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Crime, Fear and Trust

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Most casual readers of the general press know three things: crime is up, public safety is down, and trust is declining.

The problem is: the first two are flat out wrong, and together they cast doubt on the third.

Crime and Fear

(The following data are compiled from the Atlantic, March 2015, Be Not Afraid).

Fear: In the US, Gallup annually asks if crime is up or down from the previous year. Every year, and usually by large amounts (73% vs 24% last year) the public says crime has risen.

Fact: Violent crime has declined by 70% since the early 1990s. The homicide rate has been cut in half, and three years ago hit the lowest level since 1963. Rape and sexual assault rates declined 60% from 1995 to 2010.

Fear: 58% of the public fears another US terrorist attack, down not much from one month after 9-11, when the number was 71%. The Chairman of the Joint Chiefs of Staff declared the world “more dangerous than it has ever been,” and that was two years ago and before ISIS.

Fact: Despite the horrific stories of ISIS, you’re four times more likely to drown in your bathtub than from a terrorist attack. Armed conflicts in the world are down 40% since the end of the Cold War.

And so on.

The point? Fear of crime and of danger are not necessarily linked to actual rates of crime and danger. In fact, myth is often negatively correlated with reality.

I’m fond of the saying, “Just because you’re paranoid doesn’t mean they’re not out to get you.”

But as ee cummings said, sometimes a cigar is just a cigar. And sometimes paranoia is just irrational.

Trust and Statistics

What’s this got to do with trust? Good question.

First of all, ask yourself what the headlines say: Is trust in business generally up? Or is it down?  You all know the ‘right’ answer.

But trust has a definitional problem that crime doesn’t. Determining whether crime is really up or down is simple: look at the crime rate.

When it comes to trust, however there are three conceivable measures:

  1. Trust, the verb – are people more, or less, inclined to offer their trust in principle?
  2. Trust, the adjective – is business more or less trustworthy?
  3. Trust, the noun – is the resultant state of people’s trust in business up, or down?
Verb x   adjective  =  noun
Propensity to trust of trustor x trustworthiness of trustee = Level of trust achieved

All too often, the business press is guilty of mass confusion. When you see precise statistics from sources like the high visibility Edelman Trust Barometer, saying ’Trust in XYZ industry is up (or down)’  – ask yourself just what that oh-so-precise percentage is referring to. Does it mean:

  • People are X% less inclined to trust a given industry or company?
  • Industries/companies have gotten X% less trustworthy?
  • The state of consumer-to-industry trust has undergone an X% decline?

Presumably it means the last – the state of trust has declined. But here we have a problem – because we can’t tell which driving factor drove the decline.

  • Do we have a problem of paranoid consumers?
  • Or do we have a problem of endemic industry untrustworthiness?

If consumer fear-driven low propensity to trust is the root issue, then the financial services industry has got a public relations problem on its hands, and they should hire Edelman.

But if industry misbehavior is the root issue, then we’ve got a social, regulatory and political problem – throwing PR solutions at it won’t help, and may hurt.

Parsing the Data

There do exist some data. Every year the General Social Survey asks some trust questions, which are clearly of the “verb” type, assessing people’s general propensity to trust strangers in principle.

Here there is a clear trend: across the world, and particularly in the US, there is a secular decline in the level of propensity to trust.  So we have part of the answer: paranoia is increasing.

The question is: is the paranoia justified? Has trustworthiness declined, or has it increased?

I only know of two data sources that speak to that, and only partially at that. One is Trust Across America’s FACTS database, which gathers a number of data-points and aggregates them into measures of corporate trustworthiness. And while the TAA data does an excellent job of facilitating cross-company comparisons over time, its five years of data isn’t yet enough to speak clearly to aggregate trends.

The other source is our own Trust Quotient, or TQ, which overtly measures trustworthiness at the personal, not corporate, level.  We have noticed, both anecdotally and statistically, a gradual rise in the average level of TQ over the past 7 years. However, the data is self-reported, and is not a controlled valid sample of a broader population; it may just be grade inflation, or it may be comparing apples and oranges.

The conclusion? Except for the propensity to trust, which is clearly down on average, most trust data is either very specific and qualified, or definitionally vague.

I confess to some irritation on this topic. Trust is a serious issue, with many people seriously studying it, and doing so carefully. There are many more, however, who feel qualified to spout generalities and truisms about trust with no definitional clarity. Simply put, there is a lot of non-sense out there.

Next time you read something about trust being up or down, be critical. Ask whether the ‘trust’ being measured is a verb, an adjective, or a noun.  Ask whether pessimism is justified by data, or whether paranoia is overwhelming reality. Ditto for trust on the upside: if a company tells you their trust levels are up, push for definitions.

Don’t just nod your head: be a discerning student of trust data.

 

 

 

Are You a Trusted Twitterer?

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Measuring instrumentThose of you who love new social media and are measurement mavens, this blog’s for you.

