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Posts from the ‘Economics’ Category

The Millennial Definition of Success

Wealthfront Team, June 2014

Wealthfront Team, June 2014

It’s hard to believe in 2014, but when I first considered joining LinkedIn in 2007, most of my colleagues had trouble seeing the value in a platform built on top of what looked like an online résumé. At the time, when I was asked why I joined the company, I would tell them that it had always been true that success in business was based on what you know and who you know.  LinkedIn was just the modern incarnation of that powerful fact.

One of the most pleasant surprises in my current role at Wealthfront has been discovering how relevant career success is to millennial investors. As it turns out, every generation has grappled with the issue of how to find financial success, and millennials are no different.

What may surprise most people (including my compatriots in Gen X) is that more than any other generation, I believe that Millennials may have a lot to teach us. You see, it turns out that Millennials have figured out how to make that old adage actionable.

Who You Work With & What You Work On

Increasingly, as I talk to Millennials, some of whom who have found early success in their careers, and others who are just starting out, I hear the same things. This generation overwhelmingly associates success with control over who they work with, and what they work on.

There is an old refrain in management that people join companies, but they leave managers. There is a kernel of truth in that statement. However, in the modern workplace, relationships with colleagues, managers and leadership all have a role to play. Increasingly, valuable employees ask:

  • Am I learning from the people I work with?
  • Are we succeeding together as a team?
  • Do I share the same values as my colleagues?
  • Will I fight for them? Will they fight for me?

Driven by Passion, Seeking a Mission

There have been numerous surveys and studies indicating that Millennials are overwhelmingly focused on “their passions.” I think, in some regards, this has trivialized a more fundamental and important trend.

Is it really surprising that more and more people have realized that what you are working on matters?

The old duality of your work life and your personal life have been hopelessly intermingled. Instead of arguing about whether you live to work or work to live, in the 21st century people increasingly turning away from a purely mercenary view of their labor. They want to believe in the mission, believe their efforts are going towards something bigger than just financial reward. This is why you hear increasing anecdotes of young people choosing lower paying jobs, in some cases jobs that pay tens of thousands of dollars less, to focus on an organization that they draw more purpose from.

Success = Control

Not everyone has this luxury, and in some ways that is the point. What does success really mean, if it doesn’t mean that you get increasing control over who your work with, and what you work on?

Wealthfront now has over 12,000 clients, and most of them are under 35. What I find striking is that, overwhelmingly, with every success in their financial lives, these young people seem to immediately focus on using their success to gain control over their careers. They don’t seek to optimize for title, or  financial reward. Instead, they increasingly use their success to effectively fund the ability to work on a product they believe in, an organization they want to be part of, and a leader they want to follow.

As the CEO of a hypergrowth company, this leaves me with two pieces of actionable advice:

  • Financial reward is not enough. If you want to attract and retain the best and the brightest, financial reward is somewhat of a commodity, and an undervalued one at that. Instead, expect potential candidates to look at your company and ask, “Is this a problem I want to work on?” and “Are these people I want to work with?”
  • This is a networked economy. As Reid Hoffman has described, increasingly the value people build in their careers extends outside of your company. There is a material, and possibly essential difference, in a consumer business where your employees feel like they are punching a clock, versus a team that truly believes in what they are working on and the team they are working with. The influence of your employees, especially as your company grows, is under-measured, and as a result, under-appreciated. But in a huge networked economy, it may be the key to differentiated success.

Leadership Lessons from the Code Conference

This past week, I was able to attend the inaugural Code Conference organized by Walt Mossberg & Kara Swisher.  One of the perks of the conference is, within close quarters, the chance to hear the leaders of huge, successful consumer technology companies.

      • Satya Nadella, Microsoft
      • Sergey Brin, Google
      • Brian Krzanich, Intel
      • Brian Roberts, Comcast
      • Reed Hastings, Netflix
      • Travis Kalanick, Uber
      • Drew Houston, Dropbox
      • Eddie Cue, Apple (iTunes / iCloud)

As I think about lessons from the conference, I find myself focused on a particular insight watching these leaders defend their company’s strategy and focus.  (It’s worth noting that anyone being interviewed by Kara does, in fact, have to be ready to play defense.)

