Urgent Speed

Mathematicians will inherit the Earth

Technology, combined with social networks have the power to stop oppression and improve people’s lives. 

We are already seeing the impact of Facebook, Twitter, Google+ and Linkedin in the Middle East, and the media industry, but we believe this change is just the beginning.  Other industries like Finance, Education and Healthcare may be nearing their Napster moment. 

At my Start-up, Lenddo.com we are using the social graph to improve people’s lives and restructure finance.  Members are using their online reputation to prove identity and access credit in regions where there is little access to credit.   Every day members are able to get education for loved ones, medicine for family members, and shelter for relatives.  Tangible life improvements.  We expect to impact millions.

The other day I was asked about the predictive capabilities of algorithms, so I thought some background information might be helpful. 
 
We like to think of ”trustworthiness” algorithms as falling into three broad categories.

Bayesian – This is classic machine learning (pattern matching) to build a probabilistic model, within a acceptable false positive, false negative range. The core to growing these predictors is massive volumes of data.  Data could include any information collected or observed.  This can include; stated interests, sites visited, biometrics, writing style, age, words uses, images, network composition, machine configuration, geographic data, internet usage, job, demographics, education, hobbies, and financial history.  The Adtech industry has built a substantial “behavioral profiling” infrastructure to predict what ads are most appropriate (sell you sugar water), why not leverage and extend this technology to actually empower individuals with access to credit?
 
Validators – (Heuristic, Taxonomical, or Bayesian) – these algorithms are used to validate or perform a reasonableness test for information volunteered by an applicant or her friend.  For example: someone from a big company will generally have friends at that company, or someone from Manila will generally have log-ins from Manila, or someone in medicine will use certain words in their general correspondence.    Validators are very important in the Emerging Markets, where standard RAC (Risk Assessment Criteria) rules are necessary but insufficient due to a general shortage of customer data. 
 
Homophily – (“birds of a feather flock together”) builds on the well documented tendency for individuals who interact regularly, or share some social bonding to behave similarly.  In science, many of the best Homophily data scientist come out of computational psychology or epidemiology.  In business, Online Ad networks (Demand Side Platforms) are a good place to hire as Homophily based algorithms are often the basis of their mathematical underpinnings.

More on Homophily

A good example of Homophily in nature is with smoking, game fraud, sexual promiscuity and obesity.   For example there is some great studies and talks by Harvard health researcher Dr. Nicholas Christakis.

His team found in a social network of 12,000 over 32 years, that friends had the greatest impact on becoming obese and that the type of friendship made a difference. For example, a close, mutual friendship resulted in a 171-percent increased risk of obesity while a one-way friendship increased the chances by 57 percent. These findings contrast with a 40-percent increased risk among siblings and 37 percent between spouses. Friendships are so influential, in fact, that the likelihood of obesity even increased when the friend of a friend was the one to gain weight. Same gender relationships also have a stronger influence than those between genders.
 
Perhaps most surprising was the finding that geographical closeness made no difference.   This last fact is interesting to us, because we believe geographic clossness will become even less important as people increasingly use the internet to maintain relationships.   We are able to use the social graph to measure “closeness” and “friendship strength” as well as of course “geospatial closeness”.
 
I Hope this is helpful.  Predictive Algorithms and important part of what makes Lenddo so simple for our members. 

If you have an interest in using math to makes people’s lives simpler and better, please lets us know.  At Lenddo.com we are trying to make a dent in the universe and always looking for exceptional Data Scientists.

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Image source Forbes

Startups Should Make a Dent in the Universe

Steve Jobs had it right: Startups should make a dent in the universe.    Big ideas attract the top teams. Big ideas keep the teams going through the inevitable hard times.  Big ideas with top teams change the world.   For decades, the life blood of Silicon Valley was great teams working on big ideas.

But recently, as Jon Evans at TechCrunch points out, the Valley is increasingly fascinated with “the big distraction of entertainment.”  I could not agree more.

Silicon Valley has lost its way.  Stop screwing around in the small pond of media and advertising and tackle big industries and real problems.   Heck, why not invent a new industry? Did you know in New York City there are at least a dozen companies that have sprung up around the “personal replicators industry” aka 3D printing ( MakerBot , Quirky, Shapeways etc.).

Did you know that all Media, (including NBC, CBS, Google, AOL, ESPN, every radio station, every magazine and every advertising agency) only represents about 2.5% of GDP?  The Valley has become obsessed with “selling sugar water.”   

The world needs Silicon Valley back.

Energy, Finance, Healthcare, Education… that is where the BIG problems are.  (BTW: Facebook already has $470M in financial service revenue from Facebook Credits).

How do you expect to attract great talent if you are not substantially improving the world?  Is it pay?  Has Silicon Valley become filled with “technology whores” like the East Coast hedge funds they like to make fun of?   As an entrepreneur, changing the world is what keeps me going.   Building a company is hard work. How can you work 80+hr weeks if the outcome is: it’s easier to buy crap you don’t need online (aka sugar water).    

