So, You Don’t Have Time To Be a Trusted Advisor?

One of the more frequent comments I get in talking about being a trusted advisor is this:

“We’d love to practice all the things you talk about, Charlie, we agree with them all.  But, we just don’t have the luxury of the kind of time it takes to get there. There are too many other demands, and we just can’t spare that kind of time.”

True or False: It takes more time to be a true trusted advisor than it takes to do just a very good job of service delivery.

Just to be clear where I stand: that statement is as false as a three dollar bill.

Trust Doesn’t Necessarily Take Time

First of all, the old truism that “trust takes time” isn’t necessarily true. Only one of the four trust equation components necessarily takes time, and that’s reliability – because by definition reliability requires a track record.

The other trustworthiness components – credibility, intimacy, and low self-orientation – can be, and often are, assessed in a few moments.  We all form very strong first impressions of people about whether they are truthful, competent, paying attention to us, of high integrity, and so forth.  Furthermore, we’re generally pretty right in those impressions, or at least we tend not to modify them greatly.

But that’s only about a single instance of trust establishment. Let’s look at trust over time.

Trust Saves Time

The fact that trust can be established quickly is only the beginning. What happens after trust is established?

Most would agree that having a trusting relationship means that things go more quickly from then on; your word is taken as bond; your advice is heeded; processes proceed more quickly; there is less double-checking, and so forth.

So, do the math. Let’s say you’ve got ten interactions with a client, and in the first one, you establish a great deal of trust. The next 9 interactions will proceed more quickly, with deeper results, than if you did the dance of distrust every time you interacted. The aggregate amount of time spent is almost certainly less, not more, in the trustworthy case.  Trust doesn’t require more time, trust saves time.

In other words, even if trust took time up front, the investment is more than paid off in future interactions by a host of benefits. But even that’s not the end.

It’s Trust Quality, not Quantity, that Counts

If you had to invest time to create trust, the ROI created would typically be very positive; it drives lower costs of sales, better time to market, and so forth. But you don’t have to invest much time. Not if you are qualitatively excellent.

Imagine two equally competent and good-willed professionals.  Over the same period of time, one does high quality client work, displays excellence, and offers good value.  The other one does the same – but in addition, becomes highly trusted. If time were the only variable, then this scenario makes no sense – given equal time and equal everything else, they should be equally trusted.

But we all know that scenario is actually quite common – one professional is frequently more trusted than another, often with even less time invested. Why is that?  What are those highly trusted people doing?  Ask yourself that question about the highly trustworthy professionals you know.

Let me suggest they don’t get there by logging more hours – they get there by higher quality trust creation. They are authentic. They take emotional risks. They pay attention. They don’t focus on driving clients toward their own desired outcomes. They go where the conversation takes them. They freely admit their blank spots. Their goal is client service, not account profitability. Their highest calling is to make things better for the client.

They are fearless, humble, generous, curious, and other-oriented.  Those are the qualities that make them trustworthy – not how many basketball games they took the client to.

You don’t have the time to be a trusted advisor? In the aggregate, there may be a positive correlation between high-trust relationships and time spent, but you’d have a hard time convincing me that time caused the trust. In fact, I think it’s more likely that trust drives the length of time.

You don’t get to be a trusted advisor by logging hours. You get there by being more trustworthy. And not only does that not take more time, it actually takes less time.

Don’t let yourself off the trust hook; you can do it with quality, not time.

3 Principles to Positively Measure Sales Training Effectiveness

It’s an article of faith in business that “if you can’t measure it, you can’t manage it.” The alternative phrasing is, “What gets measured gets managed.”

Nowhere are those mantras more repeated than in the fields of corporate sales and training. And at the intersection—the field of sales training—it’s beyond an article of faith; it’s more like The Book.

And yet, in my admittedly limited experience (serving mainly high-end, intangible, B2B businesses), I’ve noticed very curious things:

  • Learning and development organizations want to see precise, detailed performance metrics in their sales training programs, and they request evidence of such metrics from vendors’ past client engagements.
  • Those same companies do not themselves have such metrics for past training programs – and they balk at the opportunity to create them when offered.
  • Those companies feel guilty about this disparity.

They shouldn’t feel guilty. There’s a reason none of them actually produces the metrics they claim to want—because the metrics they want are the wrong metrics. Furthermore, the act of measuring them is harmful.

