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The Sharing Economy: The End of the Summer of Love

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The Summer of Love – early 1967, to be precise – was a high point in 60s-era ideology, when reality seemed to match the hype. Shortly after, things began to fall apart. 1967 was also the summer of riots in Newark, Detroit and 126 other US cities. Drugs and violence popped up.

By late 1969, the Altamont Festival heralded an end to the 60s; but the seeds were sown well before.

The Sharing Economy Summer of Love

The high priestesses of the sharing economy – Lisa Gansky and Rachel Botsman – were early promoters, long on utopian idealism. They spoke about trust, and about transforming business, consumerism, and the way people related to each other. And there’s still a lot to like about that story.

It’s all based on vastly under-utilized resources. How often do you use your video camera, anyway? Your bicycle? Table saw? Your car? Your apartment? What if there were a way other people could use them, and you could get paid for that use? And, amazingly, there were apps for that.  Lots and lots of apps. And so the “sharing economy” got its name.

With karma and economics moving in parallel, what could possibly go wrong?

Disintermediation by Any Other Name…

The sharing economy was originally rooted in peer to peer sharing. But we temporarily forget there are two kinds of peer-to-peer situations.

In Type A, mi camera es su camera (or gardening tool, or bicycle, etc.), all through the miracle of an app that connects us – peer to peer. Directly. No intermediary, no middleman.  Works great, and we don’t mind paying the app-producer a bit, or even more than a bit, for arranging and facilitating the serendipity.

Of course, there was that pesky issue of trust.  But in fairness, outfits like eBay figured that one out to a great extent – reputation, track records, public shaming. And it works pretty well.

It worked well enough that we could vacation on AirBnB at half the price – partly because the owners didn’t have to deal with irksome regulations and taxes on hotels. Ditto rides on Uber and Lyft – who needs all that regulation, and taxes, and for that matter all those lazy taxi drivers waiting in queues.

But then another Fact of Life showed up. In this day and age of Thomas Picketty’s best-selling book Capital, we have re-learned the word for an important phenomenon: it is, indeed, capital.  When the peer supply of the good in question falls short of the peer demand of the good in question, capital emerges to fill the gap. These are Type B peer situations – where intermediaries, or middleman, have a role to play. In e-babble, it’s called scaling.

Type B works like this. Not everyone has a spare apartment to rent out when they’re on vacation; maybe because they hardly ever go on vacation, or maybe because their condo in central Pennsylvania doesn’t sound all that attractive in February anyway.

Not everyone has a car with a backseat you’d want to ride in, much less the time to drive around waiting for people to call their app.

The solution: The app-makers team up with capital-owners, integrate downstream into buying assets, then hire cheap labor to manage the pool. Buy a bunch of apartments; buy a bunch of cars. Hire freelance maids and drivers.

Suddenly, there are lots of people who own multiple apartments and rent them out as a business. Of course, they’re not in the hotel business, they’ll tell you, hence they shouldn’t be taxed by cities or subjected to safety or labor regulations.

What just happened? Maids just got disintermediated, and returns to capital just went up, while aggregate wages just went down.

If there aren’t already, there very shortly will be people who get the idea of hiring their neighbors to run the family car for hire in their own off hours; and maybe of buying a few more cars, for more neighbors. But don’t call it a taxi service, because those services are regulated and pay taxes.

What just happened? Taxi drivers just got distintermediated, and returns to capital just went up, while aggregate wages just went down.

With Uber sporting an implied $17B valuation, and AirBnB at $10B, don’t forget to ask yourself to whom these returns accrue. The answer is not you and your car, or you and your apartment. It’s capital.

Economic Change is Fast: Economic Justice Takes Longer

To be clear, there’s nothing immoral going on here. Nor is this anything economically unique (though it may be dysfunctional).  The legal and regulatory status of these new capital intensive businesses is under review through the normal legal and regulatory channels, and will proceed quickly; see, for example, the insurance industry is taking aim at Uber and Lyft.

But let’s be clear – this is not the second coming of peace, love and understanding. While there are lots of small-scale apps and programs that link peers directly to peers, the big money, as always, will be found where capital joins labor. Where there’s room to scale, you will find capital. That’s precisely the case in Big Businesses like transportation and lodging.