Finance:

Credit, Savings, Insurance and Payments are Huge.  Sean Park has a great post on "digitally native finance.”  At my startup, Lenddo.com,  we are using the social graph to improve people’s lives and restructure finance.  Members are using their online reputation to prove identity and access credit in regions where there is little access to credit.   Every day members are able to get education for loved ones, medicine for family members, and shelter for relatives.  Tangible life improvements.  Our team sees how we will impact millions.  This is why you have a start-up!  This is the power of technology! 

Education:

At Aristotle Circle, where I am an Angel, they are using technology to build a network of peers and experts to radically improve educational outcomes.  Other companies are using algorithms for adaptive/dynamic course material to tailor online material to the specific pace, medium and style of each individual learner.  Today about 5.5% of GDP goes to public education which does not include private universities and corporate training.  What happens when education cost half as much, or is twice as good?  Technology combined with entrepreneurship will show us.

Health Care:

We waste more in healthcare then we spend in media..come on.  We spend around 16% of GDP on healthcare in the US, and baby boomers are not getting younger.  Did you know computational linguistics combined with analysis of social media is being used to guide drug discovery?   If you are great at math or engineering, why would you be optimizing online photos, when you could be extending human lifespan?  Why not ask a health care entrepreneur?

Energy:

Don’t worry about Energy; why would we want to have more of that?  

Don’t get me wrong.  I love Silicon Valley. The Valley had a great run with semiconductors, PCs and the Internet.  They did a fine job “taking on” media.  The Media Industry is Powerful, but they are pussycats (or leave off the cats) when compared to Wall Street, The Teachers Union, Health Insurance Companies, Big Pharma, and Energy.   

My friend in Silicon Valley once gave me sound advice: “Jeff, as a tech-entrepreneur you need to be back here in Silicon Valley at least every 30 days”  He was absolutely correct.  There is nothing like the innovative energy and echo chamber of northern California.  I go often, and every trip is time well spent. 

Now my advice for Silicon Valley: Get out of the echo chamber at least once a month.  See what is going on in Finance, Education, Health Care, Energy and “personal replicators.” 

It’s time to think big again.

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Photo: from Bob Cringely's awesome 165 minute history of the PC industry "Triumph of the Nerds"

A taxonomy of motivation (Part 2)

In Part 1 “Is Zynga be the first billion dollar psychology company? or a taxonomy of motivation” I hypothesized the science of understanding motivation is about to advance, and that site designers can use the emerging framework to better segment and engage site visitors. 

Like Billy Bean used math to advance baseball, scientist are about to use big social datasets to advance the disciplines of computational physiology, game theory and behavioral economics.  These are important disciplines when trying to make a service viral, engaging, or impactful.  Let’s hope entrepreneurs use this new science to do more than just sell more toothpaste (improving education and healthcare would be noble).

Below is a framework I use for segmenting motivation.  My interest is not academic, but rather in the application of the social sciences and mathematics to business.  That being said, I believe real progress will only be achieved by engaging academia. 

My hope is that by posting this framework, someone from academia will reach out and advance our thinking, point out the short coming...…or even better, come work with us.   

My DRAFT framework is as follows:

A.      Intrinsic process motivation (fun). - If people are motivated to perform certain kinds of work, or to engage in certain types of behavior for the sheer fun of it, then intrinsic process motivation is the driving motive. The work itself, not the task outcomes, acts as the incentive, as followers enjoy what they are doing. Intrinsic motivation is characterized by task pleasure and sheer enjoyment of the work. Some of the behavioral indicators that suggest an employee is motivated by intrinsic process include:

•        Easily completes tasks when he/she doesn’t enjoy the tasks assigned.
•        Often talks about how much he/she likes or dislikes the tasks assigned.
•        Volunteers freely for the activities that he/she enjoys most.
 
Basically, there are four factors that contribute to an individual’s intrinsic motivation:

