startups as the path to enlightenment

~ ginsu ~ 3 Comments

So if you didn’t work at PayPal during their halcyon days, what else makes for an attractive startup résumé?

I would say that ideally startup hiring managers should try to get folks who’ve been through at least two of the four private company stages, including at least one that the hiring company has not yet been through.

Well, I would say that, except I find that these “stages” are not particularly well defined by anyone.  Or at least not anyone I could find in 28 seconds of Googling.  So like any moron with a digital pen and printing press, I can just make up my own definitions.

Some of the typical “stage” terms are seed, early, expansion, and late – these are often used by investors, are vaguely defined, and don’t always track to a company’s internal status and expectations.  I’ll try to align the four stages of private company progress with some more-fun-if-equally-irrelevant quadrilateral perspectives, from psychology and Buddhism.

Stage I:  pre-product

psych: unconscious incompetence – the individual neither understands or knows how to do something, nor recognizes the deficit or has a desire to address it

Buddhist: the path to stream-entry; the fruition of stream-entry

This stage is everything before you have a product launched to anyone outside your “friendlies” (relatives, friends, close contacts) – from the idea on the napkin to your Hello World! launch to the general public.

What others call ‘seed stage’ is often short of this – just the idea through a prototype, with ‘early stage’ then following from pre-launch to revenue traction.  But although that division may be natural for funding demarcation, from a product perspective you just don’t know what you have until it’s in the hands of the buying public, so I regard all of this period of not knowing as a single period of sustained ignorance.  It is all the pre-product path before the fruition of entering the great stream of commerce.

Stage II:  maximum iteration

psych: conscious incompetence – though the individual does not understand or know how to do something, he or she does recognize the deficit, without yet addressing it

Buddhist: the path to once-returning ; the fruition of once-returning

This is the period where the company has both the maximum flexibility and the most urgent need to rapidly iterate development.  Not just product development – everything about what the company makes, does and is.  The flexibility is there because the product has been launched, which not only lifts the inchoate burden of launch, but begins the collection of data (customer feedback, product metrics, use data etc) which can now be mined for insights about how to shape and reshape the product.  The need is there because if you don’t iterate, you will not grow and then you will not exist.

And again, it’s not just product iteration but an opportunity to examine and tune everything you do as a company:  recruiting and review systems, management team and tools, compensation, cultural principles, office design, everything.  The things you do to shape the company during this period will have an enduring effect on everyone who works there for years to come.  Too bad you don’t really know what you’re doing just yet.  But now is the time to get on the path to once-returning, to reincarnation and rebirth into the next stage.

Stage III:  revenue optimization

psych: conscious competence – the individual understands or knows how to do something; however, demonstrating the skill or knowledge requires a great deal of consciousness or concentration

Buddhist: the path to non-returning ; the fruition of non-returning

Unless you were oh-so-clever enough to launch without a revenue model, the company began to enjoy early revenues during the maximum iteration stage.  Iteration remains critical, but now your flexibility is naturally limited by the existence of paying customers, who often have a limited tolerance for change.  You have to optimize existing lines of revenue while making careful tradeoffs in launching new lines of revenue.  You may for the first time begin pursuing meaningful acquisitions or divestments that could change the face of the company.

This stage may be the most difficult among the four; your hard-earned knowledge seems to have the perverse effect of increasing the challenge.  When you were young and ignorant, it served you well to underestimate the difficulty in changing the world.  Now that some corner of the world has bent to your dream, you find that the dream is a shared hallucination of many rather than your own private trip – and your role isn’t to enjoy the ride but to supply the vehicle.

Nonetheless you are on a path of no return:  in returning there is only defeat and regression to a lower form of living; you can only move forward for true enlightenment.

Stage IV:  maturity and liquidity

psych: unconscious competence – the individual has had so much practice with a skill that it becomes “second nature” and can be performed easily (often without concentrating too deeply)

Buddhist: the path to enlightenment; the fruition of enlightenment.