And while capital owners in big scale businesses are delighted to continue the “little guy against the corporation” myth, in truth it’s nothing more than another round of disintermediation. It’s important to note that while you may save a bit on a vacation room or a trip to the airport, there are also jobs at stake – jobs staffed by real people whose unions and representatives took decades to hammer out economic agreements with employers.

At the risk of grossly over-simplifying Picketty’s core dictum: absent world wars and a booming economy, capital grows faster than wages. This is a prime case in point. What looks like technological progress driving social integration with the lights dimmed down, looks a whole lot more like traditional disintermediation in the harsh light of day.

We do ourselves and society an injustice if we let new economy happy-talk blind us to the social effects of the same-old same-old economic shifts.

Trust is Not Reputation

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I trust my dog with my life – but not with my ham sandwich.

That is but one of dozens of humorous ways to indicate the multiple meanings we attach to the word “trust.” It’s remarkable how good we are at understanding the word in context, given its definitional complexity.

One interesting aspect of trust is its relationship to the concept of reputation. This issue is coming to the fore in the so-called “sharing economy” or “collaborative consumption” movement.

Who can you trust on the Internet to deliver the goods they said they would deliver (think eBay), to leave your apartment in good shape if you lease it on Airbnb, to not be a creep if you offer someone ride-sharing?

It’s tempting to look at the concept of reputation as the scalable, digital badge of trust that we might append to all kinds of transactions between strangers, rendering them all as trustworthy as your cousin. (Well, most cousins.)

Tempting, but not exactly right.  Because trust, it turns out, is not reputation.

Greenspan’s Folly

William K. Black has written about the dire consequences of Alan Greenspan confusing trust and reputation, saying:

Alan Greenspan touted ‘reputation’ as the characteristic that made possible trust and free markets. He was dead wrong.

Greenspan believed that Wall Streeters’ regard for their own reputation meant that markets were the best guarantor of trust – because they would perceive their own self-interest as aligned with being perceived as trustworthy.

Unfortunately, Greenspan’s belief was probably based more in ideology than in history or psychology, as the passion for reputation was overwhelmed by the passion for filthy lucre, immortalized in the acronym IBGYBG (“I’ll be gone, you’ll be gone – let’s do the deal”).

Early Social Reputation Metrics

Think back, way back, to November, 2006.  A company called RapLeaf was on to something. Here’s how they described their goal:

Rapleaf is a portable ratings system for commerce. Buyers, sellers and swappers can rate one another—thereby encouraging more trust and honesty. We hope Rapleaf can make it more profitable to be ethical.

You can immediately see the appeal of a reputation-based trust rating system. And with a nano-second more of thought, you can see how such a system could be easily abused. (“Hey, Joey – let’s get on this thing, you stuff the ballot box for me, I stuff it for you, bada-boom.”)

Then there’s Edelman PR’s pioneering product, TweetLevel. It does one smart thing, which is to avoid a single definition of whatever-you-wanna-call it. Instead, it breaks your single TweetLevel score into four components: influence, popularity, engagement, and trust.

Edelman says:

having a high trust score is considered by many to be more important than any other category.  Trust can be measured by the number of times someone is happy to associate what you have said through them – in other words how often you are re-tweeted.

According to TweetLevel, here are my scores:

  •             Influence        73.4
  •             Popularity      70.1
  •             Engagement   56.4
  •             Trust               46.9

So much for my trustworthiness.

Guess who owns the number one trust score on TweetLevel: it’s Justin Bieber. Now you know who to call for – well, for something.

The KLOUT Effect

It’s easy to poke fun at metrics like TweetLevel that purport to measure trust; but in fairness, because trust is such a complex phenomenon, there really can be no one definition. What TweetLevel measures is indeed something – it’s not a random collection of data – and they have as much right to call it ‘trust’ as anyone else does. Indeed, I respect their decision to stay vague about what to call the composite metric.