1.      Challenge - (levels, leader boards, badges and goals are helpful)  In order for an activity to be challenging in a positive way, goal statements have to be clear and feedback has to be provided to engage and increase the site users’ confidence. In other words, the goal has to be constructive, clear, and encouraging. Quick goals are better than distant goals. “You will feel better immediately” is much more motivating than “In four weeks you will feel better". A mix of short term and long term objectives sould be provided to keep visitors engaged with their eye on a future “prize". Additionally, goals should be personally meaningful.
•       Factors that influence a person's perceptions of the relevance of a goal include:     i.      Whether or not achieving the goal allows the visitor to do something she could not do before (the goal is “functionally useful”)
    ii.     Whether or not the learner feels emotionally connected to the outcome   (“fantasy relevance”)
    iii.    Whether or not there is social relevance:
            1.      Cooperation (team dynamics, team leader boards )
            2.      Competition (personal leader boards)
            3.      Recognition (badges, personal leader boards, team leader boards)
•       Goals are necessary, but not sufficient for challenge. There needs to be a level of uncertainty. (After all, why engage in the activity if the outcome is already known) Techniques for variety include:
    i.      Goals that vary in difficulty level
    ii.     Hidden information
    iii.    Randomness
2.      Curiosity – The element of surprise  and desire to explore. Curiosity can arise from the fascinating complexity of a subject we need to unravel, or from elements that challenge our preconceived notions. Note: Malone and Lepper elaborate)
•       Sensory curiosity – humans natural attraction to bling, slick interfaces, novelty, movement and blink tags
•       Cognitive curiosity “learners and organizers” – the human natural urge to organize our knowledge structures more efficiently. Learners will experience sustained engagement when exploring learning environments that help them to be more productive, a better information filter, a better creator, etc.
3.      Control - People find games compelling because games give them a sense of control. In the game world, player decisions have consequences; winning isn’t dependent on completely random factors (although there can be an element of randomness). Similarly, an empowering learning environment will be one whose options are dependent on the learner’s choices,and those choices must be tied to significant and meaningful outcomes. However, for control to be motivating, it has to be tied to the player's belief that they are capable of succeeding - too many choices, and the player is unable to distinguish between them, thus becoming frustrated.
4.      Fantasy – This evokes mental images of physical or social situations which are not actually present. The optimal learning environment might be one in which individuals can create their own fantasies (e.g., imaginary characters, locations, objects).
•       Outcome - fantasies that depend on the skill being learned (e.g. Hangman, where the hanged man appears as correct letters are not identified)
•       Interdependent Simulations - situations where the skill being learned and the fantasy depend on one another (e.g. a simulation or role-playing game).
Note: Malone and Lepper hypothesized that fantasies are richer learning experiences, allowing visitors to connect new learning to prior knowledge through their narrative structure.
Bonus: Fantasies often address the emotional needs of learners, allowing them to experiment with new constructs in a low-risk environment.
Note: for more, see (Barbuto & Scholl, and Malone & Lepper).

B.      Instrumental motivation $$$. - Instrumental rewards motivate followers when they perceive their behaviors will lead to certain tangible extrinsic outcomes, such as pay or promotions.  Instrumental motivation is characterized by a concern for tangible incentives (e.g. cash, bonus, or travel vouchers ).  Some of the behavioral indicators that suggest an individual is instrumentally motivated include:
•       The user wanting to know “What’s in it for me?”
•       The user expecting compensation for any and all extra work he or she performs.
•       The user talking about how much money he or she makes or should make.
•        The user will frequently talk/write about the relative wealth of others.
Note: Individuals engage in tangible exchange relationships (Barbuto & Scholl, 1998).  This integrates Barnard’s (1938) material inducements, McClelland’s (1985) need for power, Katz and Kahn's (1978) legal compliance, and Kegan’s (1982) imperial stage of ego development. 

C.      Self-concept external motivation (reputation). - This motivation tends to be externally based. Followers attempt to meet the expectations of others by behaving in ways that elicit social feedback consistent with their own self-concept (Barbuto & Scholl, 1998).  Followers behave in ways that satisfy reference group members, first to gain acceptance, and then status.  This source of motivation is similar to Etzioni's (1961) social moral involvement, McClelland’s (1985) need for affiliation, and Barnard’s (1938) social inducements and is also incorporates referent influences such as social identification theory (Ashforth & Mael, 1989). Self-concept external motivation is characterized by a concern for others’ opinions. An employee motivated this way is very interested in preserving and enhancing reputation amongst peers and supervisors.  Some of the behavioral indicators that suggest an employee is motivated by self-concept external include will:
•        Individual frequently asks for others’ feedback.
•        Individual seeks praise and recognition for work performed, and is quick to post on Facebook or Twitter
•        Individual often brags or tells stories about accomplishments.
•        Individual is attentive to who receives credit when work is finished.

D.      Self-concept internal motivation (achievement). - In this source of motivation, individuals set internal standards of traits, competencies, and values that become the basis for the ideal self.  They are motivated to engage in behaviors that reinforce these internal standards and later achieve higher competency (Barbuto & Scholl, 1998; Leonard, et al., in press).  This source integrates McClelland's (1985) need for achievement, Kegan’s institutional stage of ego development, and Bandura’s (1986) personal standards and self-regulation.  Self-concept internal motivation is characterized by a concern for meeting one’s personal standards of performance. An individual who is motivated this way is not concerned with others’ feedback and tends to be self-driven.  Some of the behavioral indicators that suggest an individual is motivated by self-concept internal include:
•        He or she seeks to perform the most difficult tasks on the site.
•        He or she works best when their own skills are needed for the tasks.
•        He or she is interested in developing their own range of skills.
•        He or she performs the most important tasks with little supervision or outside direction.

E.      Goal internalization motivation (values and principles). – In this source of motivation, followers adopt attitudes and behaviors based entirely on their personal value systems  Goal internalization is characterized by a need to believe in the cause.  A player/visitor who is motivated this way uses value-based principles to guide decisions and actions.  Some behavioral indicators that a player is motivated by goal internalization include:
•        He or she asks about, or seeks the purpose of tasks (“Why are we doing this?”).
•        He or she comments on the strategic focus of the site.
•        He or she works hard when one believes in the cause and will not if they don’t.
•        He or she lives a professional life guided by a strict set of principles and values.
Note: For more see (Barbuto & Scholl, 1998).  This integrates Etzioni’s (1961) pure moral involvement, Katz and Kahn’s (1978) internalized values, and Kegan’s (1982) inter-individual stage of ego development.