David to Goliath

One of the most complex transitions that every consumer technology company has to make is from David to Goliath.  It’s extremely difficult in part because the timing is somewhat unpredictable.  Is Netflix an upstart versus the cable monolith, or a goliath itself as it is responsible for a third of all internet traffic?  When exactly did Google go from cool startup to a giant that even governments potentially fear?  Apple, of course, went from startup to giant to “beleaguered” and all the way to juggernaut.

Make no mistake, however.  The change in public opinion does happen, and when it does, the exact same behaviors and decisions can be read very differently in the court of public opinion.

Technology to Economics to Politics

Most technology companies begin with language that talks about their technical platform and achievements. “Our new product is 10x faster than anything else on the market,” or “Our new platform can handle 10x the data of existing platforms,” etc.  Sometimes, these technical achievements are reframed around end users: “We help connect over 1 billion people every day,” or “we help share over 10 billion photos a week,” etc.

Quickly, however, the best technology companies tend to shift to economics. “Our new product will let you get twice the sales in half the time,” or “our application will save you time and money.”  As they grow, those economic impacts grow as well.  Markets of billions of dollars are commonplace, and opportunities measured in hundreds of billions of dollars.

Unfortunately, as David moves to Goliath, it seems that many technology leaders miss the subtle shift in the expectations from their leadership.   When you wield market power that can be measured on a national (or international) scale, the challenge shifts from economics to politics.  Consumers want to know what leaders they are “electing” with their time and money, and their questions often shift implicitly to values and rights rather than speed or cost.

What Will the World Be Like Under Your Leadership?

As I watched various leaders answer hard questions about their companies, a clear division took place.  Most focused merely on questions of whether they would succeed or fail.  But a few did a great job elevating the discussion to a view of what the world will be like if they are successful.

There is no question that the leaders who elevated the discussion are finding more success in the market.

Satya Nadella gave no real reason why we would like the world better if Microsoft is successful.  Neither did Brian Krzanich of Intel.

Sergey Brin promises that in a world where Google is successful, we’ll have self-driving cars and fast internet for everyone.  Jet packs & flying cars.  It’s an old pitch, but a good one.

Eddie Cue tells us that Apple cares about making sure there is still great music in the world.  And of course, Apple has spent decades convincing us that when they are successful, we get new shiny, well-designed devices every year.

Is it really surprising that Google & Apple have elevated brands with high consumer value?

Technology Leadership

There is no way around the challenges of power.  As any company grows, it’s power grows, and with that power comes concern and fear around the use of that power.  Google has so much control over information and access to information.  Apple tends to wield tight control over the economics and opportunities within their ecosystem.  However, the leaders at these companies are intelligently making sure that the opportunities they promise the market counter-balance those fears, at least at some level.

Wealthfront, my company, is still small enough that we’re far from being considered anything but a small (but rapidly growing) startup in a space where giants measure their markets in the trillions.  But as I watched these technology leaders at the Code Conference, I realized that someday, if we’re successful, this same challenge will face our company.

If you lead or work for a technology giant, it’s worth asking the question:

Does your message elevate to the point where everyone understands the tangible benefit of living in a world where your company is successful?  If not, I’d argue your likely to face increasing headwinds in your efforts to compete in the consumer market going forward.

Google vs. The Teamsters

Yesterday, Google launched Chromecast, a streaming solution for integrating mobile devices with TV, part of another salvo against Apple.  Google vs. Apple has been the hot story now in Silicon Valley for a couple of years.  Before that, Google vs. Facebook.  Before that, Google vs. Microsoft.  Technology loves narrative, and setting up a battle of titans always gets the crowd worked up.

Lately, I’ve been thinking about the next fight Google might be inadvertently setting up, and wondering whether they are ready for it.

