LinkedIn Recommendations & The Reputation Economy

Last Friday, I had a chance to write a good, solid piece about LinkedIn Recommendations for the official LinkedIn blog.  In case you missed it, the article is here:

LinkedIn Blog: LinkedIn Recommendations & The Reputation Economy

I spent a good bit of time on this post, and even took a half hour to discuss some of the fundamental driving concepts behind it with Reid Hoffman, to help stitch together my thoughts with some of the underlying premises behind LinkedIn.  I’m pretty happy with the result.

Here’s a quick snippet:

Whether or not we realize it, we all live and work in a networked world.  Reputations matter.  Relationships matter.  Information is bombarding us from a rapidly swelling variety of sources, with increasing frequency and variability in terms of quality.  Interestingly, people are managing this incredible increase in complexity with habits and business practices that date back decades, if not centuries.

They consider the source.  They consider the context.

Fortunately, in the 21st century, with the birth of the social web, we have tools at our disposal that are orders of magnitude more powerful than we have ever had as individuals or as a society.  To quote David Weinberger from his recent talk at PDF09, Transparency is the New Objectivity:

What we used to believe because we thought the author was objective we now believe because we can see through the author’s writings to the sources and values that brought her to that position. Transparency gives the reader information by which she can undo some of the unintended effects of the ever-present biases. Transparency brings us to reliability the way objectivity used to.

This change is, well, epochal.

David is talking about journalism, but his insights are at the heart of why LinkedIn is such a powerful concept.  On LinkedIn, the skills that you’ve spent your career obtaining, the experience that you’ve earned, the trusted relationships that you’ve formed – they are all made largely transparent.  Your professional reputation and relationships matter – and not just to you.  That value extends far beyond your profile itself – it carries over to every interaction, every message, and every piece of contributed content.

It’s always rewarding when you write a post like this to get positive feedback.  Here is a flattering quote from Neal Schaffer:

I think the most brilliant blog post to come out of reaction to Jeremiah’s is the one on the official LinkedIn Blog entitled “Recommendations and the Reputation Economy” and written by LinkedIn’s own Product Director Adam Nash.  He went further to talk about how transparency is the new objectivity and that not only are recommendations often mutual, but that requesting recommendations is absolutely normal.  In fact, he ends his post asking you to write three recommendations for people unsolicited.  Exactly!  That line could have been taken out of my upcoming book!

Normally I don’t flag every post I make to the corporate blog here on my personal site, but if you’re interested, do check out the piece.

How Virtual Goods Caused the Market Crash of 2016

No, that’s not a typo.  I have seen the future.  And in the future, a burgeoning virtual goods economy that has been building over the past few years will lead to the next great financial bubble and crash.

Far-fetched?  Read on.

In some ways, virtual goods are almost as old as role-playing games.  Experience and special weapons are time consuming to earn, so a light grey market to “cheat” by purchasing equipment or characters has always existed.

This ecosystem exploded with popularity of massively multiplayer games, like World of Warcraft, and virtual worlds, like Second Life.  For the first time, cottage industries of real human beings sprang up to devote full time effort to investing time and resources into accumulating virtual wealth.

While typical Silicon Valley chit-chat turned to the impressive revenues that virtual goods firms began generating in 2008 & 2009, it wasn’t until Zynga IPO’ed in 2010 with eye-popping revenues of more than a quarter billion real dollars that the concept of virtual economies really became mainstream.  Major players from across the entertainment and technology domains raced to enter the market, and to leverage the powerful virality of social platforms combined with the fundamental addictiveness of gaming, reading a comprehensive buying guide every time you buy a gaming monitor is really important.  Add the final magic ingredient – pure monetary greed, and you had all the animal spirits needed to create the great virtual goods boom.

Unfortunately, as described in Devil Take the Hindmost, almost all great booms and busts are created through a combination of financial innovation in products that create leverage combined with a technology innovation that drives wildly optimistic views of future value.

Virtual goods and virtual economies had all the right elements to boom.  Initially, the conversion from real world stores of value into virtual stores was highly controlled.  Some of these economies allowed for the transfer of goods and virtual wealth, and some didn’t.  Quickly, however, competition forced a basic truth – people like obtaining virtual wealth in the form of virtual goods.   They like seeing that value multiply and grow.  More and more innovative services and economies were built, and increasingly they enabled mechanisms to convert those virtual stores of value into other virtual stores.  They also enabled players to compound their virtual wealth.  In fact, some even enabled the conversion back into real money.