Some Background, Notes and Related Reading
Some of this taxonomy is based on the work of Leonard, Beauvais, and Scholl  These sources of motivation include intrinsic process, instrumental, external self-concept, internal self-concept, and goal internalization. Research using this taxonomy has examined influence tactics (Barbuto & Scholl, 1999; Barbuto, Fritz, & Marx, in press), transformational leadership (Barbuto, Fritz, & Marx, 2000) and other miscellaneous variables.  In 1987, Thomas Malone and Mark Lepper published: Making learning fun: A taxonomy of intrinsic motivation.
There have been many perspectives offered from different fields.  These perspectives have included psychosocial (Jung, 1971) expectancy (Vroom, 1964;), need-based (Alderfer, 1969; Maslow, 1954; McClelland, 1985), social identification (Ashforth & Mael, 1989), value-based (Etzioni, 1961; Katz & Kahn, 1978), goal setting (Locke & Latham, 1984), self concept-based (Brief & Aldag, 1981; Sullivan, 1989), and ego development (Kegan, 1982; Loevinger, 1976) perspectives. 
Daniel Pink has a wide range of popular and recent material on psychology.  There is a great YouTube video http://www.youtube.com/watch?v=u6XAPnuFjJc  His books Drive: The Surprising Truth About What Motivates Us is a best seller, and available on iTunes
Noah J. Goldstein wrote: Yes!: 50 Scientifically Proven Ways to Be Persuasive
Alderfer, C. P. (1969).  An empirical test of a new theory of human needs.  Organizational Behavior and Human Performance, 4, 142-175.
Ashforth, B. & Mael, F. (1989). Social identity theory and the organization.  Academy of Management Review, 14(1), 20-39.
Bandura, A. (1986). Social foundations of thought and action: A social cognitive theory.  Englewood Cliffs, NJ: Prentice Hall.
Barbuto, J. E., & Brown, L. L. (1999). Motivating your employees. NebGuide G99-1397A, Cooperative Extension, Institute of Agriculture and Natural Resources, University of Nebraska-Lincoln.
Barbuto, J. E., Fritz, S. M., & Marx, D. (2000). A field study of two measures of work motivation for predicting leader’s transformational behaviors.  Psychological Reports, 86, 295-300.
Barbuto, J. E., Fritz, S. M., & Marx, D. (In press). A field study of two measures of work motivation for predicting leader’s influence tactics used.  Journal of Social Psychology.
Barbuto, J. E. & Scholl, R. W.  (1999). Leader’s motivation and leader’s perception of follower’s motivation as predictors of leader’s influence tactics. Psychological Reports, 84, 1087-1098.
Barbuto, J. E., & Scholl, R. W. (1998).  Motivation sources inventory: Development and validation of new scales to measure an integrative taxonomy of motivation.  Psychological Reports, 82, 1011-1022.
Barnard, C. (1938). The functions of the executive. Cambridge: Harvard University Press.
Brief, A. & Aldag, R. (1981). The self in organizations: A conceptual review.  Academy of Management Review, 6, 75-88.
Etzioni, A. (1961). A comparative analysis of complex organizations. NY: Free Press.
Jung, C. G. (1971).  Psychological types. Princeton, NJ: Princeton University Press.
Katz, D., & Kahn, R.L. (1978). The social psychology of organizations. NY: Wiley.
Kegan, R. G. (1979). The evolving self. The Counseling Psychologist, 8, 5-34.
Kelman, H. C. (1958). Compliance, identification, and internalization: Three processes of attitude change. Journal of Conflict Resolution, 2, 51-56.
Leonard, N. Beauvais, L., & Scholl, R. W. (1999). Work motivation: An incorporation of self-concept based process. Human Relations, 52, 969-998.
Locke, E. & Latham, G. (1984). Goal setting: A motivational technique that works.  Englewood Cliffs, NJ: Prentice Hall.
Loevinger, J. (1976). Ego development. San Francisco: Jossey-Bass, Inc.
Maslow, A. (1954). Motivation and Personality. New York: Harper & Row.
McClelland, D. C. (1985).  Human Motivation.  Glenview, ILL: Scott, Foresman.
Sullivan, J. (1989). Self theories and employee motivation. Journal of Management, 15, 345-363.
Vroom, V.H. (1964). Work and Motivation. New York: Wiley.
Biggs, J. B. (1987). Student approaches to learning and studying. Melbourne: Australian Council for Educational Research.
Bruner, J. S. (1966). Towards a theory of instruction. Cambridge, MA: Harvard University Press.
Czikszentmihalyi, M. (1975). Play and intrinsic rewards. Journal of Humanistic Psychology, 15 (3), 41-63.
Habgood, M. P. J., Ainsworth, S., &  Benford, S. (2005). Endogenous fantasy and learning in digital games. Simulation and Gaming, 36(4), 483-498.
Habgood, M. P. J. (2007). The effective integration of digital games and learning content.  [Doctoral Dissertation]. University of Nottingham, United Kingdom. Retrieved August 20, 2011 from http://etheses.nottingham.ac.uk/385/1/Habgood_2007_Final.pdf
Malone, T. W., & Lepper, M. R. (1987). Making learning fun: A taxonomy of intrinsic motivations for learning. In R. E. Snow & M. J. Farr (Eds.), Aptitude, Learning and Instruction III:Conative and affective process analyses (pp. 223-253). Hilsdale, NJ: Erlbaum.

