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

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.

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.

She is my “it’s complicated” on Facebook.

[updated to add: the friend in question cites xkcd as his inspiration]

I think this quote is wonderfully transcendent in capturing the zeitgeist, so much so that I’m going to spend a blog post unpacking it. Grant McCracken introduced me to the anthropological concept of unpacking in this essay contest from last year (the winners are here), where he asks his readers to supply the “underlying cultural notions” that help to explain what has been observed. So let’s take a look at what’s going on in this quote.

Let’s start with the mention of Facebook. Most people are at least aware of Facebook at this point - it’s a social networking site where one can share one’s life with one’s friends and acquaintances. In particular, one can describe one’s status in a variety of ways, write notes about one’s life, put up pictures from one’s life, etc.

One way in which Facebook is changing the culture is that there is an increased awareness of the public performance aspect of our actions. The Facebook generation is aware that they are always on stage and are comfortable with it in a way that writers like Daniel Solove certainly wouldn’t be. In fact, they use Facebook as a platform to communicate with their friends and update them more efficiently than could be done by communicating with them individually using SMS or phone calls. So it becomes a big deal when they change their relationship status on Facebook or when somebody edits their Top 8 friends on MySpace. Using such platforms to manage one’s social life becomes a reflexive performance with an explicit awareness of one’s audience; the platform is used to deliver public messages to one’s community about shifting social relationships.

The next concept I want to unpack is “it’s complicated”. In Facebook, you can describe your relationship status as one of: single, in a relationship, engaged, married, in an open relationship, or it’s complicated. The first four are the straightforward ones that everybody expects, but the last two are decidedly non-traditional. “It’s complicated” is a nice catch-all term for relationships that don’t fit into the normative bounds of society, where it takes time (and possibly a whiteboard) to explain what’s going on.

It seems like such relationships are becoming more common, and possibly even more accepted. My friend who lives with his two boyfriends is often disappointed when he gleefully explains his living situation and people say “Oh, that’s cool” rather than being shocked or dismayed. Conservatives might rail against such non-traditional relationships, but American society is slowly moving in the direction of “if it makes you happy, it can’t be that bad” (to quote Sheryl Crow).

I also wonder if Facebook including “it’s complicated” as a first-order option for relationship status will hasten the acceptance of such non-traditional relationships. Can the widespread use of Facebook redefine social norms? On Facebook there is no stigma associated with such relationships, as they are just another option in the dropdown box for relationship status (unlike other forms where one has to choose the dreaded “Other”). As people use Facebook to represent themselves, will the implicit acceptance of such relationships by the software influence how people think of those relationships?

I love how this one sentence indicates the direction our society is taking as we explore relationships that do not fit into the traditional nuclear family and how it affects us when our previously private social lives are a matter of public discourse. I don’t know if I have done justice to either the statement or the idea of unpacking, but hopefully this exercise gets you thinking about how even simple statements can tell us much about the state of our culture.

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.

Hi!

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 two years ago to join a Software Management Training Program at Fog Creek Software, and I am currently in the process of completing my 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.

If that didn’t satisfy your curiosity, here are some links to other versions of me:

LinkedIn

The corporate version

LiveJournal

A more informal version, which mostly cannibalizes content from here, but where I occasionally post memes and less serious thoughts that I don’t feel like blogging.

Bloglines subscriptions

A list of the blogs I follow, although I’ve set up LiveJournal to follow most of the personal blogs.

del.icio.us

Interesting links I want to share but don’t want to write up into a full post. Also, a way to generate new content for my sidebar when I don’t update my blog.

Twitter

A place for me to send out occasional whinges about my life.

Facebook

I wanted to hang out with the cool kids on Facebook, but all the content there is pulled from LiveJournal and Twitter.

My ancient web page, first started in 1994

Completely out of date since being superceded by this blog.

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.

What’s interesting is that NBC lost money from me in this process. I had been paying $2 an episode to watch Battlestar Galactica last year on iTunes. On hulu.com, I watched it for free, except for a total of two minutes of advertisements, clumsily sprinkled throughout the episode. I can’t imagine that the advertising revenue they are getting is worth more than the cut of the $2 they got from iTunes. So how does this make sense? It doesn’t to me. And there are a few other questions about television that don’t make sense to me either.

Why doesn’t HBO have an online portal where I can see their shows? I want to see the final season of The Wire. I don’t even get basic cable, so it would cost me $40/month to get the “standard cable” package, and then another $15/month to get HBO on top of that. It doesn’t make sense for me when I just want to watch one show. I went to iTunes but The Wire was not available there, even though I would have gladly paid $2 an episode. Heck, I would have paid $5 an episode which is comparable to their DVD pricing of $50 for a season); after all, I pay $10 for a two hour movie, and an episode of The Wire is much better than most movies. But HBO had no way for me to give them money in exchange for watching a specific show as it is released (I have to wait for the DVD).