350px-Optimusg1

Self-Driving Cars or Self-Driving Trucks

It turns out I’m not the only one who noticed that Google’s incredible push for self-driving cars actually has more likely applications around trucking.  Yesterday, the Wall Street Journal wrote an excellent piece about Catepillar’s experiments using self-driving mining trucks in remote areas of Australia.  It had the provocative headline:

Daddy, What Was a Truck Driver?

This is the first piece in the mainstream media that I’ve seen connecting the dots from self-driving cars to trucking, even with a lightweight reference to the Teamsters at the end.

Ubiquitous, autonomous trucks are “close to inevitable,” says Ted Scott, director of engineering and safety policy for the American Trucking Associations. “We are going to have a driverless truck because there will be money in it,” adds James Barrett, president of 105-rig Road Scholar Transport Inc. in Scranton, Pa.

The International Brotherhood of Teamsters haven’t noticed yet, or at least, all searches I performed on their site for keywords like “self driving”, “computer driving”, “automated driving”, or even just “Google” revealed nothing relevant about the topic.  But they will.

Massive Economic Value

The statistics are astonishing.  A few key insights:

  • Approximately 5.7 million Americans are licensed as professional drivers, driving everything from delivery vans to tractor-trailers.
  • Roughly speaking, a full-time driver with benefits will cost $65,000 to $100,000 or more a year.
  •  In 2011, the U.S. trucking industry hauled 67 percent of the total volume of freight transported in the United States. More than 26 million trucks of all classes, including 2.4 million typical Class 8 trucks operated by more than 1.2 million interstate motor carriers. (via American Trucking Association)
  • Currently, there is a shortage of qualified drivers. Estimated at 20,000+ now, growing to over 100,000 in the next few years. (via American Trucking Association)

Let’s see.  We have a staffing problem around an already fairly expensive role that is the backbone of a majority of freight transport in the United States.  That’s just about all the right ingredients for experimentation, development and eventual mass deployment of self-driving trucks.

Rise of the Machines

In 2011, Andy McAfee & Erik Brynjolfsson published the book “Race Against the Machine“, where they describe both the evidence and projection of how computers & artificial intelligence will rapidly displace roles and work previously assumed to be best done by humans.  (Andy’s excellent TED 2013 talk is now online.)

The fact is, self-driving long haul trucking addresses a lot of the issues with using human drivers.  Computers don’t need to sleep.  That alone might double their productivity.  They can remotely be audited and controlled in emergency situations.  They are predictable, and can execute high efficiency coordination (like road trains).  They will no doubt be more fuel efficient, and will likely end up having better safety records than human drivers.

Please don’t get me wrong – I am positive there will be a large number of situations where human drivers will be advantageous.  But it will certainly no longer be 100%, and the situations where self-driving trucks make sense will only expand with time.

Google & Unions

Google has made self-driving cars one of the hallmarks of their new brand, thinking about long term problems and futuristic technology.  This, unfortunately, is one of the risks that goes with brand association around a technology that may be massively disruptive both socially & politically.

Like most technology companies in Silicon Valley, Google is not a union shop.  It has advocated in the past on issues like education reform.  It wouldn’t be hard, politically, to paint Google as either ambivalent or even hostile to organized labor.

Challenges of the Next Decade

The next ten years are likely to look very different for technology than the past ten.  We’re going to start to see large number of jobs previously thought to be safe from computerization be displaced.  It’s at best naive to think that these developments won’t end up politically charged.

Large companies, in particular, are vulnerable to political action, as they are large targets.  Amazon actually may have been the first consumer tech company to stumble onto this issue, with the outcry around the loss of the independent bookstore.  (Interesting, Netflix did not invoke the same reaction to the loss of the video rental store.)  Google, however, has touched an issue that affects millions of jobs, and one that historically has been aggressively organized both socially & politically.  The Teamsters alone have 1.3 million members (as of 2011).