Is Zynga the first billion dollar psychology company? or a taxonomy of motivation (Part 1)

The key to gamification is understanding motivation, and no game company demonstrates this understanding more than Zynga.  Game, Education, Healthcare and Fintech Entrepreneurs can learn a lot by following the motivation techniques exhibited in Zynga products.  Don’t believe me? Think of it this way: In a few month Zynga motivated over 50 Million new people to learn how to run a virtual farm, and have fun doing it.   Try motivating 50 people to sign up for a class on farm management and you will appreciate their accomplishments.

Gabe Zichermann had a great post yesterday where he described a two branch taxonomy for understanding motivation. (Intrinsic and Extrinsic).  It’s a start, but insufficient. The Mad Men of Madison Avenue sometime refer to a three branch motivation taxonomy: get paid, get laid, or get made.   This too is insufficient.  Entrepreneurs and product managers need a more robust framework, if they hope to create breakthrough products.

The good news is I believe a “unifying” motivation framework is coming!

 
Motivation has always been an elusive concept.  Economists, Managers, Marketers, Psychologists and Anthropologist have wrestled with the topic for centuries. 
I believe thanks to click and social graph data, the motivational social sciences will take significant steps forward in the next four years.  Big Data to the rescue!

Four years is an eternity in internet time, so in the interim I propose a five node framework/taxonomy:
A.      Intrinsic Process: Derived from fun or enjoyment during the task  
B.      Instrumental: Derived from expectations of tangible rewards
C.      Self-Concept External: Derived from a desire to improve one’s reputation and image
D.      Self-Concept Internal: Derived from a need to meet personal standards and achieve
E.      Goal Internalization: Derived from a deep-rooted belief in the cause or principle

Sophisticated web application developers can look at all their work flows, screen design and user stories through the lens of “motivational profiles”, and whenever possible,  customize the UI, UX and messaging based on the predicted/observed motivational profile.  

Hope this proves helpful, especially if you are about to use "social gamification" to change education or healthcare. Good Luck!

I will elaborate in Part 2..

NYC’s Shawn Parker Density

Monday,  Paul Graham gave a speech at General Catalyst.   Paul has great insights into what makes a great tech hub and zeroed in on the final piece of NYC’s start-up ecosystem. The piece just now cementing into place: Entrepreneurs' ability to run into high quality mentors.  Paul used Shawn Parker’s mentoring of Mark Zuckerberg as the classic example.  Facebook would not be what it is today had Shawn not run into Mark.  HP, Apple, Intel and Google all have similar serendipity. The founders all received critical help from the ecosystem. 
 
Paul is right to highlight the importance of running into smart, driven people who are experienced in entrepreneurship and technology.  This continuous cross-pollination of experience, vision and innovation is paramount.
 
Over the last 15 years, the NY tech scene has really evolved.   Although it takes 20 years  to build a robust start-up ecosystem, NYC has made great strides since 1995 when we started SquareEarth our first internet technology company.  Back then, similar to today, there were great reserves of engineers inside wall street, but pulling them out was almost impossible.   I got lucky. Marc Andreessen came to visit Solomon Brothers to spread the gospel of the browser, and I was able to pull from the pool of engineers whose lives were changed by his visit.  Back in the mid 90s,  Solomon Brothers was pioneering the use of the browsers as part of their $400,000,000 annual technology investment.   Banks and hedge funds are still huge pools of technical talent, but today, technical talent is more willing to transition to a tech startup.  Companies like Aristotle Circle, Delicious, Gerson Lehrman,  TheLadders and Secondmarket were all founded by former Wall Streeters.
 
Back in 1995 people in NYC interested in tech-startups were few and far between.   Guys like Peter Bloom, Michael Bloomberg and Bernard Weinstein were important tech mentors, but your chance of running into them on the street was three in a million.  Today, we have a vastly different story.  Now there are hundreds of veteran tech start-up professionals in NYC playing that “Sean Parker” role.  
 
Outsiders think access to technical talent is the gating factor for faster start-up growth on NYC. It is not. (like Silicon Valley, our demand for exceptional technical talent is limitless).  Others think the constraining factor is Seed Capital. Untrue.  NYC is full of dozens of seed-stage funds, hundreds of Angels, and thousands of qualified investors, all looking for investments.   You could argue that the lack of a MIT or Stanford will mean NYC will always be a tier 2 tech hub, but neither does this tell the whole story.  NYC is currently pursuing Stanford and 14 other top engineering schools to set up a multibillion dollar campus in NYC.  Plus, NYC is already a college town, There are about 594,000 university students in New York City attending around 110 universities and colleges.   Low rent space, easy transportation, access to media, and a huge creative class all help, but it is the high density of people passionate about startup tech that makes all the difference.  
 