Ever wonder how you’re doing on Twitter? Of course, you can’t miss the “followers” count at the top of your and everyone else’s twitter page. But, as you tell your fellow-twitterers, it’s not about the numbers. (Not that you’d turn down a doubling of your followership, of course…)

The urge to emulate former New York Mayor Ed Koch runs deep: “How’m I doin’?”

Well, courtesy of the Edelman PR agency  you can now measure your, well, your Tweetlevel. An interesting choice of words, because, well it’s hard to say just what’s being measured.

Measuring TweetLevel

Mechanically, you get a blended score of four attributes: Influence, Popularity, Engagement, and Trust. You can also get not only your own score, but the score of anyone else as well.

They tell you exactly how they compute each factor, and the total Tweetlevel. They also let you look under the hood, and and invite users to help improve the survey.

So let’s start by giving props. I’m no psychographic or statistics expert, but I’ve seen a few surveys, and this looks good. Note too that Edelman is perhaps the world’s leader in commercial trust measurement, authoring the Edelman Trust Barometer  for a decade now. CEO Richard Edelman builds conferences and speaking engagements around it. There are questions about any measurement of trust, but these guys are pros at doing trust surveys. It is a solid piece of work, and at the very least will raise good discussion questions.

Now for the fun.

Measuring Trust

Somebody hands you a ruler, the first thing you do is measure yourself. I clocked in at a TweetLevel of 43 (on a scale of 100). Higher than some, lower than others.

This blog is about trust, so that’s the one component on which I focused. My trust score was 39.9.

Now, just because I write about trust doesn’t mean I’m trusted. Oprah beats me. Her trust score is 64.5. OK, I can get with that.

Yet Oprah is surpassed by–Britney Spears! Spears sports a trust score of 68.7 Riddle me that one!

Now hold on to your hats; clocking in at third place, with a trust score of 95.7 is—Perez Hilton!  Of course. I should’ve seen it coming.

And hold on, in second place is—wait for it—John Mayer!  (In fairness, the NYTimes is number 5).

Why Measurement Mania is Death on Trust

It’s easy to lampoon surveys like this, but that’s only partly fair. The metrics for trust rely heavily on retweets, and on “via’s” (think of them as retweet derivatives, if you’re financially inclined). That’s not so crazy: number of citations is a decent metric for being ‘trusted’ in academia, for example.

I’ve written before  about measurement mania, the tendency in business these days to literally define management in terms of measurement (e.g. the silly phrase “if you can’t measure it you can’t manage it”). And I’ve written about the hazards of measuring trust in particular. 

The biggest problem comes not in the measurement, but in the subject matter.  So it is with trust. In the TweetLevel tool, trust is largely a function of how many people cite you. That’s perfectly reasonable. People definitely hang on Perez Hilton’s words a lot more than on mine.

But it does beg a huge trust question: trust Perez Hilton to do what? To say what? To behave how?  What is it that we trust about John Mayer–and is it the same thing as for which we’re trusting Oprah?

I trust my dog with my life–but not my ham sandwich. I trust Perez Hilton to tell me the straight poop in Hollywood–but not to show my daughter a night on the town. What is the object, the referent point, of the trust being measured?

Comparing trust metrics without defining the trust object is like comparing love metrics between a monastery and a brothel. By a perfectly obvious definition, the brothel gets a whole lotta lovin’ more than does the monastery.

In a sense, that’s right. And in another, ridiculous. Do we say a man with 5 marriages is ‘more loved’ than a man with one?  Is a parent with 5 kids more loved than a parent with one?  What is it that we’re measuring by using such metrics?

At this point, the numbers inevitably end up kind of looking like a popularity contest. There seems to be no referent point beyond the counting of incidents. Quality is overwhelmed by an onslaught of quantity. TweetLevel’s advice to increase trust scores is to get people to retweet you more. If everyone took this advice, Twitter would drown in derivative re-tweets. We’ve seen that movie before, on Wall Street.  It ends badly. 

On twitter, the mania to measure drives more empty-calorie retweets, which decreases original content, which ends in more retweet inflation as people try to game the game. 

It’s not that trust is ineffable, it’s just that it’s so contextual. Trust is a bit like obscenity; we know it when we see it, but that doesn’t mean we can easily define it, much less measure it. This is tail wagging the dog stuff.  The measurement system has a bad feedback loop to the content system; the mania for measurement ends up destroying the content it purports to measure.

Do You Want Meaning?  Or Measurement?

We can have meaning, or we can have precision. This is exactly the case in sub-atomic physics, where (as per Heisenberg) the act of measurement itself alters the thing being measured. It’s a perfect metaphor.

• You can say that you trust Perez Hilton to dish dirt, and Oprah to get real with you
• Or, you can say that Perez Hilton is 48.3% more trusted than Oprah
• But you can’t say one without rendering the other silly.

In accounting, there’s an age-old debate about how to define ‘profit.’ My finance prof Pearson Hunt said it the best: “Profit is–the bottom line of the income statement.” In other words: give it up; there is no one answer.

All you metrics mavens out there: when you get into the soft stuff, ask yourself: what is it you’re measuring? Is it the thing itself? Or is it some reflection of metrics in an infinite mirror?