose and accountability, such that they believe in the team and will do what is necessary to make the team successful, rather than looking out for themselves in a zero-sum way.
As an aside, I just re-read the Katzenbach post and realized that good ultimate frisbee teams match up perfectly with his criteria for teams: small number (7 on the field), complementary skills (handlers, mids, and deeps), common purpose and performance goals (scoring and winning), common approach (teams that are successful work together in a coherent fashion), and mutual accountability (it’s almost funny how many people on an ultimate team try to take the blame after a close loss - everybody focuses on the mistakes they made that cost the team a couple points).
I’m not saying all managers should go out and take up ultimate frisbee (okay, that’d actually be kind of cool), but I did find it interesting that this mindset of non-zero-sum thinking about management had me seeing the same lessons so clearly on the ultimate frisbee field. This may just be another example of me taking a single perspective and seeing it everywhere, but I think that ultimate frisbee may be a good exemplar for truly distributed management techniques, the sort that would be appropriate in a knowledge worker economy.
A few months ago, I read a post calling for authors for a book called The Age of Conversation. It sounded interesting, so I put in my name and will be one of 275 people (listed below) contributing a single page 400-word essay on the theme of “Why Don’t People Get It?”
Here’s where I need your help. When I signed up several months ago, May 15th, the deadline for contributions, seemed eons away. But May 15th is suddenly next week, and because I’ve been distracted by finishing up my degree, I haven’t started on my essay yet. I signed up to write on the topic of Business Model Evolution, and could use some help in brainstorming. I have the noodlings of some ideas, but I’m sure I can do better with the help of another few people.
Also, if anybody is willing to be an editor, that’d be great as well. I would just post drafts here on the blog, but the organizers have requested that essays not be posted before the book is released.
Thanks!
P.S. Following the lead of other authors, here’s the list of all 275 contributors with links to their online presences: Adam Crowe, Adrian Ho, Aki Spicer, Alex Henault, Amy Jussel, Andrew Odom, Andy Nulman, Andy Sernovitz, Andy Whitlock, Angela Maiers, Ann Handley, Anna Farmery, Armando Alves, Arun Rajagopal, Asi Sharabi, Becky Carroll, Becky McCray, Bernie Scheffler, Bill Gammell, Bob Carlton, Bob LeDrew, Brad Shorr, Bradley Spitzer, Brandon Murphy, Branislav Peric, Brent Dixon, Brett Macfarlane, Brian Reich, C.C. Chapman, Cam Beck, Casper Willer, Cathleen Rittereiser, Cathryn Hrudicka, Cedric Giorgi, Charles Sipe, Chris Kieff, Chris Cree, Chris Wilson, Christina Kerley (CK), C.B. Whittemore, Clay Parker Jones, Chris Brown, Colin McKay, Connie Bensen, Connie Reece, Cord Silverstein, Corentin Monot, Craig Wilson, Daniel Honigman, Dan Goldstein, Dan Schawbel, Dana VanDen Heuvel, Dan Sitter, Daria Radota Rasmussen, Darren Herman, Darryl Patterson, Dave Davison, Dave Origano, David Armano, David Bausola, David Berkowitz, David Brazeal, David Koopmans, David Meerman Scott, David Petherick, David Reich, David Weinfeld, David Zinger, Deanna Gernert, Deborah Brown, Dennis Price, Derrick Kwa, Dino Demopoulos, Doug Haslam, Doug Meacham, Doug Mitchell, Douglas Hanna, Douglas Karr, Drew McLellan, Duane Brown, Dustin Jacobsen, Dylan Viner, Ed Brenegar, Ed Cotton, Efrain Mendicuti, Ellen Weber, Emily Reed, Eric Peterson, Eric Nehrlich, Ernie Mosteller, Faris Yakob, Fernanda Romano, Francis Anderson, G. Kofi Annan, Gareth Kay, Gary Cohen, Gaurav Mishra, Gavin Heaton, Geert Desager, George Jenkins, G.L. Hoffman, Gianandrea