Maybe my view is skewed by having offices on either side of Union Square, with my main office sharing an elevator with Foursquare, resulting in a regular flow of random reconnections.   
 
That said,  like a diamond dealer making regular trips to Antwerp, or a movie star visiting Hollywood, as a tech entrepreneur, I still need to make regular trips to Silicon Valley.   It’s Tech Start-Up Mecca, but after 15 years,  it’s good to see NYC has achieved its “Sean Parker” density. 

Information wants to be Free, Money wants to flow Freely

In the mid 1980s, technologist Stewart Brand observed “Information wants to be free”, in one simple statement Brand predicated the fall of governments and the restructuring of industries. There were powerful interests, aligned against the idea of information flow, but in the end Middle East dictators, and media executives all had to adapt to the tide of new technology.

Brand was the Founder of the Whole Earth Catalog, and his full quote is:

“On the one hand information wants to be expensive, because it's so valuable. The right information in the right place just changes your life. On the other hand, information wants to be free, because the cost of getting it out is getting lower and lower all the time. So you have these two fighting against each other.”

I think CraigsList, BitTorrent and Google are the embodiment of the idea of free flowing information.  Google, along with other search tools, empower individuals to connect directly with information, disintermediating any friction that does not add value to the flow of information. Not good for record labels, great for consumers.

But just as Google empowers information flow, Facebook and Google+ empower Money.

Money and information are in many ways interchangeable. Money represents a special type of information, an informational unit called trust.  In barter, one trusts that 8 chickens will be worth something in the future, either to yourself or to others. In Roman times one trusted that metal coins could be exchanged for goods, in the 50s it was trusted that paper money could be exchanged for gold or silver, and today one trusts that your government issued paper will buy goods in the future.

Information = Trust

Trust = Money

Information = wants to be free

Therefore

Money = wants to be free

Or said another way

Money wants to flow freely

Historically only big institutions had the gravitas to be the trusted intermediary for industrial scale commerce, and for this role they extracted a hefty fee. Wire fees, transaction fees, merchant interchange fees, credit card fees, regulations, bank fees and currency depreciation all represent friction to the free flow of capital.

What happens when trust can be calculated by careful analysis of your endorsements and social network?

What happens when communities can easily form groups (AKA "circles"  ) to cross collateralize, insure, or drive better terms?

The result will be hundreds of new companies, maybe even new industries. Companies like AirBnB, Groupon, Lenddo and Square are just the tip of a “socially empowered” commerce renaissance.  

Stewart Brand was right, and we see information flow in the form of media has been radically changed over the last 10 years. But consumer media represents only about 2% of GDP,  finance is closer to 8% of GDP.

Let me say that again for emphasis.  TV, Radio, Advertising and Social Media represent about 2% of GDP, and they have been transformed by technology. The finance Industry is 4 times bigger!

Media is a precursor of the change to come, Mark Zuckerberg says "every industry will be changed by social". Tom Anderson, co-founder of MySpace says "everything got better when it was social".

What happens when finance becomes socially empowered?  

I guess the best way to predict the future is to create it.   

 

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It takes 20 years

Marc Andreessen was interviewed about Bubbles in today’s New York times.  It got me thinking about a core lesson from history: breakthrough technologies impact society in unexpected ways, and generally take 20 years before their true potential is realized.  

In late 1994 I had to make the biggest decision in my life: Should I quit my career as a management consultant to start my first internet business? I was learning tons as a consultant, had great mentors, and had a hard time imagining having more fun.

However, since my first lemonade stand, I always felt destined to start companies. In following the growth of the World Wide Web, I felt the time was right to try my hand as a full time entrepreneur. My gut said the magnitude of the web opportunity would more than offset my relative lack of business experience.

My holistic, big picture right brain was ready to make the move, but my analytical left brain still wanted more data. I needed data to squash my hesitation. The problem was little data existed about the World Wide Web. I charted mentions in the press; I charted user growth; I extrapolated future data. But none of them gave insights into the impact of the internet on society. For that I would have to look back into history.

Edmund Burke said, “Those Who Don't Know History, Are Destined To Repeat It.”

I say “Those Who Don't Know History, Are Destined to Not Profit From The Future.”

So I hit the books to study the biggest technological changes of the last 1000 years with an emphasis on the societal impact. My targets: Gutenberg Printing Press, Steam Engine, Electricity, Railroad, Broadcasting, Telegraph, Movies, Telephone, Automobile and the Personal Computer. Research took several weeks, but my view was unobstructed as I was able to stand on the shoulders of giants. Much had been written about the impact of technology on society. Eventually a pattern emerged:

Phase I: People at first underestimated the technology’s potential
Phase II: People then got excited about the potential, but then underestimated how long it would take (The bubble)
Phase III: Technology eventually reached its potential, but only years after the bubble popped
Phase IV: Eventually Society was impacted in even more than expected, and in unexpected ways, usually about one generation later (20 years)

Printing Press, Steam Engine, Electricity, Railroad, Broadcasting, Telegraph, Movies, Telephone, Automobile and the Personal Computer all conform to this pattern. This is not an asset bubble pattern (think Tulips, Silver or Mortgage Backed Securities).  It’s a technology bubble pattern. Around 2015 we should expect to enter Phase IV for the internet.