The mature company does not have to be moribund, there is a vitality and pleasing grace to the well-oiled machine.  You know what you’re doing and you’re at the height of your powers, freed from the mixed blessings of youth.

And no matter your personal attitude towards money, getting the company to liquidity is the last barrier to enlightenment.  (Here I’m putting aside the case of those who want to build a big, sustainable private company without calling it a “lifestyle business” – the more typical startup dream involves shareholders and employees who want to be able to freely trade their stakes in the business on the open market.)

With your first big liquidity event, you find out if the other side of that barrier really is nirvana.  You find out whether the money has changed you, or whether it exposed who you really are.

That is the startup path as self-actualization, the startup path to enlightenment.  When you’re hiring for a startup, you need to pay careful attention to which of these stages your candidates have progressed through, and uncover their self-knowledge about their enjoyment in what has been learned and their eagerness to learn what hasn’t.

btw, if you are on that path or would like to be, and have skills in javascript, php and/or other web programming-fu: send me your résumé! (just a link to your LinkedIn or other relevant online bio would also be fine.)  use the intarwebs to find how to contact me.

résumé gold

~ ginsu ~ 2 Comments

If you are a hiring manager for a tech startup, what is the one company you’d most like to see on the résumé of a prospective candidate?

A lot of people might reflexively answer ‘Google’ on the belief that it’s still the most interesting and profitable company in technology.  While this isn’t as bad as saying ‘IBM’ or ‘Microsoft’ it’s still an undue faith in the benedictory power of large companies.

Not that there’s anything wrong with folks from IBM or Microsoft, mind you – I’ve worked with many and hired some, and don’t regret any incidences from either.  However, as a statistical matter, you’re not likely to find the kind of employee that really thrives in a small startup if they’ve spent a ton of time working in longstanding behemoths.

Doesn’t mean that big companies can’t innovate – in fact these days some say that only big companies can innovate big.  Of course, it may be that the people saying that tend to reap consulting dollars from big companies for advising on innovation . . .

Anyway, Google is a slightly different case than IBM and MSFT, in that it hasn’t been around as long and is not quite so large in terms of revenue and employee base.  However, because of the neck-crimping trajectory of Google as a company, I think it might be hard to get startup-ready employees out of Google:  the good ones that are still there are engaged on the big premium projects, many of the not-so-good more recent vintage are as big-company-minded as anyone, and the truly great early employees who departed are retired or VCs – too rich to be enticed into a little startup unless they start it themselves, which they rarely do as it distracts from counting the money.  Even if you follow startup news, you don’t hear so much about Google guys leading startups, with the notable exception of Paul Buchheit at FriendFeed.

So, if not Google, what company should be the most desirable to see on a résumé, all other things being equal?  I think I’d pick the one company that spawned founders and early investors and employees at YouTube, LinkedIn, Facebook, Yelp, Slide, Zinga and Yammer:  PayPal.

See, the ideal company – at least in terms of educating talent for the next venture – doesn’t have a Googlerian or Microsoftesque trajectory.  From founding to acquisition by eBay for $1.5 billion, PayPal lasted about four years and grew to a profitable company with over 600 employees, having been through a lot of growth, innovation, regulatory challenges and corporate evolution.  People in key positions through the bulk of that time saw the whole arc of company development, but never got so fat and happy that they didn’t want to do another startup.  Yep, if you’re hiring for a startup, the name you’d most like to see on that résumé is PayPal, pre-acquisition by eBay, natch.

simply amazing

~ ginsu ~ 2 Comments

p. 57:

‘It was – simply amazing,’ she repeated abstractedly.

What’s amazing to me is that every time I’ve read that sentence before today, I read ‘abstractedly‘ as ‘distractedly‘ – thinking that Jordan was distracted by the hour-long conversation she’s just had with Gatsby.