Silicon Valley was late to lobbying and political influence, but this goes beyond influence.  We’re now getting to a level of social impact where companies need to proactively envision and advocate for the future that they are creating.  Google may think they are safe by focusing on the most unlikely first implementation of their vision (self-driving cars), but it is very likely they’ll be associated with the concept of self-driving vehicles.

I’m a huge fan of Google, so maybe I’m just worried we may see a future of news broadcasts with people taking bats to self-driving cars in the Google parking lot.  And I don’t think anyone is ready for that.

Behavioral Finance Explains Bubbles

Note: This post ran originally in TechCrunch on April 20.  As a courtesy to regular followers of my blog, I’ve reposted the content here to ensure that longtime readers have access to it.

“Bubbles are beautiful, fun and fascinating, but do you know what they are and how they work? Here’s a look at the science behind bubbles.” – About.com Chemistry, “Bubble Science

“Double, double toil and trouble
Fire burn, and cauldron bubble.” – Macbeth, Act 4, Scene 1

Given the incredible volatility we’ve seen lately in the Bitcoin and gold markets, there has been a resurgence in discussion about bubbles. This topic is always top of mind in Silicon Valley, especially given that the two favorite local topics of conversation are technology companies and housing.

Defining a market bubble is actually a bit trickier than it might first appear. After all, what differentiates the inevitable booms and busts involved in almost any business and industry from a “bubble”?

The most common definition of a speculative or market bubble is when a broad-based, surging euphoria or wave of optimism carries asset prices well beyond supportable value. The canonical bubble was the tulip mania of the 1630s, but it extends across history and countries all the way up to the Internet bubble of the late 1990s and the housing bubbles in the past decade.

WHAT DO BUBBLES LOOK LIKE?

Not surprisingly, there are a number of great frameworks for thinking about this problem.

In 2011, Steve Blank and Ben Horowitz debated in The Economist whether or not technology was in a new bubble. In those posts, Steve cited the research of Jean-Paul Rodrigue denoting four phases of a bubble: stealth, awareness, mania and blow-off.

bubble chart

(Source: Wikipedia)

HOW DO BUBBLES HAPPEN?

In 2000, Edward Chancellor published an excellent history and analysis of market bubbles over four centuries and a wide variety of countries called “Devil Take the Hindmost: A History of Financial Speculation.” In his book, he finds at least two consistent ingredients.

  • Uncertainty. In almost every bubble, there seems to be some form of innovation or insight that forces people to rapidly debate the creation of new economic value. (Yes, even tulip bulbs were once an innovation, and the product was incredibly unpredictable.) This uncertainty is typically compounded by some form of lottery effect, exacerbating early pay-offs for the first actors. Think back to stories about buying a condo in Las Vegas and flipping it in months for amazing gains. This creates the inevitable upside/downside imbalance that Henry Blodget recently framed as: “If you lose your bet, you lose 100%. If you win your bet, you make 1000%.” Inevitably, this innovation always leads to a shockingly large assessment of how much value could be created by this market.
  • Leverage/Liquidity. In every bubble, there is some form of financial innovation that broadly increases both leverage and liquidity. This is critical, because the expansion of leverage not only provides massive liquidity to fund the expansion of the bubble, but the leverage also sets up the covenants that inevitably unwind when the bubble turns aggressively to the downside. In some ways, it’s also inevitable. When a large number of people believe they’ve found a sure thing, logic dictates they should borrow cheap money to maximize their returns. In fact, the belief it may be a bubble can make them even greedier to lever up their investment so they can “cash out” the most before the inevitable break.

BEHAVIORAL FINANCE LESSONS IN BUBBLES

Bubbles clearly have an emotional component, and to paraphrase Dan Ariely, humans may be irrational, but they are predictably irrational.

