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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.

Blow Up Your Budgeting Process

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If you work in a large organization – This Blog’s for You.

You know what season is coming soon – you dread it. ‘Tis the season of Planning & Budgeting; the annual ritual of much time, many iterations, and little meaning – full of sound and fury, signifying not much.

What if you could radically revolutionize that process? Almost blow it up? All in a socially and politically acceptable manner, of course.

Resource Allocation is So Last Millennium

Planning and budgeting processes are about resource allocation. Partly that’s to coordinate plans. But partly it’s about predicting the future – of markets, the economy, technology – so we can intelligently place resource bets. So that we can plan on having umbrellas in case it rains.

We have built processes to worry about the future so that we can place resource bets in advance. But what if we didn’t have to place those bets in advance? Who cares about predicting rain for tomorrow if I know there will be an umbrella within arm’s reach when I need it?

What if you always had access to an umbrella? What if you did not have to make capital investments, hire and train people, develop new products – until the day before you needed to? And you were then able to do so with the snap of a finger?

You wouldn’t waste time predicting the future – you’d just deal with it on arrival. And increasingly, that’s what the world looks like.

The umbrellas, it turns out, are right within our grasp, right when we need them – if we just know to look for them. And there are three places to look.

The Three Sources of Umbrellas When You Want Them

Old style planning and budgeting assumes scarcity of resources – few umbrellas. We need to re-think; to recognize the umbrellas are already there, and we’re just facing a sourcing or distribution problem.

The three keys to changing that problem definition are speed, collaboration, and transparency.

Speed. You probably budget for headcount. If so, you assume a certain elapsed time for a category of employee – let’s say, a three-month cycle.

What if you could cut that to three weeks? To three days?  Think contracting, outsourcing, working virtually, across time zones, modularizing work. It’s the way software and movies and consulting and projects get done now, why not extend it to “core” hiring?

Speed attacks the need to plan for umbrellas, because it reduces your exposure to time-spent-without-umbrella.

Collaboration. You probably budget for facilities and equipment – because you assume you must own or have first call on assets. But what if you could get all the access you need just by sharing with others? And save tons of money at the same time?

After all, you rent a room at the Marriott in Chicago instead of owning a condo there. Push that thinking further; it’s like doubling your proven resource reserves without spending a penny on exploration.

Why own a car when you can use Zipcar? Why are you paying Microsoft for software to sit on your PC getting old when you can access cloud software, always updated, for less? Why are you buying books instead of renting them? Why are you spending money on dedicated office space when you could share it out with other tenants? Why are you driving alone?

Collaboration attacks the need to plan for umbrellas, because it changes a resource scarcity problem to a capacity utilization problem, while expanding perceived capacity.

Transparency. You probably budget for knowledge management and IP development – because you think your organization must carefully nurture its precious wisdom. But what if you could generate more knowledge, and more know-how, by openly sharing what you have with everyone else?

This is the logic behind meet-ups, networks, communities of interest, affiliate marketing, tribes, wikis, webinars, curating, mash-ups, and Spindows.

Transparency attacks the need to plan for umbrellas, because it sensitizes everyone to the presence of more umbrellas, to the availability of umbrella substitutes, and to rain-control initiatives.  

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Help free your organization from the tyranny of old-think resource-constrained planning and budgeting processes. Ask yourself how to get your group’s work done faster, more collaboratively, and more transparently.

This is how to be a socially and politically acceptable business revolutionary.

(Props to my mastermind group of @StewartMHirsch, Scott Parker and John Malitoris for this post) 

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