And what’s really amazing is that Fitzgerald never has an imprecise paragraph or sentence or phrase or even a single slightly improper word choice. He used ‘abstractedly’ because that’s precisely what he meant.  Jordan wasn’t distracted by some diversion or emotion; she was abstracted, lost in thought. I’ve read the word wrong every time and never noticed until I took the time to find the artistry on every line.

A mild note of interest on this page is Jordan’s reference to her aunt, Sigourney. The actress Sigourney Weaver, star of the Alien movies, was born Susan and changed her name after this character, who is only mentioned this once in passing.

love the machine

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The Wall Street Journal reported that Google is working on an algorithm to predict which of its employees is likely to leave. Putting aside for the moment whether there is some creepy aspect to the machine anticipating personal career choices, there are two aspects to this that I find interesting.

First, exactly how and why did this make it into the news? I’m not questioning whether it’s newsworthy (it is), I’m wondering about the exact path that this took from fact to front page. Was this program broadly announced at Google, and a random employee alerted the media? That would be one typical path. Was it an unannounced program, and someone in the HR department leaked it to the press? Or perhaps the HR folks proactively fed this to the press. If one of the latter two, what’s the motivation? Does it make Google look smart as a company? Does it comfort employees to know that Big Brother is watching and cares whether or not you leave? I don’t think any answer to any of these questions is necessarily a bad thing, I’m just wondering what the answers are.

Second – and more answerish this time than questioney – it’s really interesting to consider the reported inputs to the algorithm. According to the WSJ, “data from employee reviews and promotion and pay histories” comprise the formula. At first glance, this might seem logical: you would hope that reviews and compensation have some correlation to job performance and satisfaction.

Ah but then – you’ve been hoping that all your life, haven’t you? And haven’t you found that the content of employee reviews is often radically disconnected from actual performance, that the “wrong” person often gets promoted, that compensation has at best a tenuous connection to performance and satisfaction?

So the data set might not be as logical as it first seems; fortunately the magic of the sample size means that this isn’t a logic problem, but simply a correlation exercise. There is certainly some correlation between the content of that data and the incidences of employee departure, or Google wouldn’t be trying this.

But I’d bet that the correlation is much weaker than you’d think, and much weaker than Google would like. Any manager knows that reviews and compensation are blunt tools, and these are likely to be trailing indicators rather than the leading indicators of dissatisfaction that you want for real predictive power.

I worked at a company that somewhat famously had a “Love Machine” – a simple tool for employees to express appreciation for each other. Basically, as an employee, if a colleague did something that you appreciated, you could send them a point of Love, along with a one-line comment as reason for the gift. It was just a neat little way to say Thank You, and people really appreciated both giving and getting Love. And as very minor benefit, periodically the accrued Love points would be paid out to employees as a cash bonus.  (Distribute that on a Friday and watch people really spread the love around.)

When this was reported externally, some people misunderstood the corporate purpose of the Love Machine. Which is to say, some people thought it had no purpose at all, except as some gross hippy dippy vibe. Those people not only misunderstood the effect on morale, but also vastly underappreciated the value of the data from the Love Machine.

Think about it: as a manager, is it valuable to know which of your employees is appreciated, and which is not? The Love Machine is certainly not the sole source of information on this, but the data gives at least some general information on both specific and aggregate cases. You can see not only who is appreciated, but who gives appreciation. You can see which departments are praised and which toil without recognition. You can see who works across departmental boundaries and who only interacts upwards or downwards in their own reporting silos.

All this is phenomenally powerful data that gives factual indication of matters that you might otherwise pay significant amounts to guess about through expensive organizational consultants. I was convinced back then and I still am today that if HR departments and managers understood the power of this data, every company would have a Love Machine. Most would call it something else, but that part is just internal marketing.

Back to Google: as far as I know, they don’t have a Love Machine. But that doesn’t mean that they are feeding the best data they have into their Who’s Leaving? algorithm. Nearly every company has somewhat similar data in their email traffic, and certainly in a big data set, email traffic would work quite well. Now, I’m not saying that the email content should be analyzed – even though many companies actually do that, I find it unacceptably creepy. I just mean the fact of communication. Every manager knows that communication is a powerful indicator (and motivator) of job satisfaction.