Thus the vicious cycle was born.  Converting real money into virtual goods, and then taking advantage of the ability to compound that virtual value at unrealistic rates, set off a true boom.  The rate of return on virtual investments was so high compared to the anemic returns offered by the still moribund real economy, that early adopters looked like geniuses.  In 2014, the meme began to spread that everyone should have a portion of their portfolio allocated to “virtual assets”, which were not highly correlated to traditional stores of value.   Funds sprang up to allow the average individual without the time or inclination to invest and build virtual wealth to access the market.

The companies providing these ecosystems had no reason to dampen this enthusiasm.  Their systems, like those of investment bankers or market makers of yore, ensured a percentage of all transactions as revenues.   They made money as people converted real currency to virtual currency, and technically, as they converted it back.  Like central bankers with no fear of inflation, they juiced their economies to juice their own revenues.  Fortunately, the higher the internal rates of return in the virtual worlds, the less people were incented to take their virtual goods out and convert to real money.  Everyone effectively let their money ride, watching their virtual wealth grow.

By 2015, the notional value of virtual goods exceeded $1 Trillion for the first time.  Government bureaucrats began to explore the possibility of taxing these virtual economies to help cover increasing deficits.  Lobby groups sprang up to protect this “new economy” from destruction.  Pundits debated this nightly on all major cable networks.  People borrowed real money at relatively low rates in the real world to invest in virtual goods, because the returns were so much higher.  Real debt grew, savings dropped, but virtual assets grew faster.

Then, in 2016, one of the more flagrant virtual worlds began to see withdrawals rise.  Not significantly at first, but it turned out they had allowed virtual wealth of their members to grow high enough that people began to “retire”.  Everyone was in the game, so new entrants with smaller balances could match the asset loss.  Suddenly, the bear arguments, which had been discussed for years (beginning with a famous blog post from 2009) began to make more sense.

No one had the real money to cover these virtual “liabilities” the companies implicitly had to their members.  There was no virtual FDIC to cover accounts.  There was no regulation to ensure that these accounts would be paid.  The first “run” on a virtual economy had begun.

Suddenly, it became clear that these virtual economies were linked, even if owned by different giant companies.  People who lost money in one virtual economy, began pulling real money out of others.  One virtual world froze conversion, like a panicked 20th century third world nation.  Then the run really began.

Virtual asset values plummeted.  But the real debts did not.  Suddenly it turned out that more companies had their fingers in the virtual pie than most people thought.  Asset management firms.  Insurance firms.  Hedge funds.  Large banks.  Tech giants.

And that’s how virtual goods caused the market crash of 2016.

Do I believe that it will really happen?  No.  Do I believe that conceptually, virtual goods and economies could lead us into uncharted waters economically if we are not careful?  Yes.

I’ve read quite a bit in the past decade about the history of market bubbles and panics, and the patterns of each.  In every case, financial innovation creates some new way for people to assume liabilities in a highly leveraged way, outside of existing regulation or norms.  In combination, some technology offers the world hope of a much larger economic future.  Given the new found ability to invest heavily in that future, and radically different perceptions of that future, people invest, creating a virtuous cycle of high returns and increased investment that sucks almost all the air out of the system… and then keels over.

A fun mental exercise for a Thursday night.

Still I wonder. Since it’s only 2009, I feel like I don’t own enough stock in these companies.  It’s going to be quite a ride.  🙂

LinkedIn for IBM Lotus Notes is Live

Kudos to the team.  LinkedIn for IBM Lotus Notes is now in beta.

LinkedIn Blog: LinkedIn Widget for IBM Lotus Notes Now Available

Quote from Ed Brill, Director of Product for Lotus Notes at IBM:

This week, IBM and LinkedIn are announcing the availability of the LinkedIn plug-in for Lotus Notes.  This easy to use add-in dynamically displays LinkedIn profile, status, and other information in the Notes 8 sidebar.  The new plug-in is a great example of “contextual collaboration” — where users access relevant information without having to leave behind what they are already working on.