There are five obvious attributes of components of bubble psychology that play into market manias:

  1. Anchoring. We hear a number, and when asked a value-based question, even unrelated to the number, they gravitate to the value that was suggested. We hear gold at $1,500, and immediately in the aggregate we start thinking that $1,000 is cheap and $2,000 might be expensive.
  2. Hindsight Bias. We overestimate our ability to predict the future based on the recent past. We tend to over-emphasize recent performance in our thinking. We see a short-term trend in Bitcoin, and we extend that forward in the future with higher confidence than the data would mathematically support.
  3. Confirmation Bias. We selectively seek information that supports existing theories, and we ignore/dispute information that disproves those theories. (This also tends to explain most political issue blogs and comment threads.)
  4. Herd Behavior. We are biologically wired to mimic the actions of the larger group. While this behavior allows us to quickly absorb and react based on the intelligence of others around us, it also can lead to self-reinforcing cycles of aggregate behavior.
  5. Overconfidence. We tend to over-estimate our intelligence and capabilities relative to others. Seventy-four percent of professional fund managers in the 2006 study “Behaving Badly”believed they had delivered above-average job performance.

The greater fool theory posits that rational people will buy into valuations that they don’t necessarily believe, as long as they believe there is someone else more foolish who will buy it for an even higher value. The human tendencies described above lead to a fairly predictable outcome: After an innovation is introduced and a market is formed, people believe both that they are among the few who have spotted the trend early, and that they will be smart enough to pull out at the right time.

Ironically, the combination of these traits predictably leads to these four words: “It’s different this time.”

IT’S DIFFERENT THIS TIME

After two massive bubbles in the U.S. in less than a decade, many people question spotting bubbles ahead of time is so difficult. In every bubble, a number of people do correctly identify the bubble. As in the story of the boy who cried wolf, however, the truth is apt to be disbelieved. The problem is that in every market, there are always people claiming that prices are too high. That’s what makes a market. As a result, the cry of “bubble” is far more often proven wrong than right.

Every potential bubble, however, provides an incredibly valuable frame for deepening and debating the role of human psychology in financial markets. Honestly and thoughtfully examining your own behavior through a bubble, and comparing it to the insights provided by behavioral finance, can be one of the most valuable tools an investor has to learning about themselves.

Apple & Dow 15000: Update

In February 2012, I wrote a blog post that indicted the Dow Jones Industrial Average for including Cisco in 2009 instead of Apple.  At the time, Apple had just crossed $500 per share, and that simple decision had cost the US the psychology of an index hitting new highs.

I was driving home on Sunday, listening to the radio, and it occurred to me how different the financial news would be if Apple ($AAPL) was in the Dow Jones Industrial Average (^DJI).

Of course, being who I am, I went home and built a spreadsheet to recalculate what would have happened if Dow Jones had decided to add Apple to the index instead of Cisco back in 2009.  Imagine my surprise to see that the Dow be over 2000 points higher.

Update: AAPL at $700

With the launch of the iPhone 5, we find ourselves roughly 7 months later.  For fun, I re-ran the spreadsheet that calculated what the DJIA would be at if they had added AAPL to the index in 2009 instead of CSCO. (To date, I’ve never seen an explanation on why Cisco was selected to represent computer hardware instead of Apple.)

Result: Dow 16,600

As of September 17, 2012, AAPL closed at 699.781/share.  As it turns out, if Dow Jones had added Apple instead of Cisco in 2009, the index would now be at 16,617.82.  Hard to think that hitting all new highs wouldn’t be material for market psychology and the election.

Anyone up for Dow 20,000?

Apple, Cisco, and Dow 15000

I was driving home on Sunday, listening to the radio, and it occurred to me how different the financial news would be if Apple ($AAPL) was in the Dow Jones Industrial Average (^DJI).

Of course, being who I am, I went home and built a spreadsheet to recalculate what would have happened if Dow Jones had decided to add Apple to the index instead of Cisco back in 2009.  Imagine my surprise to see that the Dow be over 2000 points higher.

In real life, the Dow closed at 12,874.04 on Feb 13, 2012.  However, if they had added Apple instead of Cisco, the Dow Jones would be at 14,926.95.  That’s over 800 points higher than the all-time high of 14,164 previously set on 4/7/2008.