Why do all broadcast networks have an online video on demand service now? I love it as a consumer. If I forget to tape a show, or if two shows I want to watch are on simultaneously, I can just go to the network’s site a day later and watch the show I missed. Most sites even store four episodes so that I can catch up on a series if I lost track for a few weeks. NBC has the entire run of Friday Night Lights online to try to build viewership. While it’s tremendously convenient, I don’t know how it makes sense economically (NBC doesn’t even put advertising in their online episodes).

I suppose one possibility is that the networks are using online rebroadcast of their content as a way of gaining access to a highly profitable market segment, which would be people like me that have broadband video connections and the tech savvy to even want to watch a TV show online. The problem I see with this explanation is that they don’t have any way of targeting me currently. I don’t login to hulu.com or to the network sites. So unless they start delivering advertising interspersed with the show, they’re not making money, and given typical online advertising rates, I don’t know if they’d be profitable even then.

I have been waiting for years for the “a la carte” option of television to become a possibility, where I can pay for just the content that I want to see and nothing else. I wanted this as a cable subscriber - I hated paying for the entire cable package when I really wanted just four channels. I want this as somebody who follows specific shows - I got into television as a result of becoming a Buffy fanboy, and still have an instinctive revulsion for the idea of flopping on the couch and “seeing what’s on”. The funny thing is that I would be willing to pay more to get what I specifically wanted - while the cable company charges $40/month for 40 or 50 channels, I would pay $10/month happily for the 4 channels I actually wanted. I know the economics don’t work that way (the channels I want cost more because they are higher profile) but I hate the idea of paying for something I’m not using.

I was excited by the advent of iTunes video, as it seemed like I could finally pay for only what I wanted. I’ve been following The Shield and Battlestar Galactica on iTunes because those are shows on cable channels I don’t get. I would have happily paid for The Wire if given the option. But with various content producers like NBC pulling their content from iTunes so that they can go their own way, it does not appear as if iTunes will be the “a la carte” solution I had hoped.

I wonder how much of my disappointment is because I’m decidedly atypical in my television consumption. I used to use a VCR and now use a DVR to ensure that I only watch shows that I want to watch. So I record shows, and play them back at times convenient to me, generally skipping the commercials. I’m a nightmare for the traditional television advertising model in the sense that I both time-shift and skip commercials. My viewing habits ensure that I am an advertising money-loser, so the “a la carte” solution would seem to be the only way to make money from me.

But I’m guessing most people aren’t like me when it comes to television (the Nielsen ratings back up that assertion). Most people come home from work, flip on the TV and watch whatever’s on. They surf through the channels available to them, rather than focus on specific shows. And when they do focus on specific shows, they don’t set their Tivo - they make sure they’re home to watch it. A digital analogy would be that I’m one of the minority that uses an RSS reader to follow blogs, where most people just go to a site when surfing to see if there’s new content.

Beyond the “a la carte” subscription model, there are a few other possibilities for how television gets made in the future. One possibility is a donation culture, where customers donate money to get the next book or record produced. I’m not sure that scales to the amount of money necessary to get a television episode produced, though.

Another intriguing possibility that may be what the networks are thinking is using content as a loss leader. ValleyWag had a recent article suggesting that “Recorded music is no longer a product, but advertising”, where artists should give their music away as advertising for things they can actually sell, like t-shirts and concert tickets. Perhaps television episodes could now be used to increase the power of the brand, with the actual money being made from DVD sales and other merchandising. Again, this seems unlikely with the much greater money necessary to make television than music.

Another possibility that occurred to me after posting is that networks may still consider the TV show aired in its normal time slot as the franchise. The video on demand on their sites and sites like hulu.com are merely designed as ways to bolster the original broadcast. This way, if I miss an episode, I can catch up and not feel like I missed a key plot point. Or I can watch a few episodes online and start watching a show that I might not have otherwise (this is how I started watching Friday Night Lights). The network assumes that I will then start watching the broadcast version so they can get their advertising revenue that way. But this assumption is headed towards breakdown as people become more comfortable with technology options like DVRs and video over the internet, which is inevitable as the net generation grows older.

I don’t really have answers. I’m not sure I’m even asking the right questions. But it’s an interesting topic, and I wanted to write about it while the hulu.com/iTunes discrepancy was still fresh in my brain.