Who’s talking to who? Who’s on how many email lists? What is the response rate and timing and length? Is communication cross-functional, up and down and across reporting levels, inside and outside the company?  All of that information is available in company email – I guess you could call it the email graph.

I would bet almost anything that this kind of data from email traffic provides a more powerful indicator of who’s leaving the company than the data from reviews and compensation. In fact, I’d bet that the email graph has better correlation to actual job performance than performance reviews!

Of course, the combination of those data sets could be even more powerful, and it’s entirely possible that Google is already doing this, though that wasn’t reported in the Journal piece.

black storm networks

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So what’re you up to these days?

I’m spending a good amount of time in residence with my old friends at Storm Ventures, which reminds me of the last time I sat around with them, back in 2002. Coincidentally that was also around the last time the sky was falling, though the dot-com implosion was more localized than today’s lovely global financial crisis.

Although more contained, I think in many ways that downturn felt more severe in my world, the tech industry centered around Silicon Valley. It seemed that there were more local job losses, but more than that, the feeling of panic ran a little deeper, and wasn’t backstopped by the recent practical experience that we have today because of the prior crash. When the dot-com bubble burst in 2000, the prior domestic market crash was in 1987, and 13 years is enough time for people to forget, long enough for the prime of a career to pass through the ephemeral industries of the tech world. In 2008, the last crash was only 8 years ago, so now most people working here remember what happened the last time, and they can separate the chickens from the oracles.

A lot of people say that an economic downturn is a great time to start a new business. Of course, there’s a difference between saying it because others say it, and saying it because you’ve seen it before. In 2002, one of the partners are Storm was saying it to me, and it all made logical sense: costs were lower, recruiting was easier, competition was scarce. But I hadn’t seen it before. Tae Hea Nahm and Tim Danford at Storm were sure it was the right time to incubate a company, so they formed Black Storm Networks and recruited the founding team of Ajay Mishra, Pat Calhoun, Bob Friday and Bob O’Hara. The founders huddled in Storm’s offices through the dark days of telecom nuclear winter and built the company piece by piece.  I was lucky just to hang around and watch the sweat and optimism they put into every single day.

Jump ahead to 2005 and Black Storm had become Airespace, the leading startup for a new class of enterprise wireless networking equipment.  That year, Airespace was acquired by Cisco in a great deal for both sides. I was lucky again, for by that time my peripatetic career had allowed me first to invest in the company for another firm, and then to join the team in time to help the last push.  For most people, the story of any startup ends with the liquidity event. But I enjoy watching the afterstory too; I like to follow whether the acquired product continues to succeed, whether the team has an impact in the new company and afterwards. On that measure as well as others, I’m really proud of the Airespace team.

The product and its successors achieved a dominant market position. Airespace’s CEO, Brett Galloway, has become a senior exec at Cisco responsible for all wireless and security products. Pat Calhoun is now the CTO of one of Cisco’s biggest business units. Bob Friday continues his wireless wizardry as a director of engineering for Cisco. After several successful years for Cisco, Ajay joined Airespace’s biz dev paladin, Bob Tinker, for another startup run. Bob O’Hara pulled perhaps the best move, retiring from Cisco last year to live in Twitterville.

Anyway, my fondness for that team and those days brings me back to these days, back at Storm with time to dream. I believe it because I’ve seen it:  an economic downturn is a great time to start a new business.

Update:  Bob O’Hara adds his perspective.

that’s entertainment

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Is social media entertainment?

Of course it is, whatta silly question, you say. When people spend their leisure time engaged in updating their profiles, messaging each other with pokes and posts and status updates, posting and viewing photos and videos – well, that’s entertaining. The answer to the question from the user’s perspective is undeniable. But of course the fun in any analogy is to see how far you can extend it, so I’m really wondering if social media is entertainment from a business model perspective.