KLOUT raises a more specific question: it directly claims to measure Influence, and is clear about its definition, at least at a high level:

The Klout Score measures influence [on a scale of 1 to 100] based on your ability to drive action. Every time you create content or engage you influence others. The Klout Score uses data from social networks in order to measure:

  • True Reach: How many people you influence
  • Amplification: How much you influence them
  • Network Impact: The influence of your network

I find that to be a coherent definition. If I’m a consumer marketer, I want to know who has high KLOUT scores in certain areas, because if they drive action, I want them driving my action.

Note that Klout doesn’t mention reputation at all – just influence. Where does trust come in?  Klout says, “Your customers don’t trust advertising, they trust their peers and influencers.”

Well, I wouldn’t go there. On TweetLevel, the top three influencers are Justin Bieber, Wyclef Jean, and Bella Thorne. Influencers – definitely. People to be trusted? What does that even mean?

Trust Metrics

One problem with linking trust to reputation is that it can be gamed. One problem with linking trust to influence is that notoriety and fame are cross-implicated. Bonny and Clyde were notorious, so was Bernie Madoff and the Notorious B.I.G. – that doesn’t make them trusted.

Take Kim Kardashian. Is she influential? You betcha: her Klout score is a whopping 92. Does she have a reputation? I bet her name recognition is higher than the President’s.

But – do you trust Kim Kardashian? Well, to do what? (By the way, TweetLevel gives her a 70.1 trust score – way higher than mine. Now you know who to ask when you need a trustworthy answer; I’m referring all queries to her).

So here are a few headlines on trust metrics.

  1. They’re contextual. You can’t say you trust someone without saying what you trust them for. I trust an eBay seller to sell me books, but I’m not going to trust him with my daughter’s phone number.
  2. They’re multi-layered. Both Klout and TweetLevel correctly recognize that social metrics can’t be monotonic – a single headline number is useful, but it had better have nuances and deconstructive capability.
  3. Behavior trumps reputation. You can get lots of people to stuff the ballot boxes for you; it’s a lot harder to fake your own  behavioral history. Trust metrics based more on what you did, rather than just on what people say about you, are more solid.
  4. Good definitions are key. When people say ‘trust’ and don’t distinguish between trusting and being trusted, they’re not being clear. There’s social trust, transactional trust – it goes on and on. Good metrics start by being very clear.

So what’s the link between reputation, influence, and trust? There is no final arbiter of that question. Language is an evolving anthropological thing, and as Humpty Dumpty said, words mean what we choose to say they mean. So job one is to be clear about our intended meanings.

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Full disclosure: I have a small interest in a sharing economy company, TrustCloud. I have written more about the sharing economy and collaborative consumption in a White Paper: Trust and the Sharing Economy, a New Business Model.

Trust and the Sharing Economy

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What if everyone could be trusted? And everyone became willing to trust?

Unrealistic? Sure, if you insist on all or nothing.

But if we moved directionally toward those goals, it’s not hard to envision significant improvement. Increased trustworthiness, and increased propensity to trust, would most likely lead to:

  • Fewer and simpler contracts
  • Fewer lawyers and lawsuits
  • Less transaction complexity
  • Lower insurance costs

This is not pie in the sky. There is an emerging part of the economy that does precisely this: it’s called the Sharing Economy, or Collaborative Consumption.

The Sharing Economy

The Sharing Economy is composed of assets which were previously owned by single entities (either persons or corporations), but which have been freed up to be used by many. Perhaps the best-known example of the concept is ZipCar.

In principle, the concept can apply to any asset used at less than its full capacity. That includes all manner of goods.  Airbnb has made a business of helping people rent out their homes. Couchsurfing is just what it sounds like.

This can sound like pure 20-something left coast social experimentation, but it’s also gotten the attention of General Motors. It’s not fundamentally different than when McDonalds figured out it could use its under-utilized real estate to serve breakfast.

In fact, the Sharing Economy is resurrecting some 19th century ideas like the Grange Movement that helped stimulate the Great Plains agricultural economy.

For that matter – remember libraries?

Trust: the Backbone of the Sharing Economy

The Sharing Economy is, pure and simple, about trusting strangers. How, in an age of global markets and internet-based communication, can we do that?  Or to make it more personal: what would it take for you to rent your house or apartment for a week to someone from France you met online?  And how, finally, can you make that answer scalable?