Companies for the most part end up doing the right thing despite their “best thinking.” Like Huckleberry Finn, who felt himself a sinner for having helped the slave Jim escape to freedom, learning and development departments are not sinners at all—they’re actually doing the right thing.

In this article, I’d like to congratulate them for their “failure” and point out an alternative to the wrong thinking they’ve been holding themselves accountable to.

The Heisenberg Principle of Training

In physics, the Heisenberg Principle says that at the sub-atomic level, the act of measuring either mass or velocity actually changes either the velocity or the mass. In other words, measuring affects measurement.

What’s true at the micro-level in physics is true at the higher-order level in business training—the training of skills in areas such as engagement, vulnerability, listening, trust, empathy, or constructive confrontation. In those areas, the act of measurement affects the thing being measured. That effect can be positive or negative.

It does matter that you measure. What also matters, however, is what you measure and how you measure it – and we think wrongly about each.

It goes wrong when we approach these higher-level human functions as if they were lower-level behavioral skills. We apply the same mindset to them that we successfully apply to learning a golf swing, developing a spreadsheet, or creating a daily exercise habit.

These higher-level arenas evaporate when we subject them to the relentless behavioral decomposition appropriate for lower-level skills. Consider an example:

You declare to your spouse your commitment to improving your marriage. Your spouse is happy to hear of this decision until, that is, you declare that “obviously” you need a baseline and a set of metrics to regularly track your improvement. Still, your spouse is a team player and grudgingly agrees to go along. You jointly assign a 79.0 basis (on a 100 scale) for your baseline quality of marriage.

All goes well the first week: you are mindful of taking out the garbage, looking away from your email when your spouse speaks to you, and asking “how are you?” at least once a day—until measurement time. You then ask your spouse to rate your progress at the end of week 1: “Do you think I’ve moved the needle from 79.0? Maybe up into the 80s, huh?”

At this point, your spouse declares the experiment over, suggesting that you don’t “get” the whole concept. Oops. And by the way, you just slipped below 79.

What went wrong? On one level, it trivializes marriage to describe it solely in terms of behavioral tics like taking the garbage out, even though in the long run there is clearly a correlation. Further, focusing on taking the garbage out suggests it’s a cause rather than an effect. Finally, the frequency of focus on such things forces attention away from the true causes and drivers—a mindful attitude.

And on a deeper level, treating measurement this way confuses ends and means. A good marriage should be rewarding on its own terms. The overlay of a report card raises ugly questions: From whom are you seeking approval? And approval of what? Why, after all, are you doing this in the first place? What does “success” at the scorecard add to success in the marriage?

Gamification, so useful in more plebeian aspects of life, is trivializing, even insulting, when applied to the game of life.

Want proof? Ask your spouse.

Errors in Training Measurement

Such measurement is also trivial when applied to higher-level sales training. It’s true that to be successfully trusted as a salesperson, you need to do a great job of listening, empathizing, telling the truth, collaborating, and focusing on client needs. And if you do all of those things, you will sell more.

But the higher sales come about because you focus on the relationship.  The sale should be a byproduct of a relationshipnot the purpose or goal in itself, with the relationship solely a means to the sale. Focusing solely on the byproducts sends exactly the wrong message.

There are two errors you can make:

  • Measuring those improved sales every week (or very frequently). Doing so proves to everyone that you really don’t care about all of that empathy and trust stuff except insofar as it improves sales. Which means you’re a hypocrite. Which means they won’t trust you and won’t buy from you. Hello Heisenberg.
  • Measuring the constituent behaviors. If you break down “empathy” into various behaviors (looks deeply into client’s eyes, pauses 0.4 seconds before answering questions, uses phrases like ‘that’s got to be difficult’ at least once per paragraph, etc.), it proves to everyone that you don’t “get” empathy. You are just a mimic, and not a terribly good one at that. Which means they won’t trust you, and won’t buy from you. Hello Heisenberg, again.

Using Measurement Positively

Up until now I’ve been negative about the ways measurement is used—actually, the way we talk about it being used—because in fact, our better instincts take over and we don’t actually do these things often. But there are positive ways to measure. There are three principles:

  1. Pick long-term, big picture metrics. The best one for sales training is, of course, revenue—but measured over time. The right timeframe varies with the business, but less than quarterly is too much.