Facchini, Gordon Whitehead, Graham Hill, Greg Verdino, Gretel Going & Kathryn Fleming, Hillel Cooperman, Hugh Weber, J. Erik Potter, J.C. Hutchins, James Gordon-Macintosh, Jamey Shiels, Jasmin Tragas, Jason Oke, Jay Ehret, Jeanne Dininni, Jeff De Cagna, Jeff Gwynne, Jeff Noble, Jeff Wallace, Jennifer Warwick, Jenny Meade, Jeremy Fuksa, Jeremy Heilpern, Jeremy Middleton, Jeroen Verkroost, Jessica Hagy, Joanna Young, Joe Pulizzi, Joe Talbott, John Herrington, John Jantsch, John Moore, John Rosen, John Todor, Jon Burg, Jon Swanson, Jonathan Trenn, Jordan Behan, Julie Fleischer, Justin Flowers, Justin Foster, Karl Turley, Kate Trgovac, Katie Chatfield, Katie Konrath, Kenny Lauer, Keri Willenborg, Kevin Jessop, Kris Hoet, Krishna De, Kristin Gorski, Laura Fitton, Laurence Helene Borei, Lewis Green, Lois Kelly, Lori Magno, Louise Barnes-Johnston, Louise Mangan, Louise Manning, Luc Debaisieux, Marcus Brown, Mario Vellandi, Mark Blair, Mark Earls, Mark Goren, Mark Hancock, Mark Lewis, Mark McGuinness, Mark McSpadden, Matt Dickman, Matt J. McDonald, Matt Moore, Michael Hawkins, Michael Karnjanaprakorn, Michelle Lamar, Mike Arauz, Mike McAllen, Mike Sansone, Mitch Joel, Monica Wright, Nathan Gilliatt, Nathan Snell, Neil Perkin, Nettie Hartsock, Nick Rice, Oleksandr Skorokhod, Ozgur Alaz, Paul Chaney, Paul Hebert, Paul Isakson, Paul Marobella, Paul McEnany, Paul Tedesco, Paul Williams, Pet Campbell, Pete Deutschman, Peter Corbett, Phil Gerbyshak, Phil Lewis, Phil Soden, Piet Wulleman, Rachel Steiner, Sreeraj Menon, Reginald Adkins, Richard Huntington, Rishi Desai, Beeker Northam, Rob Mortimer, Robert Hruzek, Roberta Rosenberg, Robyn McMaster, Roger von Oech, Rohit Bhargava, Ron Shevlin, Ryan Barrett, Ryan Karpeles, Ryan Rasmussen, Sam Huleatt, Sandy Renshaw, Scott Goodson, Scott Monty, Scott Townsend, Scott White, Sean Howard, Sean Scott, Seni Thomas, Seth Gaffney, Shama Hyder, Sheila Scarborough, Sheryl Steadman, Simon Payn, Sonia Simone, Spike Jones, Stanley Johnson, Stephen Collins, Stephen Cribbett, Stephen Landau, Stephen Smith, Steve Bannister, Steve Hardy, Steve Portigal, Steve Roesler, Steven Verbruggen, Steve Woodruff, Sue Edworthy, Susan Bird, Susan Gunelius, Susan Heywood, Tammy Lenski, Terrell Meek, Thomas Clifford, Thomas Knoll, Tiffany Kenyon, Tim Brunelle, Tim Buesing, Tim Connor, Tim Jackson, Tim Longhurst, Tim Mannveille, Tim Tyler, Timothy Johnson, Tinu Abayomi-Paul, Toby Bloomberg, Todd Andrlik, Troy Rutter, Troy Worman, Uwe Hook, Valeria Maltoni, Vandana Ahuja, Vanessa DiMauro, Veronique Rabuteau, Wayne Buckhanan, William Azaroff, Yves Van Landeghem
As I’m finishing up my master’s program at Columbia, it’s time to reflect back on my experiences of the past two years. I wrote up an email to Frank Giardini from the comments on yesterday’s post, who asked about comparing the program to getting an MBA, and realized I might as well post my thoughts in public.
I have not pursued an MBA myself, so my perspective is admittedly biased. I’m also biased by the book Managers not MBAs, which points out how artificial the skills learned in an MBA program are when compared to the skills needed to be a manager. That being said, let me extol the benefits of the Technology Management program.
The Technology Management program has a very specific goal - it is designed to give experienced technologists the business tools they need in order to take their technology domain expertise and become successful technology executives. So we took classes in corporate finance, innovation, technology and the law, operations, knowledge management, marketing, etc. These are all standard classes that might be taken in an MBA program, but each class is taught with a technology focus so the examples and the assignments involve challenges relating the subject to a technology organization.