Can you imagine what the daily financial news of this country would be if every day the Dow Jones was hitting an all-time high?  How would it change the tone of our politics? Would we all be counting the moments to Dow 15,000?

Why Cisco vs. Apple?

This isn’t a foolhardy exercise.  The Dow Jones Industrial Average is changed very rarely, in order to promote stability and comparability in the index.  However, on June 8, 2009, they made two changes to the index:

  • They replaced Citigroup with Travelers
  • They replaced General Motors with Cisco

The question I explored was simple – what would have happened if they had replaced General Motors with Apple on June 8, 2009.  After all, Apple was up over 80% off its lows post-crash.  The company had a large, but not overwhelming market capitalization.  The index is already filled with “big iron” tech stocks, like Intel, HP & IBM.  Why add Cisco?  Why not add a consumer tech name instead?

In fact, there is no readily obvious justification for adding Cisco to the index in 2009 instead of Apple.

The Basics of the Dow Jones Industrial Average

Look, I’m just going to say it. The Dow Jones Industrial Average is ridiculous.

You may not realize this, but the Dow Jones Industrial Average, the “Dow” that everyone quotes as representative of the US stock market, and sometimes even a barometer of the US economy, is a mathematical farce.

Just thirty stocks, hand picked by committee by Dow Jones, with no rigorous requirements.  Worse, it’s a “price-weighted” index, which is mathematically nonsensical.  When calculating the Dow Jones Industrial Average, they take the actual stock prices of each stock, add them together, and divide them by a “Dow Divisor“.  They don’t take into account how many shares outstanding; they don’t assess the market capitalization of each company.  When a stock splits, they actually change the divisor for the whole index.  It’s completely unclear what this index is designed to measure, other than financial illiteracy.

In fact, there is only one justification for the Dow Jones Industrial Average being calculated this way.  Dow Jones explains it in this post on why Apple & Google are not included in the index.  To save you some time, I’ll summarize: they have always done it this way, and if they change it, then they won’t be able to compare today’s nonsensical index to the nonsensical index from the last 100+ years.

So what? Does it really matter?

It’s a fair critique.  Look, with 20/20 hindsight, there are limitless number of changes we could make to the index to change its value.  Imagine adding Microsoft and Intel to the index in 1991 instead of 1999?

I don’t think this exercise is that trivial in this case.  The Dow already decided to make a change in 2009.  They decided to replace a manufacturing company (GM) with a large hardware technology company (CSCO).  They could have easily picked Apple instead.

The end result?  People talk about the stock market still being “significantly off its highs” of 2008.  In truth, no one should be reporting the value of the Dow Jones Industrial Average.  But they do, and therefore it matters.  As a result, the choices of the Dow Jones committee matter, and unfortunately, there seems to be no accountability for those choices.

Appendix: The Numbers

I’ve provided below the actual tables used for my calculations.  Please note that all security prices are calculated as of market close on Monday, Feb 13, 2012.  The new Dow Divisor for the alternate reality with AAPL in the index was calculated by recalculating the appropriate Dow Divisor for the 6/8/2009 switch of AAPL for CSCO, and a recalculated adjustment for the VZ spinoff on 7/2/2010.

Real DJIA DJIA w/ AAPL on 6/8/09
Company 2/13/2012 Company 2/13/2012
MMM 88.03 MMM 88.03
AA 10.33 AA 10.33
AXP 52.07 AXP 52.07
T 30.04 T 30.04
BAC 8.25 BAC 8.25
BA 74.85 BA 74.85
CAT 113.70 CAT 113.70
CVX 106.38 CVX 106.38
CSCO 20.03 AAPL 502.60
KO 68.44 KO 68.44
DD 50.60 DD 50.60
XOM 84.42 XOM 84.42
GE 19.07 GE 19.07
HPQ 28.75 HPQ 28.75
HD 45.93 HD 45.93
INTC 26.70 INTC 26.70
IBM 192.62 IBM 192.62
JNJ 64.68 JNJ 64.68
JPM 38.30 JPM 38.30
KFT 38.40 KFT 38.40
MCD 99.65 MCD 99.65
MRK 38.11 MRK 38.11
MSFT 30.58 MSFT 30.58
PFE 21.30 PFE 21.30
PG 64.23 PG 64.23
TRV 58.99 TRV 58.99
UTX 84.88 UTX 84.88
VZ 38.13 VZ 38.13
WMT 61.79 WMT 61.79
DIS 41.79 DIS 41.79
Total 1701.04 Total 2183.61
Divisor 0.13212949 Divisor 0.146286415
Index 12874.04 Index 14926.95