That, it turns out, is one of the fascinating aspects of the Sharing Economy.  It doesn’t make sense for each sharing business model to develop its own proprietary database, any more than it makes sense for every mortgage lender to develop its own creditworthiness database.

Hence, the race is on to determine who will develop the FICO score of trustworthiness, the most dependable metric, the database that will provide the underpinnings of a potentially considerable amount of economic activity.

Trust Metrics

I have written a White Paper on this subject: Trust and the Sharing Economy: A New Business Model. [I should add here – full disclosure – I am an advisor to and have a financial interest in one of those players, TrustCloud.]

The Sharing Economy is a microcosm for observing trust concepts I’ve been writing about for years. For example:

  1. Trusting vs. being trusted: If you have an apartment you’d like to rent out, you are the one doing most of the trusting; your question is about potential renters – are they trustworthy? So often missing in general discussions of trust (“trust in banking is down…”), the distinction is obvious and vital here.  What’s needed is trustworthiness ratings of the potential renters.
  2. Reputation vs. trustworthiness: It’s easy to mistake reputation for trustworthiness, and some previous online trust metrics have done so. The result is data that suggest Perez Hilton and Justin Bieber lead the pack in trustworthiness.  Does not compute.
  3. Trust comes in several flavors, and is all about context. Unlike digital recordings, some forms of trust don’t travel well (remember the game of “telephone?”). Or as I’m fond of saying, I trust my dog with my life – but not with my ham sandwich.

In the race to build trust metrics, it’s tempting to over-emphasize the technical aspects of the problem. But in the case of trust (as with knowledge management), the more important problem to solve is to correctly define trust and its indicators.

I’ll be writing more about this in future.

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Many Trusted Advisor programs now offer CPE credits.  Please call Tracey DelCamp for more information at 856-981-5268–or drop us a note @ [email protected].

For continued reading check out: Trust Is Not Reputation

Solving Knowledge Management with Speed Dating: Interview with Clay Hebert

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Most corporate discussions about knowledge management (KM) are about databases, software, and IT. One mid-sized law firm I know took a different approach – getting partners to interact over lunch. It was very effective.

It turns out the 1-to-1 nature of speed dating is perfect for mega-companies that want to improve KM.

That’s the kind of insight Clay Hebert has come up with. I met with him recently in his coffee-shop office so far on the West Side of Manhattan it might as well be in the Hudson. Here are excerpts.

Charlie: We’ll get to the speed-dating thing soon; but first, how’d you get to this point?

Clay: The quick story? I spent ten years at Accenture, a massive consulting company. Even though I was surrounded by smart, hard-working people, the work wasn’t stimulating. I was a “Mac” soul stuck in a “PC” company.

In January of 2009, I had my big break. My business hero Seth Godin offered a unique and exclusive MBA program, and I was accepted. There were more than 500 applicants and I was one of nine who were chosen. For six months, nine of us sat around a table in Seth’s office learning from the marketing master (and each other). It completely changed my life. After that, there’s no way I could go back to corporate America.

Now, I’m building a technology startup called Spindows.com – an enterprise video chat platform that will change the way organizations collaborate and share knowledge.

Sharing Knowledge

Charlie: I hear collaboration, I hear video-chat; I can infer speed-dating, I think. But tell me more.

Clay: After a decade at Accenture, I only knew about 100 colleagues, 1/20th of 1% of the company. This is astonishingly inefficient when you think about the skills and expertise that should be shared across the organization.

The single most valuable asset for most companies is the knowledge of its employees. Most companies understand this, but their current KM solutions consist of clunky file-shares and databases.

It’s a tremendous opportunity wasted.

Charlie: You’re right, it is an astonishing waste; every big company I know reverts to massive databases then worries about incentives to get people to load the data, or hires support staff to do it.  Lately, they’re all trying various social media. But it’s still kind of artificial, or time-consuming, or just not interesting.

So, what’s the answer?

Clay: Well, I’m hoping Spindows will be at least part of the answer.