I love being part of teams. When I’m on a good team, I work harder, I get more done, and I enjoy the activity more. My biggest career achievement thus far was achieved as part of a tight interdisciplinary team. And yet I’ve often been part of teams that never jell, and are ultimately more frustrating than inspiring. What are the qualities that make a team work, and what can prevent good teams from forming? That’s what Katzenbach (whose work I previously enjoyed in Real Change Leaders) and Smith investigate in The Wisdom of Teams.

The book is filled with inspiring stories of teams that came together under dire circumstances and achieved amazing things. Katzenbach and Smith use these stories as a way of organizing their observations about how to create high-performance teams, from details of how to get people to exchange an individual focus for a team focus, to the characteristics of good team leaders, to how to get a team unstuck from obstacles. But let’s start with determining what a team is.

The authors define a team as “a small number of people with complementary skills who are committed to a common purpose, performance goals, and approach for which they hold themselves mutually accountable.” These are the key components to creating what they call a “real” team, as opposed to a group of individuals who are working together. They studied teams in dozens of organizations and determined these were the common elements among the teams that were highly successful. So let’s take a closer look at these characteristics.

• Small number - Smaller groups have fewer logistical issues with meeting often enough for them to form a real team. In a small group, each person’s contributions and responsibilities are clear, whereas larger groups have a more difficult time organically determining those responsibilities.
• Complementary skills - The members of the team have to have all of the necessary skills for them to achieve their goal. This requirement is somewhat less important than the others, as the authors observe that real teams give their members the incentive to go learn the skills they need for the team to be successful.
• Common purpose - Everybody on the team has to believe in a common goal. Teams in the process formation often require a great deal of communication and negotiation to agree on their common goal, but until the overall purpose is clear, the team can not move forward.
• Performance goals - The team must translate the common purpose into specific and measurable short-term goals. These goals give the team a chance to bind together in the pursuit of the goals, and create situations where all team members must contribute in order to achieve the goals. The goals also provide chances to celebrate small wins along the way towards the larger purpose.
• Common approach - How does the team accomplish its goals? Who takes care of necessary logistics? The answers to these questions must be articulated for the team to continue moving towards its larger purpose, and not get mired in process and procedure.
• Mutual accountability - This is the big one in my opinion. Teams have to feel accountable for their results as a team, not as a group of individuals. The idea that the team can fail but that an individual team member has succeeded is incompatible with a real team. But when a team really believes in its purpose and performance goals, it will often hold itself to standards far beyond what the organization is expecting of it.

The CellKey team which I enjoyed so much had all of the characteristics of a “real team”. We were 12 people, each with different skills, who were trying to build this completely new instrument. MDS Sciex gave us short-term performance goals in the form of “phase-gates” where we had to prove the viability of our research in order to continue moving forward with product development, but we held ourselves mutually accountable to a higher standard than Sciex did. And we achieved more than I would ever have thought possible when we originally started experimenting with cells in a back room at Signature.

One surprising lesson from this book is that an emphasis on teams does not create teams. No amount of team-building exercises or team initiatives will create teams… unless there is a focus on strong performance. The first “uncommonsense finding” in the prologue states that “Companies with strong performance standards seem to spawn more “real teams” than companies that promote teams per se”. When the stakes are high and things absolutely have to get done, the normal way of doing things breaks down as being too slow to change and react, so teams emerge as the method to reach those performance goals.

This observation reminds me of a paper on innovation that Scott Berkun recommended, which said that the way to spur innovation was to set a goal that was impossible to achieve by normal methods. People don’t think of new ways of doing things unless they are forced to by circumstance - why take the risk of trying something new when the old way will work? Similarly, organizations will cling to hierarchy and bureaucracy unless they absolutely have to achieve more than they have been; teams emerge to save the day.

I have to admit that I’m not entirely convinced that teams can be manufactured by applying the principles described in this book. As the Peopleware authors observe, team building is more about removing the obstacles to the team forming. I think that the observations of Katzenbach and Smith fall into a similar category - these are necessary but not sufficient conditions for a team to emerge. I suspect that you could do everything mentioned in this book and still not have a team form because of a personality conflict or some other detail.

I recommend the book as a good way to reflect on how high-performance teams can be cultivated within an organization. It’s also fun to read about teams that conquer all the obstacles before them - the epilogue tells the story of the “Killer Bees”, a basketball team in Bridgehampton that competes for the state championship every year despite a male student body of less than 20. But they work hard, they play as a team, and with an entire town rooting for them, they somehow overcome the odds to succeed. Stories like that continue to inspire long after the book is done (which isn’t surprising, since it fits all of the Made to Stick rules of being simple, unexpected, concrete, credible, emotional and in the form of a story) and only add to the enjoyment of the book. Thumbs up.