It’s designed for experienced professionals - most students in the program have 8-15 years experience, so the class discussions are grounded in that experience. Instead of theoretical musings, most discussions come back to “When I was in that situation, this is what I did”, which is far more useful in my opinion. For instance, in the innovation class, when we were discussing the phase-gate method of
managing innovation, I was able to offer my perceptions from having gone through a project run with that method.
The other students are definitely a highlight of the program. I have really enjoyed working with and learning from my classmates over the past two years. I also look forward to continuing to benefit from their knowledge and expertise in the future, as we plan to stay in contact via our Google Group and other social networking tools like LinkedIn.
The centerpiece class of the program, in my opinion, is Alan Morley’s class, “Behavioral Challenges in Technology Management”, or Becoming a CIO, as I like to call it. The class covers the financial and strategic tools necessary to become an effective executive and teaches how to synthesize those tools into a coherent plan. See my linked post for more details.
The master’s project itself is developing a business plan and pitch for a technology venture. Some people do an internal project at their company, while others pursue an idea for a startup. At the end of each term, each student has to present their master’s project to a panel of three mentors. They have ten minutes to give their project pitch with another ten minutes to take questions, and they are graded on whether the panel would fund the project based on that presentation. It’s a terrifying but educational experience, as these presentations (whether to boards of directors or venture/angel boards) are what executives face when getting projects funded.
The program also finds each student an industry mentor as a guide, somebody who offers feedback on the project from the perspective of somebody who is already a successful executive. My mentor was Jon Williams, who was CTO of Kaplan Test, and is now the CTO of iVillage. Other mentors are similarly distinguished, generally CIOs and CTOs from different industries in New York. I am extremely fortunate to have worked with Jon over the past two years, as he has been unstinting in sharing his advice and knowledge with me.
I highly recommend the Technology Management program, and think I learned more from it than I would have from an equivalent MBA program. It’s not right for everybody as it definitely has a technology focus, and may be a little light on general management techniques. But it succeeded in giving me new perspectives and new ways of looking at the world, which can only help me as I continue to move up in the management hierarchy.
Yesterday was the last class of my master’s program at Columbia (I have one more final next week, but no more class sessions). A bunch of us technology management students went out for drinks afterwards in celebration, and ran into another group of students from our marketing class. And it was interesting chatting with them and getting their perspective on the class, since we hadn’t mixed much during the class itself.
It was also interesting to hear what they thought of me personally. Apparently I had been dubbed “physics boy” after I let it slip in class that my background was in physics (I raised my hand in one class when the professor asked who had experience with data mining, and he asked me what my experience was).
I was also surprised at the resentment a couple of them felt towards me. I had spoken up in class pretty regularly, as I was trying to ensure my class participation grade, but I had apparently come off as a snarky know-it-all. Admittedly, that’s a reasonably accurate description, but I had thought I had learned how to keep that under control. Good to know I should still be working on that.
The reason I’m writing, though, is that one person (fuelled by alcohol) complained that I was “too smart”, and made the rest of the class look bad. I find this interesting because it ties into the research of Carol Dweck, who studies the corrosive effects of praising people for innate qualities like intelligence rather than acquired qualities like persistence and effort. If we are valued for our intelligence, then when somebody comes along with more intelligence, we are less valued. We have less worth. And that’s devastating.
I’ve experienced this effect firsthand, as going to MIT is a brutal experience. All students arrive at MIT having been the smartest person in the class for their entire lives, so it’s an incredible shock to their self-image to meet people who are not just smarter, but ridiculously smarter (like my freshman physics classmate who regularly doubled my test scores). MIT’s former policy of all freshmen being graded pass/fail was a life saver for me, as it took me an entire year to adjust to this new reality.
Another implication of Dweck’s research is that praising for innate qualities contributes to a zero-sum view of the world. If somebody else is smarter, that takes away from the specialness of my own intelligence. Their gain is my loss. So it’s in my interest to tear them down or find ways to show how they aren’t as special as me.
But that’s not how the world works. I need to finish Robert Wright’s Nonzero one of these days, as it details the ways in which progress occurs because of non-zero-sum interactions. When we “grow the pie”, everybody benefits. When we fight over our percentage of the pie, everybody misses out on those possible benefits, even if they have a larger share of the existing pie.