Other things you could measure—and there shouldn’t be too many—include account penetration, share of wallet, or cost of sales. Again, these should be looked at as trailing indicators of performance, avoiding any suggestion that they are short-term causal drivers to be tweaked. You don’t cause mindsets like trust by practicing tiny behaviors; you cause tiny behaviors by focusing on mindsets like trust.

  1. Substitute discussion for reports. If your only reason for metrics is to “manage” them, then everyone will intuit your bad faith—that you don’t really care about empathy, you care about winning the battle for being empathetic as soon and as profitably as possible, and you will ding anyone for not being empathetic.

Instead, have irregular but frequent open-ended discussions about the numbers. There’s nothing wrong with discussing listening techniques or examining pipeline status. Doing so is how we get better and should be the purpose of sales coaching. But by discussing rather than “reporting” and “evaluating,” you show that your purpose is indeed on the end game (engagement, trust, etc.) and not on scorecards.

  1. Publicize discussions as motivation, not metrics. If someone has a breakthrough in listening, use the process to celebrate and educate the organization. (Look at what Joe did, and how he did it!) This is using Heisenberg in a positive way—to publicize insights and to encourage.

The alternative—defining smaller and smaller behavioral details—whether you publicize it or not, sends the message that salespeople are being evaluated, not coached. It also says that the metrics matter, not the end purpose they’re intended to serve.

Learning and development people: stop thinking you need detailed behavioral metrics. Give yourself a break, give your vendors a break, and give your salespeople a break. Coach your staff, demand principled behavior from them, and hold them accountable. Don’t track them minutely and with an hourglass. Coach on details to get better, measure end results to show it’s all working, and communicate what’s important.

Why You’re So Predictable

On the one hand, it seems the world is getting less predictable. On the other hand, looking at the successes of Big Data and AI, haven’t we all at the same time become more predictable?

Isn’t that how those kids in Macedonia made thousands of dollars running fake articles on social media? Isn’t that how James Corden got famous enough to host the Grammys?

As I thought about this, I remembered that I’d thought about this before. About 11 years ago. Let’s see how 2006 sounds from the vantage point of 2017.

————————-

Fortune talked about recommender systems a few years back.

What’s a recommender system? Well, take Amazon’s “if you liked The Da Vinci Code, you’ll love Blink.” Now move from book-to-book relationships into book-to-other relationships: “If you liked the Da Vinci Code, you’ll like a Jura Capressa espresso maker.” That’s a recommender system.

Fortune’s example was www.whattorent.com, helping slackers save time at 10PM Friday night at what was the local Blockbuster by predicting what movie they’ll love. [Remember Blockbuster? Just eleven years ago…]

Fortune interviewed whattorent’s two founders at a coffee shop, and put them to the ultimate test: pick two strangers in this restaurant, and—just by observing them—guess their favorite movie.

They settled on a guy and a young woman. After much clever psycho-babbling, the founders guess: Starship Troopers for Joe, Roman Holiday for Renee.

And wouldn’t ya know it—they were dead right.

You can hear Fortune cuing up the PGA graphic—“these guys are good!” And indeed that’s our reaction—wow, how could anyone pull that off?

But wait. What if we’re mixing up cause and effect? Maybe it’s not that two twenty-somethings are great predictors. What if we’ve just all gotten way more predictable?

Everyone had their favorite Beatle. If you preferred John to Paul, it said something about you—to everyone. Because everyone had a common reference point. The Fab Four were global litmus tests.

Since then, culture got way more global. Africans wear Arizona t-shirts; Valley Girls know Tibetan monk choirs. The weapons of mass dispersion are well known—iPods, MySpace, YouTube, Hollywood [can you believe – this was only 11 years ago…the iPhone was still a year away…]

Everyone wants to be different—but we share referent points from which we diverge. Jeans, music, hair, slang… Take five variables with five values each: five to the fifth power is 3,125 combinations. Sounds like a lot, but it’s based on a small set that’s easy to reverse-engineer.

People don’t predict us: we self-identify, and the code is easy to read. Marketers love this stuff.

Ironically, it also makes it easier to trust others. When a British Stones fan meets a Jagger aficionado from Beijing—the world shrinks.

The question is: can we keep the diversity while enhancing the trust?

———————

Well, that was my question then. My question now is similar, but updated: can we keep the authenticity while mechanizing the means of connection?