One session I attended early in the weekend was led by Joe Fernandez, on how to measure influence in the social web. This started a great discussion, as we first had to agree what influence meant. The marketers in the room translated it into how much money can we make from this person’s recommendation? If Bob has 1,000 readers, but only 5 of them buy the product, and Alice has only 10 readers, but 7 of them buy the product, who is more influential? Bob’s got the bigger audience, but Alice has more influence, as measured by the dollars.

We also discussed social influence. What does it mean to be a thought leader? Somebody mentioned the Fast Company article on whether the idea of Influentials is valid. Somebody (not me!) brought up Clay Shirky’s new book. Rohit Khare mentioned his work on leveraging not just the social network, but also the documents as rated by that network (which makes sense when we realize that documents only have value when creating a connection). Lots of interesting ideas floating around, and Sanford Dickert suggested that we do another session to try to come up with a better definition.

On Sunday, Sanford led a session where we tried to derive an equation measuring influence. Sanford’s background is in robotics, so he was applying systems theory and feedback loops to the problem. We spent some time discussing what the equivalent concepts of inertia, friction, and dampening might be (we came up with the acceptance of the current worldview, the difficulty of forwarding a new idea/concept on, and the natural decay of interestingness of a new idea over time as possible analogues).

Sanford led a later session on “Web 3.0″ where he tried to build on these ideas of influence, and what that would mean for designing social applications. One marketer in that session suggested that marketing was making potential customers want what you have. I thought that was too simplistic and Machiavellian, but it got me thinking.

I realized that this might be a good situation in which to apply actor-network theory as a framework for thinking about this problem. Actor-network theory is all about evanescent indirect connections between people that need to be re-established. It’s also about how every element in the network has an effect on every other element - all participants are “actors” in that they have an effect on the network. Objects that have no effect are not actors and can be removed from consideration. But there are rarely direct connections between network endpoints - all effects must be traced through mediators which can alter the message in surprising ways. Actor-network theory is about observing the network and tracing the connections between different actors and seeing the effects of mediators.

So I started mulling the idea of trying to trace the network between the product on one end and a customer on the other end (my notes from the session say, in contrast to the earlier claim, that “Marketing is building a connection between the product and the person”). The product has certain characteristics, the marketer advertises some of those characteristics, the newspaper reviewer might write about the product and its characteristics, a friend might read the reviewer and think highly of the product, and mention it to the eventual customer who happens to have a need for a product like that.

I wanted to write up these ideas this evening, so I went back to review my posts about actor-network theory from years past, and discovered that I had already written a post on applying actor-network theory to marketing. Clever of me, eh? Go read that post now.

One thing I don’t address in that post is how to create a mathematical model of influence. I was talking about it with Sanford later, and suggested that it’s a tricky problem because influence is such a personal thing. I may be influenced more by a famous person like Oprah or by my good friend. Also, a person’s influence is not invariant - I may trust my geek friend for a recommendation on which laptop to buy but not at all on where to eat. So the model would need coefficients of influence for each connection between nodes on each topic, with those coefficients varying depending on results.

I wonder if a neural network might be the way to model this sort of thing. Our brain can be modelled as a collection of neurons, each of which influence each other with certain coefficients that are strengthened or weakened based on how well their outputs contributed to desired outcomes. Perhaps our networks can be modelled in the same way. This would play into my idea of cognitive trust, where I suggest that once we trust other people enough, they’re just an extension of our own brain. I certainly have people like that, where I don’t even bother having opinions on certain topics like cuisine and fashion because I can always call my friends to get a more informed opinion. In some sense, my outsourcing of taste is the ultimate in influence.

I really need to find the time and energy to do some programming. It wouldn’t be that hard to create a toy model of an influence network built off a neural network model. And it would be interesting to see how that model corresponded with real world tastes. Maybe I should throw it at the Netflix data to see what happens. But that might have to wait for the summer when classes are over.

Technorati tag: barcampnyc3

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 amuse, which was a tiny cup of squash soup, with a foie gras oreo on the side. I forgot to take a picture of it, but it was excellent. And cute.
  

• The cauliflower flan. The sweetness of the flan combined with the strong cauliflower flavor was a really interesting combination.
• The golden beet ravioli with pecorino and microgreens. Yum.
• Cod with rosemary grits in a blood orange reduction. I love blood oranges and rosemary, so I particularly liked this one.
  

• Venison with spaetzle with black currants. Our table agreed that this was the most tender venison that we had ever tasted.
• A nutella tart with a hazelnut milkshake. This was incredibly tasty, especially sipping the milkshake while eating the tart.

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