We go further when we work together and learn from each other. In industry, we benefit from being surrounded by talented coworkers, as our collective product is more likely to be successful. This assumes that one is in a team-oriented environment, and not one that practices destructive practices like rank-and-yank. But, in general, we try to hold on to the talented people around us, as we benefit from knowing them - talented people do wonderful things which we can participate in and learn from. They also tend to know other talented people in a meritocratic version of the old boy network, and being able to draw on those weak ties is a huge benefit.
Another interesting observation is that I’ve never gotten any vibe of resentment from my technology management classmates. In fact, they were defending me last night to this person. This provides some confirmation that real world experience leads away from the zero-sum your-success-is-my-loss view of the world, as everybody in my program has years of experience in industry. Meanwhile, the classmates who felt resentment were much younger - I think they were recently out of college. They may still be thinking they are being graded on a curve, where somebody else’s success pushes one’s own grades down.
I’ve been thinking a lot about the power of non-zero-sum thinking, and have been seeing it everywhere recently. I’m not sure it totally applies to this particular situation, but I think it does.
P.S. I should start posting more regularly again with classes being done. As usual, I have a ridiculous backlog of ideas that awaits only me being motivated enough to write them up.
P.P.S. I couldn’t figure out how to fit this into the post, but I wanted to comment about the weirdness of being praised for intelligence. There’s no reasonable reaction. “Thank you” is disingenuous, as intelligence is innate and I can’t really take credit for my genes. It’s also weird because intelligence really doesn’t mean that much in the big picture. Effort and persistence matter far more. Intelligence and all other innate qualities are only a starting point - what you achieve with the gifts you have been given is a far better measure of character. We should measure ourselves against our potential and what we could achieve, and starting with more luck in the gene lottery just means our potential is higher and we should be striving to achieve more.
Over the weekend, I went for a walk and listened to Nassim Nicholas Taleb’s talk at the Long Now (viewable at the Whole Earth site, and summarized here). I’ve been doing this for a few weekends now - I can never pay enough attention to listen to a talk like that if I’m at home because I get distracted, but going for a nice long hour-and-a-half walk is a good way to burn off some energy and get educated at the same time. I recommend the Long Now podcast if you’re looking for good talks from interesting intellectuals.
Taleb recently published The Black Swan, a follow-up to his original book, Fooled by Randomness, and uses the talk to discuss some of the ideas from that book. I won’t try to summarize the whole talk but he made two key points that I want to record for future reference. Both points derive from how our intuitions and our mental tools are not equipped to handle nonlinear models. This may seem like an abstruse topic but had very real consequences in the subprime meltdown, when investors theories’ did not take into account non-linear exponential failures of their models.
Taleb posits two worlds: Mediocrestan and Extremistan. He describes Mediocrestan by having the audience imagine a group of 100 people and their distribution of weights. Then he says to determine how the average weight of the group would change if we added the heaviest person in the world to that group. It turns out to not affect the average that much - even if we add a 1,000 pound person, it shifts the average by only 0.5% or so. This is the world of the normal Gaussian distribution that we understand very well with standard deviations and the like.
Now do the same thought experiment, but use people’s wealth instead. Imagine a group of 100 typical people, and their average wealth. Now add Bill Gates to the group. At this point, 100 of the 101 people in the group are below average in wealth, and Bill Gates has approximately 100% of the wealth of the group. This is the world of Extremistan, where outliers can blow up the normal distribution. This is the world of the Black Swan.
And what’s interesting is that we are so bad at dealing with Extremistan. We just don’t intuitively get it, even though we are surrounded by examples of it. Finance and wealth. Book publishing (a significant portion of all book sales are Harry Potter books). The music industry. eBay. We live in an Extremistan world, but our intuition (evolved in a simpler time without network effects) is still stuck in Mediocrestan. So we have to beware of our instincts, because they will get the wrong answers. And we have to beware of charlatans using Mediocrestan theories because they are calculable - it’s like physicists treating everything as a simple harmonic oscillator because that’s the only equation they can solve.