This is most evident in commerce. You still know, in your bones, when you receive a mechanized spam email, trying to pass itself off as personal. I suppose scams may be getting more sophisticated; but a ton of people aren’t even bothering to be sophisticated. They confuse the ability to target and segment with the desirability of doing so. Just because you can doesn’t mean you should.

We’re all pretty predictable. That’s OK. Go ahead, predict me – just let me know there’s someone behind the prediction machine, someone who cares enough to add the whipping cream topping by making it personal.

The difference between being sold to by a person and being sold to by an algorithm is the difference between talking to a person who used a robot to find me, and talking to the robot itself. I don’t mind being predicted – just don’t insult me.

The Semantics and Study of Trust

This post isn’t quite as wonky as the title would suggest. Bear with me.

Most of us would agree that ‘trust’ is a complex concept. But few of us, I suggest, have any idea how sloppily we think about it.

The Semantics of Trust

Consider some obvious grammatical usages of ’trust’:

  • Trust as a verb, as in “I trust James.”
  • Trust as an adjective, as in “James is less trustworthy than Jane.”
  • Trust as a noun, as in “trust is less common in Russia than in Denmark.”

Now ask yourself: what is the meaning of the sentence, “Trust in banking is down”?

Does it mean:

  1. that people are less inclined to trust banks these days? or
  2. that banks have become less trustworthy than they used to be? or
  3. that the customer-bank relationship is less based on trust than it used to be?

Why is that important? Because if you don’t know what problem you’re trying to solve, you’re just going to spin your wheels.

Is that a real issue? You betcha. It goes to whether we need more bank regulation, better bank PR, or a rebirth of spiritual values.

For an analogy, consider the fact that serious crime in the US has been declining for about two decades – and the mistaken belief held by majorities that it has actually been rising.  That’s a PR problem.

Now consider that Wells Fargo consistently and consciously incented its employees to sell unnecessary products for years. That’s a trustworthiness problem.

In the aforementioned link, from the Edelman Trust Barometer, you can find hints of all three meanings.  Which suggests, first of all – we have a semantic problem. What the heck does Edelman mean by ‘trust’?  Because if that answer isn’t clear, then how can we meaningfully talk about how to create trust (by smarter consumer risk-taking? by better regulation? by broader social change?).

Biases of Trust Researchers

Psychologists who study trust are, as a group, fixated on trust-the-verb. This is hardly surprising; their view of the world is from an interior perspective, the mind looking out, hence on issues of perception.  They focus on the decision to trust, and thus on the attitudes toward risk-aversion and risk-seeking. Trustworthiness as an adjective is dealt with as an issue of perception by the trustor, not as an attribute of the trustee – trustworthiness is all in the eye of the beholder.

Sociologists are concerned with trust the noun, and with questions like why southern Italy is a lower-trust society than Sweden. When they say ‘trust is down,’ they are talking about the  likelihood of a surveyed population to have a more suspicious outlook on strangers than they used to. They’re interested in herd behavior, not in the perceptions of individual cattle.

Business writers on trust are the most confusing of all.  They pay about as much attention to trust-as-adjective (trustworthiness) as they do to to trust-the-noun. Unlike the academics, however, business writers use the word ‘trust’ to refer to institutions, as opposed to most academic talk (and most talk on Twitter, for that matter), which is about interpersonal trust.

Unfortunately, business writers are often unclear about the distinction (if banks are untrustworthy, is this because bankers are venal, or because ’the system’ is amoral? And is my trusting JPMorgan Chase really not qualitatively different from my trusting Susie?).

Definitions: A Simple Trust Ecosystem

Here’s a simple, five-factor description of the trust ‘ecosystem.’

Trust (1. the noun) is a relationship, between a trustor who trusts (2. the verb) and a trustee, who is or is not trustworthy (3. the adjective). The trustor initiates the relationship by taking a risk (4. the driver of trust); and continues when the roles reciprocate (5. the sustainment of trust).

At the risk of grammatically complexifying what isn’t all that complicated in practice: trust is an asynchronous bilateral relationship initiated by risk-taking and sustained by reciprocation.

If all who wrote about trust simply referred to these five factors, and were clear about what meaning they intended, the trust literature would be much clearer, and recommendations more cogent.

 

 

 

Do We Learn From Our Mistakes? Or Not?

The NYTimes reported a few years back on a Harvard Business School study of venture capital-backed entrepreneurs to test whether or not we learn from our mistakes. The results are confounding to many—including me.