Calculating the “alternate divisor” requires getting the daily stock quotes for the days where the index changed, and recalculating to make sure that the new divisor with the new stocks gives the same price for the day. It’s a bit messy, and depends on public quote data, so please feel free to check my math if I made a mistake.

The Game Mechanics of Silicon Valley Careers

Regular readers of this blog know that I’ve been a huge fan of game mechanics for years.  Game mechanics is a loose term for a variety of insights into the neurological and sociological underpinnings of the games that humans like to play.  In the past decade, there has been a massive growth in our understanding of game mechanics, even to the point now where you can’t go 10 feet in the Valley without tripping over a venture capitalist dropping the term in conversation.

This past weekend, I had the chance to chat with an old friend from a former start-up, and I was talking about why I love Zynga, and why game mechanics were one of the more interesting product insights to come out the last few years of product design.  The conversation moved on to catching up on old friends and careers, and the obvious hit me: our very careers in Silicon Valley are based on game mechanics.

Primal Response Patterns: Schedules of Reinforcement

In Amy Jo Kim’s lecture, Putting the Fun in Functional, she outlines some of the basic neurological drivers for response patterns to reward.

I’m going to grotesquely simplify the concept for the purposes of this post.  Real students of psychology & neurobiology – hold your nose while you go through this section.

It turns out that there are demonstrated patterns for response (neé addiction) for different types of reward systems:

  • Simple: You hit the lever, you get a treat.  Most animals will understand and play this game. (Hello, Pavlov)
  • Variable Interval: You hit the lever, but sometimes you get a treat, sometimes not.  This game turns out to be even more addictive, likely due to the combination of uncertainty (triggers fight-or-flight) and then the rush of the intermittent reward when it comes. (When you go to puppy school, you learn to *not* give your dog a treat every single time they do something right.)
  • Variable Interval, Variable Payout.  The most addictive of games.  You hit the lever, and sometimes you get a treat, and sometimes you don’t.  But sometimes the treat is big, and sometimes the treat is small.  (Hello, slot machine)

I was explaining this fact to my friend, when it occurred to me that this is the game that we all play in Silicon Valley.

Addiction: Hypergrowth Tech Companies

This pattern explains a lot about why Silicon Valley is so… addicting.  Venture capitalists invest capital into startups seeking outstanding returns.  Most engineers, on the other hand, invest their human capital to get the same result.  Engineers join hypergrowth companies with the assumption of receiving an equity stake.  That equity stake is the difference between making a good salary, and potentially hitting a step-function in their net worth.

Let’s play out the reward pattern:

  • Variable Interval: Tenure at tech companies can be anywhere from a few months to a few decades, however it averages about 2-3 years.  Sometimes startups go bankrupt less than 2 years after you join or found them.  Sometimes they get acquired.  Sometimes they become truly large, successful ongoing companies.  The timing definitely varies.  Many people would count themselves lucky if one in three of the companies they join turns out to be successful at a level that provides a meaningful value for their equity.
  • Variable Payout: Sometimes tech companies go bankrupt.  Other times they can produce equity worth 2x your salary.  Sometimes 10x.  Sometimes 100x+.

The lever is joining, and the payout is equity.

Is it any wonder that, after three decades, we’re all still addicted to this game?

 

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