Get Ready! Phase IV is where the second order and unexpected societal impacts occur.  The automobile led to suburbization, highways, the drive-in movies, fast food and a change in how you interacted with your community.   Electricity lead to the light bulb, reading at night, home appliances, and the change in the role of women in the household.   

Reshaping the media industry is entertaining, but the “World Wide Web” is just getting started.   The “big” industries are Energy, Finance and Health Care.  When the internet, combined with social and mobile, hits those industries look out! Those changes will make CraigsLists, Yahoo and Netscape look like my first lemonade stand.

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Startups and Whiteboards: Like chocolate and peanut butter

Really the title should be a phrase: we need more whiteboards!  The number of startups here and New York are growing like brushfires.  If you visit a few startups one thing you see is lots of Whiteboards. Seems like startups and dry erase boards are like chocolate and peanut butter, or like Red Bull and, well startups. They go great together.
 
Whiteboards are one of the most important business tools a startup could have… entrepreneurship and software development are inherently creative, collaborative, information intensive processes. The startup blogosphere has lots of posts on hiring, marketing, software development and fundraising.  But what about whiteboards?  The “experts” are missing this critical tool in the entrepreneur toolkit. Sure you may learn something from Lee Hower that will help you close $5,000,000 in funding, but what good is that money if can’t collaboratively design your next pivot? That requires a great collaboration and brainstorming tool, the best I've ever seen at least.   
 
Successful project management systems revolve around people.  And as you probably know, no matter how many new “innovative” project management tools you try, there is always a role for the age-old, reliable whiteboard.  It is the ultimate collaborative tool. 
 
As a startup Founder and Investor, I found the whiteboard to be central to any good business.  It encourages focus, communications and effectiveness. Sadly, today, whiteboards are not getting the critical attention they deserve, an online-startup-knowledge void I hope to fill. 
 
So at first glance, it seems easy. Walk over to Staples and pick a size and order.  But wait, you’re embarking on building a world changing company, the next Facebook, and the whiteboard is a critical tool of your craft.  It would be like Lady GaGa buying her outfits at Lane Bryant, or Michael Jordan buying his sneakers at Payless.  They're more creative than that, and you can be too.
 
True, every penny counts in a startup, but you shouldn't cut corners on your most critical tools. Would you swap your new 27’ Mac for a 5 year old Gateway to save a few bucks, no way!  Maybe your whiteboard is just as key?
 
So what are your other choices?
 
Whiteboard Wallpaper – I have had good experiences with wallpaper. Several of the conference rooms at Mimeo.com have floor to ceiling whiteboard walls, and the ideas just keep coming when the space allows.  One consideration, the wallpaper comes in both mat and glossy finish.  I recommend gloss, unless you are also using the wall for projecting in which case I would recommend a mat finish.  
 
Whiteboard paint –  I have not had as much success with paint, but I think this is a good option for irregular surfaces where you anticipate light use (i.e list that change only monthly). The other advantage is the paint can be applied it to any shape or place in your office, but it’s definitely a light duty option.
 
Write-on poly sheets - are basically glorified white vinyl sheets (just a small step up from thick trash bags) but they are great when you need something right this instant, right now, today.  Poly sheets are also temporary, so you can take them with you when you take over your investor’s summer house for your corporate offsite.   The con, they’re tricky to handle, and like plastic wrap they cling to themselves ferociously.  The other con is any office that has plastic cling whiteboards definitely gives of the image that you will be packed up and gone tomorrow.  Not exactly reassuring to potential hires. (BTW, its also easy to get overly enthusiastic and accidentally write over the edge, onto the wall).
 
I didn't mention blackboards and blackboard paint, mainly because from time to time I wear a suit, and chalk and suits don’t mix.  Betaworks seems to have success with blackboards, and I have seen them in the quantitative trading conference room at Morgan Stanley.  The math PHDs love them, they give off a real academic vibe, but I don’t like the fact that the black surface can’t double as a projector screen (and like I said, chalk is messy).  So until I get my own “minority report” super screen, I am counting whiteboards as a core startup tool.

The Entrepreneurial Singularity - or - Moore's Law for Start-ups

Steve Blank has an excellent article “When It’s Darkest Men See the Stars”  which is the talk-of-the-town in the serial entrepreneur community. A brief excerpt:

“Entrepreneurial Singularity - The barriers to entrepreneurship are not just being removed. In each case they’re being replaced by innovations that are speeding up each step, some by a factor of ten. For example, Internet commerce startups the time needed to get the first product to market has been cut by a factor of ten, the dollars needed to get the first product to market cut by a factor of ten, the number of sources of initial capital for entrepreneurs has increased by a factor of ten, etc.”