Here’s the story. Several thousand VC-backed companies were studied over 17 years. First-timers had an aggregate success rate of 22% (success meaning going public).

The study is about those trying for a second time. Did the 78% who failed the first time learn from the experience, and do better the second time? Or worse? How did the 22% first-time winners fare—did they get lazy and decline? Or did they somehow do better the second time?

No less an expert than Gordon Moore, sainted ex-leader of Intel and the author of “Moore’s law,” said “You’re more valuable because of the experiences you’ve been through under failures.”

I’m with Gordon. But according to this data, we’re both wrong.

Those who succeeded the first time upped their success rate, to 34%. But those who failed the first time stayed mired in the muck, at 23%. So much for the myth of the gritty, plucky lads who pick themselves up and learn from their failures.

Apparently the data are not the problem: “the data are absolutely clear,” says Paul Gompers, one of the study’s authors. Yet it is still far from clear what the data mean.

As is often the case, data are one thing, and explanation another. Of course, the obvious explanation may be true: people just do not learn from adversity. This seems to be the study’s authors’ view—that the learn-from-failure ethos celebrated in Silicon Valley is really just anecdotal tales over-told.

Then again, maybe we actually do learn more from success than from failure. If so, perhaps that’s because of increased confidence resulting from one win.

Or, maybe only the really good people learn at all. And they can learn from experience alone, whether success or failure.

Or, perhaps these conclusions are only true of a certain type of person, characterized by some cross-cutting characteristic, such as risk tolerance. (Did you know height is correlated with IQ? True: short people score lower on the same IQ tests that tall people take. Of course, if you separate young children from the adults, or use age-normalized tests, the correlation goes away).

Or, to channel a recent 30 Rock storyline, maybe the first time winners are just very good-looking people who are actually horrible, but live in a bubble in which others let them pass. Hey, you never know!

Causal deductions are never fully provable—thanks, Dr. Hume. But progress can be made toward explanations.

So, what do you think’s going on?

And I’ll throw one idea into the ring, borrowed from Karl Popper, who developed the falsifiability theory of meaningfulness. A theory which is highly disprovable, but which remains standing, is superior to a hard-to-disprove theory.

Maybe people who fail have a much greater chance to learn. Why it is that they don’t still seems a mystery to me.

Trusting: the Other Side of Trust

Much has been written about trust.  However, it’s often not clear in the writing whether the subject is trust, trustworthiness – or trusting.  If trust in the government is down, does that mean that the government is less trustworthy? Or does it mean that people are less inclined to trust?

Most of my work has been about trustworthiness (e.g. The Trusted Advisor). Other people write more overtly about trusting – a good example is the HBR article ReThinking Trust, by Stanford Professor Rod Kramer, which focuses on the danger of trusting.

Some people write about the big subject of trust itself – the end result of the interaction between trustor and trustee. A fine example is Francis Fukuyama’s classic Trust: the Social Virtues and the Creation of Prosperity.

Finally, many other sources end up talking about all three; think Covey’s Speed of Trust, or Bob Hurley’s The Decision to Trust.

The Power of Trusting

The sources above are largely academic. In the popular press, by far the most common topics are trustworthiness and the state of trust itself (trust as the result of an interaction between trustor and trustee). Throw a dart into a pile of 100 popular press articles on trust, and you’re likely to find Congress, investment bankers, and the Madoff-du-jour scandal as the subject.

This means most public policy debates focus on trustworthiness.  Most examples are negative; hence trusting is positioned as cautionary, i.e. watch out for car salesmen, lawyers, etc. The moral of the story is tut tut, another untrustworthy group, watch out.

And all this focus on negative examples of trustworthiness is having an effect on people’s inclination to trust. How could it not! And that is a terribly unfortunate thing. Because the scarce trust resource increasingly is not trustworthiness, but the willingness to trust.  We need to start focusing on the trustor, not just on the trustee.

The power of trusting is enormous. When it comes to trust, there is an answer to the chicken and egg dilemma of which comes first, the trustor or the trustee?  The answer is trustor.  Consider:

  • Until one party decides to take a risk and trust another, trust does not come into existence
  • Trusting has a profound impact on trustworthiness – think “the fastest way to make a man trustworthy is to trust him,” or “people live up or down to the expectations of them”
  • Trusting is inherently an act of optimism; a decline in trusting in the business world drives down innovation, and prevents collaboration and alliances.