Think of a big-budget movie. A group of people get together around a concept, script or performers. They raise financing in excess of $100 million from traditional studio and independent interests, often pre-selling shares in future revenue stream. Many dozens, sometimes hundreds of people are employed in executing the vision into the reality of the work on screen. Distribution occurs not just in theaters, but downstream on DVD, TV, and of course the Web. A successful blockbuster returns hundreds of millions of dollars in a burst, and a continuing annuity essentially forever.

Is this so different from what we’ve seen in social media? From Tribe to Friendster to MySpace to Facebook, it’s been a hits-driven business. People assemble around a concept and produce, and it seems that there is a limited window for the concept to catch fire with the broader public. If and when it does catch fire, there is a period to maximize revenue during the peak of popularity, and then a long slow decline. Maybe the curve is a little more like a successful TV series than a blockbuster movie, but the dynamics are the same: the production of a media experience that has temporal value for audience entertainment.

This is certainly an analogy that most social media companies would resist. They prefer to think of themselves as technology companies, building a platform for media delivery, or even becoming a fundamental part of the infrastructure of communication.

It’s not easy to define a platform on the Internet. You would think the concept of infrastructure is simpler. It’s relatively easy to envision the most concrete elements of the communications infrastructure: the physical wires (be they fibers, cables or tubes), the hardware of routers and switches and terminal devices, the often unglamorous stuff that moves the bits and bytes around. Database and storage are surely infrastructure components as well.

But can a software service company become part of the infrastructure? This isn’t a question of offering infrastructure services in a cloud of computing – it’s a question of whether a service that is not about transport and storage of information can be considered essential to modern communication.

In areas where that can be considered a serious question, we have an enormous market. Search is the prime example. Without search, the way we communicate and create on the Internet would be severely hampered, in the same way it would be hampered if we didn’t have significant storage or large databases. And search is a good example of a putative infrastructure element that must be provided as a service – which means a business can be built around it. Coming up with a protocol like TCP/IP may give birth to the Internet, but it doesn’t necessarily give rise to any dominant business for its creator.

So are the companies involved in today’s creation of social media making infrastructure? Can essential services be built in social media that become a fundamental component of communication? Even if so, is the social graph going to be as enriching as TCP/IP (that is, in more of a spiritual than monetary sense)?

Or is it all “just” entertainment?

an angry diamond

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p. 56:

One of the men was talking with curious intensity to a young actress, and his wife after attempting to laugh at the situation in a dignified and indifferent way broke down entirely and resorted to flank attacks – at intervals she appeared suddenly at his side like an angry diamond and hissed ‘You promised!’ into his ear.

Gatsby revolves around young couples in relatively early, fragile relationships.  Here is a rare, flashing view at an older couple, in an old relationship with fragility that age has not dissipated, but crystallized into a frozen spiderweb.  Fitzgerald is known as a chronicler of the young and carefree, but this is a pitch-perfect snapshot of a couples’ argument that has developed through many years of betrayal.

In truth Fitzgerald’s heroines were never carefree, regardless of their age.  Though often misunderstood as shallow, these young female characters were engaged in poignant struggle to define a new womanhood in a time before feminism.  Those who lost – or worse, missed – the struggle could do nothing but harden their pains into an angry diamond.

the webz for realz

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The “real time web” is a phrase that’s coming dangerously close to buzzword heaven, to the point where formerly-Web-2.0-guys will start saying it’s a key feature of Web 3.0.  I’m not sure that the people who are so fond of the phrase are entirely clear on what it really means.

Some folks seem to say that “real time web” basically means everything more and faster.  It’s been a common tenet for at least a decade that the value in the Web is found in aggregating and analyzing information, and delivering the result to the right audiences.  Today we simply have more information, from more sources, and more techniques to analyze and filter the info flow.  Creation, collection, analysis, filtering and distribution of information happens so fast now that we can call it “real time” – but that’s just a fancy phrase for “really rilly fast.”  In this view, “real time web” is an inapt phrase if it’s meant to describe a new benefit – what we really have is just a new expression of an old (in Web terms) problem.