Sounds a lot like CPU’s and Moore’s Law, eh?

If you follow Steve’s writing you find his basic premise is that a start-up is a project to find a business model, and that most startups will need to “pivot” before finding a model that works. 

Iterate to Success – Start-up Clock Speed

I look at each pivot as a special type of iteration.  An iteration is a change in product, packaging or business model.  Not all iterations are pivots, but all pivots are iterations.  The pace of iterations is an organization’s clock speed.  The faster you iterate, the more likely you are to strike success with the market. Usually the faster your clock speed the less cash you consume between iterations.  A start-up that has a clock speed of 6 months will have two chance to get it right on I year of cash, a startup with a clock speed of 30 days will have 12 chances.   In large organizations, an iteration is merely a product enhancement, or market expansion, but in a start-up one iteration can be the difference between riches and bankruptcy.   Urgency is critical.  

At the core of Ray Kurzweil’s Singularly is CPU clock speed.   In 1981, my first computer, had a clock speed of 4.77 MHzs, but computer speeds have steadily marched forward. The time and cost of a cycle was roughly cut in half every two years.  Will the same thing happen with start-ups?  Could faster iterations result in a startup singularity?    I don’t know.  It seems that the maximum start-up iteration speed is constrained by how fast customers will provide feedback.  But people have said Moore’s law would meet its constraint for over 15 years, yet every time the chip engineers think its over someone finds another way to speed up the chips.  

I wonder if entrepreneurs will have similar success in increasing the start-up cycle time.  Certainly in the next few years there will be massive improvements.  The time it takes to build teams, release software, attract investors, and close customers is still measured in months.   We (entrepreneurs and investors) can do better, and we will.    Recruiting, Agile Development, Seed Investing and Marketing are all fertile ground where innovation is flourishing, and increased innovation will increase speed.  

Tech IPO's: What TechCrunch & Fred Wilson Are Leaving Out

Erick Shonfeld has a great post up on Techcrunch called "The Poor Pilloried Tech IPO" that's worth a read, following on Fred Wilson's  recent post on the same subject.  Says Erick:

A decade ago, tech IPOs ruled the stock markets and Silicon Valley. They were the end-all and be-all for ambitious entrepreneurs and venture capitalists looking to become instant billionaires, or at least millionaires. That was many booms and busts ago. The IPO market never came back, and the multiple financial meltdowns which brought on Sarbanes-Oxley and other regulations made going public even less appealing to shoot-from-the-hip entrepreneurs. The founders of the most successful tech companies today—Facebook, Skype, LinkedIn—are pushing off the inevitable IPO for as long as possible. And for smaller tech companies, IPOs seem hardly worth the bother.

As I said in my April post on "Why Ten Million Dollar IPO's Matter", the U.S. IPO torrent has turned into to a trickle:

My concern is that we are not graduating the “Intels” of tomorrow.
 
AT&T, Disney, General Electric, Genentech, Cisco, Intel, Microsoft, Google and E-bay all had a public offering.  Since going public, they have all benefited from the credibility, profile and prestige associated with being publicly traded companies.  And of course the access to capital, both as IPOs, and perhaps even more importantly, with secondary offerings. The ability to do a short lead time secondary offering gives a company enormous flexibility.

But that flexibility is unavailable to most growth companies today.
 
Would the phone, talking movie, television, personal computer, and internet industry have been as innovative if these leading companies were instead acquired as a division of Western Union?   I think not, but that is the future of most venture-backed companies today. M&A has become the only available exit for growth investors and Founders. 

But why? Erick, as well as some of the people he quotes like Fred Wilson and Frank Quattrone, point to one or two barriers to going public - mostly the lack of "category-defining, earthshaking" precedents, and regulatory hurdles (such as Sarbanes-Oxley). But I think that's just the tip of the iceberg.

As I posted before, there are at least nine major impediments preventing tech IPO's:

1. Death of the mid-market investment firms
2. Decimalization. 
3. Rise of the Internet Brokerages
4. Growth of Prop Trading.
5. End of Equity Research.
6. Increased Litigation Risk
7. The Internationalization of Wealth.
8. Larger Global Funds.
9. Increased Regulatory Expense including Sarbanes-Oxley.

Quattrone's conclusion is right -  VC's need an IPO market. But I think he's wrong if he thinks the problem will be solved just by a few high profile IPO's from some current web standard bearers. 

Our community needs to address ALL the key impediments for tech IPOs. Something must change, even if it means moving the IPO market off-shore and and excluding U.S. participation to under 500 U.S. “Qualified” Investors.
 
There are smart people in Silicon Valley, London, New York and Hong Kong working on ways to overhaul the IPO process.  As tech innovation moves millions more into the middle class, people need a better place to invest their new wealth. And by 2035 the majority of the world’s wealth is expected to be outside the G20. It's inevitable that markets will connect these investors with start-ups and innovation will continue, that's a given.

But the big question -- how long it will take U.S. entrepreneurs and investors to figure this out?