There are three main problems with the current KM process:

    1. You need high quality information
    2. You need that information input into a system in a timely manner
    3. Other employees need to be able to find it.

In short, the KM process is broken due to quality, speed, and search. Here’s an example of each:

    1. Quality – Here’s a common KM scenario: the lowest level analyst or intern gets assigned the task of uploading project summary documents to a database or file-share. There is limited correlation between these often-insipid documents and the true learnings from the project. The KM process itself is treated like an administrative burden instead of a golden opportunity.
    2. Speed – This process often happens at the end of a long project. If anyone does find the information, it’s outdated at best. In our fast-paced world, knowledge transfer should happen in real-time, or close to it.
    3. Search – The search algorithms to find the knowledge are woefully inadequate. I recently heard that one big consulting firm actually outsourced these searches of their own KM systems to an outside vendor. Think about that for a second. The search algorithms are so bad that they pay a third party to help find their own internal information. Now that’s broken.

Spindows cures these three problems, through a video speed-networking platform where you rapidly meet relevant people in your own organization via a series of quick 1-on-1 video chats.

First, everyone fills out a user profile with simple attributes (tags) that describe their knowledge and skills as well as things like their title, industry and personal interests.

A Spindow is a completely new kind of meeting. Instead of inviting people, you invite these tags or attributes. Anyone matching these tags is invited to attend the session.

In the Spindow itself, the 1-to-1 video interactions are rapid and timed, say 4 minutes each, so at the end of a one-hour Spindow, you’ve met 15 relevant colleagues. By attending just one Spindow per week, over the course of a year, you can meet everyone in a 780 person division.

Spindows reduces friction and increases serendipity by being the easiest way to find and connect with relevant colleagues.

Charlie: Wow, very cool indeed! Where do you stand in terms of status? Have you gotten written up? Funded? Testing?

Clay: Spindows has received some great press from Business Insider, and excellent feedback from events like Startup Riot, Startup Camp, and Under 30 CEO’s startup pitch event, where we scored second place.

We’re thrilled. Right now we’re working with a minimum-viable product (MVP). It’s functional, and we’ve done some testing.

Going forward, we plan to invite a select group of early enterprise customers to try the product at discounted pricing. This is win-win because the early adopters will be allowed to take advantage of this great new technology before it’s available to the public. And it’s great for us because that early customer feedback will allow us to shape the product direction and roadmap.

Trust Works

Charlie: Let’s talk about why this makes so much sense. In my view, it’s allows super-high bandwidth – human interaction – in a socially acceptable casual wrapper. You can be ‘promiscuous’ with your interactions, and still get far deeper than if you just relied on databases and social media. You’re talking to real people. This has tons to do with trust.

Clay: Exactly. You’ve nailed it. I believe people will be more open and trustworthy when talking directly to their colleagues. We’re combining high bandwidth human interaction with big data and analytics. Companies will be able to track how many Spindows someone has participated in, who they have met and, who they still need to meet.

We’re working with PhD’s at Wharton to design valid tests to track how quickly the expertise tags are spreading throughout the organization, effectively proving that trust leads to better KM.

Charlie: Speaking of trust: you’re a heavy user of Airbnb, a Sharing Economy business whereby you rent out your apartment to others, and vice versa. Do you worry about people trashing your apartment? How do you prevent that?

Clay: It’s all about trust. Before they arrive, we establish a personal bond with the people who use our place. Before they come, we ask them what DVD’s they’d like us to get for them on Netflix. We leave a bottle of wine and neon Post-It notes all around the apartment encouraging them to drink the wine, read our books, surf the internet, etc.

We write notes to people on our white board and they always leave us notes when they leave, usually describing what they did on their trip. Airbnb is extremely safe in general, but these extra steps make the interaction inescapably, richly human.

Charlie: This is great social proof of “the best way to make someone trustworthy is to trust them.” Trustworthiness and trusting-ness are intertwined –

Clay: – You get what you give –

Charlie: – and each is both cause and effect.

Clay: – and you want to give what you get.

Charlie: Clay, no wonder you’re a leader in some of the new social media arenas. Next time we’ll talk about your experiences in some of the New York incubator labs for new technologies.

Clay: Can’t wait!