Another view is that the Real Time Web is not just a faster Web, but a new medium.  I don’t think I can articulate this view in brief, but the general idea is that fundamentally different sensory experiences are implicated by this new kind of personalized information that is delivered and filtered nearly concurrently with its creation.  This view is sexy sexy sexy:  it’s always so sexy to declare a new medium.  It’s so sexy that somehow the tone of new media declaration infuses the works of even the commentators whose words clearly describe nothing more than a faster Web.  When you read just about any writing that uses “real time web,” it seems that the author is striving to discuss new tools for new problems, rather than new tools for old problems, and would be aghast if it turned out that it’s actually just a discussion of old tools for old problems.

So is the real-time Web really just a faster Web, or is it a new medium, as different from the Web as the Web is from TV and radio?

That’s a deliberate question, since I think the fascination with ”’real-time”’ often represents a yearning for old media forms – especially broadcast media like TV and radio.  Ironically, people who have seen a lot of media evolution tend to race to declare every older medium dead, while they simultaneously pine for the familiar patterns of old media.

The idea of broadcasting – getting the same information out to many users at the same time – might be a familiar pattern that people are seeing when they think of the Real Time Web as a new medium.  Early Internet businesses like Pointcast and Broadcast.com were simply about using the Web to get the same information to as many people as possible at (roughly) the same time.  But at this point, thinking of the Web as a broadcast medium requires perverse ignorance of the distinct characteristics that make the Web interesting as a new media format.

What is distinct about the Web versus other media is the extent to which information can be aggregated and analyzed, the low cost and ease of creation of content, the application of both computer algorithms and social means to filter and personalize delivery.  When people began to understand that, they stopped trying to broadcast and instead built businesses like Ebay and Amazon and Google – and it so happens that those businesses were built on aggregating and analyzing asynchronous information.

I guess I’m asking:  Is the asynchronicity of information creation, collection and analysis also an important distinct characteristic; and if so, does that mean that doing those things in real time makes the Web a different medium?

Another way to gauge the relative importance of the real-time concept:  Which would you rather have at your disposal, everything on the Web that is older than one hour, or everything that is more recent?  (Picking It Depends is not a choice.)

loving and leaving linden lab

~ ginsu ~ 8 Comments

The test of a first-rate intelligence is the ability to hold two opposed ideas in the mind at the same time, and still retain the ability to function.

F. Scott Fitzgerald, “The Crack-Up” (1936)

I love Linden Lab.  Over the past four years, I’ve poured everything I had into the company.  Leaving was a tough decision.  But at the same time, it was easy to see that it was time for me to go.

Departure missives are a tricky thing.  This is actually my third for this same departure:  I said goodbye to the company internally, I posted to the company blog, and now here’s one for my own blog.  Why so many?

I’ve studied the art of the departure memo, it’s really quite interesting.  The business world sees many comings and goings, and in certain companies, internal communications are destined to get leaked – and you can see that the authors know this.  Compare two examples from the same company, Yahoo:

  • Stewart Butterfield’s resignation was bizarre, funny, and ultimately a scathing indictment of a place that overdiversified and lost the love of innovation.
  • Sue Decker was more restrained, with a classic and classy goodbye that nevertheless could be read as a defensive listing of all the progress made under her watch.

In their own way, each goodbye note took pains to remind people of the author’s special qualities and accomplishments.  I avoided doing that in my earlier announcements.  It’s not that I’m especially modest –  I just didn’t want to muck up messages to colleagues, customers and company commentators with shameless self-promotion.  There’s a time and place for self-promotion.  Like right here, on my own damn blog.

Ah, but I’ve never been great at claiming credit.  I’m struck by the wisdom that one mentor told me earlier in my career, which I’ll paraphrase as:

Success has many fathers, and even more virgins trying to claim paternity.  No one who wasn’t there can really understand the full story, and even the ones who were there didn’t see everything.  But you’ll know what you did, and so will the people that matter.  Let the others play their guessing games.