Another example of Extremistan comes from a completely different source. I’m currently reading Poor Charlie’s Almanack, a book of the wisdom of Charlie Munger, Warren Buffett’s investment partner. Munger notes: “If you look at Berkshire Hathaway and all of its accumulated billions, the top ten insights account for most of it.” He also quotes Buffett as saying:
“I could improve your ultimate financial welfare by giving you a ticket with only twenty slots in it so that you had twenty punches - representing all the investments that you got to make in a lifetime. And once you’d punched through the card, you couldn’t make any more investments at all. Under those rules, you’d really think carefully about what you did, and you’d be forced to load up on what you’d really thought about.”
The typical investment strategy is diversification - invest in lots of things and trust in the average, which would work in Mediocrestan. Buffett and Munger have internalized the idea of Extremistan in investing and exploited it to their advantage by realizing that there will be successes wildly out of proportion to the norm and targeting only those investments.
The other illustration of nonlinearity that Taleb used was to imagine an ice cube melting into a small puddle. Now imagine starting with the puddle and trying to reconstruct what the ice cube looked like. You can get the volume of the ice cube, but you can not derive the shape of the ice cube because there are an infinite number of shapes that could have melted and left that puddle. In other words, there is not sufficient information in the final state to determine the initial state; information is lost in this process. He uses this observation to illustrate why he doesn’t trust theories; because the observable world does not constrain theories enough, many theories can fit existing data without providing predictive power.
This multiplicity could also be illustrated by taking the sequence: 1, 2, 3. What’s the next number? Most of us would answer 4. But the answer could be anything from 0.1 to 100,000. I can construct an equation that would give any answer you chose as the fourth entry in that sequence. There are an infinite number of possibilities that fit the available data. Taleb reminds us of this multiplicity and displays extreme skepticism when decisions are made based on believing just one possible theory.
Taleb’s ice cube reminds me of a discussion from Zen and the Art of Motorcycle Maintenance. Pirsig quotes Poincare as saying “If a phenomenon admits of a complete mechanical explanation it will admit of an infinity of others which will account equally well for all the peculiarities disclosed by experiment.” This is the dirty secret of science - theories are worth nothing, because an infinite number of theories can explain any experimental result, including such outlandish ones as the Flying Spaghetti Monster. Popper’s claim that theories must be falsifiable to be scientific is a consequence of this - every theory is always one experimental observation away from being disproven. Scientists live in a world where they are sifting through an infinity of possible theories, trying to choose one that best fits their observations, but knowing that their theories can never be proven true, only proven false.
I don’t really have any deep analysis here. I liked the visual imagery Taleb used to illustrate his points, and wanted to record that in this post. After listening to his talk, I may have to get The Black Swan from the library this summer to see if the rest of the book is of similar quality.
I just realized I don’t have an “About Me” page on this blog. You can get a sense of who I am from reading the various posts and browsing the archives, but I figured it might be handy to have an introduction post. This is partially inspired by skimming through Derek Powazek’s book Design for Community, which emphasized the importance of making the people behind the site real. So…
I’m Eric Nehrlich. I call myself an unrepentant generalist.
What does that mean? It means I specialize in nothing. Or everything.
My being a generalist is partially aptitude (I learn fast so I can pick up new ideas quickly, and I have enough mental models that adding more is easy), partially limitations (I don’t have the focus necessary to dive deep into a subject for five years, as I found when I tried to be a grad student), and partially interest (I like talking about everything). The phrase “Unrepentant Generalist” is a reminder to myself to glory in rejecting specialization, and to explore where this generalist path leads. I use this blog to help trace that path, recording my thoughts on everything from cognition to community to conversation to design to management to media to philosophy to politics to stories.
I didn’t mean to be a generalist; in fact, I had planned to be a specialist. When I was a kid, I decided I was going to be a particle physicist because I was a big nerd and wanted to be Richard Feynman when I grew up. I did a high school science fair project at Fermilab, went to MIT where I worked on the Superconducting Super Collider over the summers, did an internship at CERN, and went to grad school at Stanford to work on the Stanford Linear Accelerator. But instead of studying physics all the time like my compatriots, I was singing in the chorus, playing volleyball, going to various talks, running the alt.tv.buffy-v-slayer FAQ, etc.