Special kudos to the LinkedIn LED Team, and to Elliot Shmukler for this big win.

In fact, the only thing I find a tad disappointing is the lack of a new Elliot blooper reel for this launch.  As a consolation, I’ll link to the old one from 2008 here.

Embrace the Minimum Necessary Change (MNC)

In keeping with my theme this week of blogging observations, this one ties together a basic tenet that I learned from science fiction in my pre-teen years, and applies it to product management.

The concept is borrowed from “The End of Eternity“, one of the classic science fiction novels from Isaac Asimov.  The book imagines a future with time travel, and the guidelines that govern its use:

There is a group of people (only males) who are called The Eternals. They live outside of ordinary time and space in a man-made construct called Eternity. The Eternals can move back and forth between Eternity and Earth, entering into any time period of Earth’s history. Their mission is to make Reality Changes, changes in the course of human history that will result in an improved Reality. They try to do this with the help of computers that can predict how even subtle changes will alter Reality. There is an art to finding the minimal intervention that will result in a desired Reality Change. There is a special change called “The Minimum Necessary Change“.

I’ve been surprised over the years how often I find myself using this concept, the “minimum necessary change”, to help frame potential solutions to problems.

In some ways, it’s a fairly obvious outcome of a scientific education.  Occam’s razor demands that, all things being equal, we bias towards the simplest explanation.  It’s not a far stretch to morph that concept into a bias towards the simplest solution to a given problem.

Seasoned product managers are also familiar with another, related concept, the “minimally viable product”.  The MVP, of course, is the minimal number of features necessary for a product to be successful at achieving it’s business & product goals.

Today, at LinkedIn, I was in a fairly intense meeting discussing potential solutions for a product that we’re trying to roll out in the next few weeks.  A fairly significant issue has arisen, and the team has been debating solutions.

It’s very easy for product managers and engineers to sometimes get caught up in “redesign fever”.  An unexpected issue or constraint arises that wasn’t expected.  Immediately, smart people will retrace their steps back to the beginning, and imagine a radical new design for their product that incorporates that new issue.  The problem is, there are always new issues.  There are always unexpected constraints.  Redesign fever can and will prevent products from converging, and prevent teams from shipping.

I’ve found that the best way to resolve these types of issues is to clearly define the problem, brainstorm potential solutions, and then way the pros/cons of each.  Not rocket science.

However, make sure as part of the exercise that the “Minimum Necessary Change” is one of the solutions that is part of the decision set.  It helps frame the costs (and benefits) of more elaborate solutions.  In fact, the intellectual pleasure of finding a simple, elegant solution to a complex problem can turn into a highlight for the entire project.

If you believe in fast iteration, in shipping product quickly and frequently to incorporate real user feedback into your designs, then more often than not you’ll find that the Minimum Necessary Change is your friend.

Guide to Product Planning: Three Feature Buckets

In the spirit of capturing some of the observations that I find myself repeating, I’m adding this one to the mix tonight.  Unlike the previous two, this is really a piece of concrete advice for product managers of consumer software or consumer internet products.  It’s also a more recent observation that I’ve formulated in the past few years.

This advice takes the form of a simple classification framework for the features that you are considering for a product, whether it’s a single “large scale” launch, or a series of product features that are planned out on a roadmap.

Place your feature concepts in one of three buckets:

  • Metrics Movers. These are features that will move your target business & product metrics significantly.  In most healthy product organizations, there are specific goals and strategies behind the decision to invest in a product or feature.  Engagement.  Growth.  Revenue.  Typically, very few features are actually metrics movers.  Know which ones they are ahead of time, because in the end, the judgment of whether your product or roadmap succeeded or failed will rest on the evaluation of the metrics.
  • Customer Requests. These are features that your customers are actively requesting.  There is no mystery here.  Listen to your customers, and know which features they want to see the most.  You don’t necessarily want to implement every suggestion, but product professionals need to listen to direct requests carefully, with humility and deep consideration.  Nothing irritates customer more that to see you roll out new features that exclude the ones that they have already identified and requested actively.
  • Customer Delight. These are features that customers haven’t necessarily asked for, but literally delight them when they see them.  Typically these are features that require several ingredients: listening to customers to understand their pain points, leveraging a knowledge of technology to know what might be possible, and innovative design to come up with an unexpectedly elegant & delightful experience.