So then here’s a game to play.  When success really does have many fathers, how do people claim any successes for their own?  I thought about what successes I’d want to highlight from my time at Linden, and I realized that any of them could have at least two opposing interpretations.

my would-be claim one idea opposing idea
key exec in managing company growth from early revenue to profitable phenomenon can spot and guide a winner just along for the ride
lead exec in many areas through company history: international markets, legal, finance, HR, developer relations, enterprise segment, business and corporate development multifunctional business executive short attention span to the point of personality disorder
led finance through early revenue, raising $15+ million equity and debt financing, accurately projecting 2+ years of revenue growth within 10% talented early-stage financier and prognosticator wild-ass guesser
early leader of international growth from 30% to 70+% of audience makes worldwide progress with limited resources strained the organization beyond its ability to grow
established basic legal and regulatory policy and strategies, with humor insightful thinker on social and governmental issues paper-pushing policy dork, with wicked streak
architected Linden Dollar as unique virtual currency and multimillion real dollar business fearless and creative new product innovator reckless and dispiriting goon
wrote, tweaked, and rewrote the Tao of Linden sensitive guardian of company culture feckless appeaser of management fads
executive sponsor of startup-within-a-startup initiative for enterprise segment constant pioneer in new markets and strategy focus-diluting disruptor
negotiated and managed acquisition and integration of several businesses accomplished M&A dealmaker heartless crusher of helpless entrepreneurs
helped recruit and integrate new management team before departure selfless assembler of talent ruthless operative in reorg-and-run

Can I claim any of these successes as wholly my own? Where does the truth lie? Would the modesty of my saying that all opposed ideas could be true be undercut by the implication that I would then be claiming a first-rate intelligence?

Ah well, that’s about the best I can do for self-promotion.

social networks and the dunbar break

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A couple of months ago, The Economist noted that the Dunbar number appears to apply to online social networks like Facebook.  I’ve since been thinking about the threat this represents to Facebook’s business, and all social networking businesses.

To recap:  The Dunbar number is a theoretical limit to the number of social relationships that one person can maintain – this number is often estimated at 150.  Facebook’s “in-house sociologist” confirmed that the average Facebook user has 120 “Friends” (i.e. other Facebook accounts linked to the user’s account).  Moreover, when measuring the interaction between users, such as comments on each others’ accounts, men average regular interaction with only four people, while women average six people.

You see the problem?  It’s too easy to leave social networks:  you’ll leave as soon as your six closest friends do.  From Tribe to Friendster to MySpace, no one has been able to hold on to their users.  Given that history, Facebook and Twitter have to fight more than just faddishness – they have to fight the cognitive limits of the human brain.

Ironically, social networks do not have the full benefits of network effects.  A really robust network effect means that each additional user of a network adds value to the network for all users.  In social networks, once all of my friends have been added, I don’t really care if any more people join the network.  And that means that the converse is true:  once all of my friends leave, the network has no value to me, no matter how many other users are still on the network.

The ”’Dunbar break”’ occurs at the point at which so many of your contacts have left a social network that you no longer value the network.  Dunbar’s number suggests that this point might be as high as 150, but looking at the actual interaction on Facebook, your personal Dunbar breaking point for Facebook could happen when as few as half a dozen of your friends leave.

That’s why Facebook and other social networks must paddle furiously to try to add value that scales across all users with a true network effect.  But with advertising and applications and ”’lifestreaming”’, they haven’t quite found the magic formula yet.

Does current media darling Twitter hold the key to defeating the Dunbar break?  As a combination of social media and broadcasting, it has some intriguing possibilities.  Ask yourself:  Once all of my friends are on Twitter, do I care if anyone else joins?  And would I care if all my friends leave Twitter, while the rest of the world joins?  A lot of people are answering those questions differently for Facebook and Twitter, which is why Twitter is such a popular dance partner these days.