So I left Stanford to try a different specialization. I had always liked computers even after taking several CS courses at MIT, and friends and advisors often wondered why I chose physics over computers when I had a knack for getting computers to do what I wanted. Since physics hadn’t worked out, I went to work for a friend as a software consultant. Working with a variety of companies taught me about software, but taught me even more about people. I learned that the best technical solution was not always chosen, and that clients rarely asked for what they wanted, so I started to see the limits of being a specialist.
I then joined Signature BioScience, a highly interdisciplinary startup developing new instrumentation for drug discovery. Working there gave me a unique insight into the dynamics of an organization, as the software I developed had to reflect the interests of everybody from engineers to testers to biologists to physicists to managers. I eventually grew into a “union foreman†role, representing the interests of employees to the management team, as I had worked with all factions of the company and understood their issues. And I began to see my value to Signature was not my specialized software expertise - it was my ability as a generalist to meld different viewpoints into a coherent synthesis that happened to be expressed in software.
Signature BioScience unfortunately went bankrupt due to some poor decisions by the management team. The failure of Signature as a company showed me how even a great technical team’s efforts could be wasted by key management decisions. I realized that the value I could bring to an organization by improving its management would easily dwarf any technological contributions I could make, given the multiplier effect of management decisions on the rest of the organization. And my skills as a generalist were well-suited to management, as managers have to balance the interests of their group with those of the larger business, so it requires the ability to see from multiple perspectives.
With this in mind, I moved to New York in 2006 to join a Software Management Training Program at Fog Creek Software, and concurrently completed a M.S. in Technology Management at Columbia University, a degree that is similar to an MBA but with a focus on using technology strategically to serve the business.
Upon completing the program, I decided to move back to California to work for Google in Mountain View. I will be an analyst on a sales finance team that develops revenue forecasting models to help Google executives make decisions. I was drawn to the position because I get to use both my quantitative skills in building the models and my generalist skills in that the models are built on understanding everything from the technical product decisions being made, to sales and marketing strategies, to what customers and competitors are doing, to the larger economic and business environment.
(last updated August 2008)
If that didn’t satisfy your curiosity, here are some links to other versions of me:
Invitation
Now it’s your turn. I’d love to be introduced to any or all of my readers. Feel free to do so in the comments, or send me an email if you’re too shy. Say who you are, why you read this blog, and anything else you want to share.
I went to New York Bite Club last weekend. Bite Club is an underground eating club which serves gourmet dinners in private apartments around New York. It was excellent. I highly recommend it.
It was an amusing process to get into the dinner. I had to apply online at their site, and then exchanged a few emails with the organizer. Then to ensure my seriousness in attending the selected dinner, I had to drop off a cash deposit - it was fairly odd to walk into an office building, go into a random office, and drop off an envelope full of cash to a receptionist with a knowing nod. I was then sent an email with the location, with the warning “IT IS VERY IMPORTANT that silence is maintained while walking through this hallway. All noise can be heard by neighbors and that can bring a lot of attention to our operation, which isn’t going to be acceptable.”
Saturday night finally arrived. I got into the elevator with three other people. We realized we were all going to the same floor, and grinned sheepishly at each other. We walked into a typical New York apartment with the main room filled with tables and chairs, and a couple people working feverishly in the kitchen. We were assigned seating (the organizer had tried to balance the tables with appropriate dinner partners). I was at a table with a Wall Street trader and a manufacturer’s representative. We started talking, but our thoughts were on the food to come.
The night that I went was a 7-course winter tasting menu with a wine pairing (click on any picture for the Flickr set). It was _fantastic_. Comments on most of the courses:
The thing that amazed me was that this was not a specialized kitchen - this was a regular New York kitchen. They brought in extra dishes, an extra set of shelves to hold them, and a table for prep, but other than that, there’s really no excuse for me not to be able to make such dishes myself. Well, except for lacking culinary skill.
Oh, that was the other amazing part - when we inquired as to which restaurant the chef was associated with, we found out that he just does this for fun. His day job has nothing to do with food. He just really enjoys cooking and trying new things, and started throwing bigger and bigger dinner parties until he decided to make it a regular event.
All in all, it was a lovely evening. Four and a half hours of good conversation, while being pampered with a wonderful seven course dinner, each paired with a well-chosen wine. It was pricy, but still far cheaper than a similar dinner would be at a haute cuisine restaurant. Definitely an experience I look forward to repeating as soon as I can raise the funds 