Don’t get me wrong – there are some features that can fall in more than one bucket, but it’s a rare feature that actually falls in all three.

I’ve found that categorizing features into these buckets forces product teams to be intellectually honest with why they are implementing a certain feature.  Is it because customers want it?  Or is it because the company wants it (to move metrics)?  Or is it just cool?

For large, monolithic releases of features, optimal success comes from packaging up items from each of these buckets.  The customer requests ensure that your customers see that the time that they are investing in your products is rewarded by a provider who listens and delivers.  Your metrics movers ensure that the business and strategy you are executing on will provide the resources to invest in future iterations.  And your customer delight features highlight your ability to leverage expertise in technology & design to deliver innovative capabilities.

Conversely, if you find yourself without one of these buckets represented, it likely represents a serious hole in either your channels for customer feedback, your product execution, or your innovation capabilities.  These holes will significantly impact both your short term and long term success in this area.

Most consumer internet companies don’t ship monolithic feature redesigns often – instead they release small iterations and additions frequently.  (At LinkedIn, we release every week.)  The logic above, however, can just as easily apply to a series of 1-2 week features executed over the course of a three month roadmap as a large monolithic release.

Take a moment and consider major product releases in the consumer space that you really respect as a product professional.  I think you’ll find that these releases have all three of these buckets well represented.  (iPhone 3.0 is not a bad recent example.)

Observations: The Paradox of Being a “Smart” Venture Capitalist

My last post, and observation of business & government students, was popular enough that I think I’ll share a second one here.   This is an observation that I’ve shared with a large number of people in the past seven years, as part of my greater set of take-aways on working in venture capital.

I worked for Atlas Venture from 2001-2002 as an Associate, and during that time I had the chance to observe quite a the interesting paradoxes that make up success in early-stage venture capital.  This particular observation is about the paradox surrounding being seen as “smart”.

In the short term, venture capitalists often look smart by saying “No”.  But in the long term, venture capitalists can only look smart by saying “Yes”.

This applies generally to new people joining the industry, regardless of level.  New associate, venture partner, general partner.  Venture capitalists deal with exceptionally long cycles.  It takes the better part of a decade to build most businesses, and it can take that long to really determine who in venture capital is doing the job, and who is just playing the part.

In the long term, the metric is simple: how many successful entrepreneurs & companies did the venture capitalist fund & help build to extraordinary outcomes.

In the short term, people are desperate for any tangible signal that will predict the long term.   Unfortunately, in many cases, the short hand for this becomes evaluating their critical thinking about risks and issues on every pitch.

As a product leader, I see this behavior play out on a regular basis outside of venture capital as well.  More experienced product managers will review the work of junior product managers, and will prove their capabilities by highlighting problems.

They don’t realize that they will never be great by pointing out flaws.  They will be great by translating that knowledge into solutions for other people’s products, as well as leading their own innovative initiatives.

I could always tell when a general partner, whether at Atlas or another firm, was “ready to fund”.  You would see their posture in meeting shift radically from finding ways to say no to finding ways to say yes.

Not surprisingly, my fondest memories of venture capital surround the start-ups where I said yes.

Observations: MBAs & Government

Sometimes I am reminded that there are a lot of observations & stories that I tell in real life that I haven’t shared on this blog.  This is one that I’ve mentioned in conversation three times this week, so I’m making an effort to actually write it out.

When I attend business school at Harvard, I took a couple of elective classes that were roughly equally populated by both MBA students and Government students.  Harvard is fairly unique in that it has both a world-class business school (technically, the oldest) and a world-class government school (Kennedy School of Government).

What I learned in these classes had less to do with the material, and more to do with the fundamental difference in mindset between the two types of students.

In every class, for every business case, the argument almost always broke down as follows:

The MBA Students:

Tell us what the rules of the game are, and we’ll tell you how to win the game.

The Government Students:

Tell us who you want to win the game, and we’ll tell you how to make the rules.

Needless to say, the conversations typically went nowhere.  The business students always felt it was unethical to either change the rules mid-stream, or to create an unlevel playing field.  The government students always felt it was unethical to set up rules that weren’t destined to generate the ideal outcome.

Let me know how many times you see echoes of this disconnect in both business &  political discussions.