 

Traveling Trust, Reciprocating Trust

I was in Munich for a one-day stopover en route to Bucharest. I left New York a day earlier than planned to avoid some weather. And I realized yet again – travel has a way of doing that – what an extraordinary level of trust we all take for granted in our modern world.

Yes, the news is full of the opposite. Doctors have a hard time trusting pharmaceutical manufacturers. Patients have a hard time trusting their doctors, and doctors have a hard time trusting their patients. Some patients trust the internet more than their doctors, often with bad results. And trust in most institutions is down over time (the military being a notable exception).

A Trusted Trip

With all that going on, it’s easy to forget some basic things. I can freely cross national borders with some mere papers. I can trust the exchange rate when I buy Euros. I can trust the flight controllers that govern the airspace, the airline handling companies that do catering, the bus and taxi systems I encounter.

But most of all, I know I can rely deeply on the basic human decency of people I run into to help with any simple issues – even though we may not speak the same language, and we’ll never see each other again. I can trust that people will give me directions, help me with travel issues, take a moment to help sort out a problem. And I’m almost never, ever wrong in that basic level of trust.

Which motivates me, of course, to try and return the favor whenever I can. And you do the same, I know.

What’s Really Amazing

What’s really amazing is not how often trust goes wrong, but how often it goes right.  Our modern life is unbelievably complex, and yet runs remarkably well.

I don’t want to be Pollyana-ish about this. The fact that trust is so pervasive is precisely the reason we notice and feel trust violations so deeply. We are all right to be deeply offended by untrustworthy behavior; if we lose our capacity to be outraged, we have lost our ability to recover.

Lots of things can be said about lost trust, but I want to highlight one. Trust is reciprocal. My trusting you causes you to trust me, and vice versa. An absence of trust starts with one party. The presence of trust starts with one party. The question facing all of us is, will you be the one to start?  Or will you always insist on the other party going first?

Do you insist on your vendors insuring you against all losses?  Then don’t be surprised when they don’t trust you.  Do you have all your employees sign cutting-edge non-compete clauses?  Then perhaps you can understand why they might seek ways around it.  Do you give lie detector tests to your employees? Then you might gain insight into why you have a shrinkage problem.

You can do your part as an individual too. To be trusted, be trustworthy.  And if you think others are not trustworthy as you – try trusting them first.

For starters, that’ll make your travel a lot easier.

Technology Transformation vs. Trust

Is technology killing trust in your organization? Are we heading for a dehumanized, low-trust business world?  Can technology itself come up with trust-enhancing ways to guard against this trend?

I’m getting asked these questions lately. And while there’s some merit to the question as framed, the news is not nearly as bad as it sounds – provided we remember a few basics.

The Technological Threat to Trust

Think of your own business – how is it being affected by:

  • Social collaboration
  • Big data/analytics
  • Mobility
  • The cloud
  • CRM
  • Process automation
  • Robotics
  • Internet of Things
  • 3d Printing
  • Cognitive systems
  • Blockchain
  • Digital wallets
  • P2P lending
  • Crowdfunding
  • RoboPlanning

Since trust is largely personal – so the logic goes – and the thrust of most of those technologies is to reduce the human connection, if not eliminate it entirely, then we must be heading into a dangerously low-trust future.

  • How can you trust a robo-planner the way you trusted a CFP?  Alternatively, maybe the robo-planner is actually more trustworthy?
  • How can you establish customer relationships when the customer has walked themself through half the buying process online without speaking to anyone? And what if the customer no longer wants those relationships?
  • What happens to trust when my firm automates a process? Doesn’t going from trusting a person to trusting a process create an inherent reduction in trust?

What We Forget

In this way of framing the problem, we forget two major offsetting benefits of technology – each a significant cause for optimism.

The Tradeoff.

The most obvious is that there is trust, and there is trust. In particular, there is “soft” and “hard” trust. These correspond to the Trust Equation components as follows:

“Soft trust” — Intimacy and Self-Orientation

“Hard trust” — Credibility and Reliability

In many of the technologies we talk about, there is a direct trust trade-off. What we lose in human contact, we often gain in reliability (in particular). It wasn’t that long ago that people stood in lines to get cash from their checking accounts. You had to walk a distance; banking hours were restricted; and you never knew how long the lines would be.

Would anyone – bank or customer – ever want to give back the freedom that ATMs gave us? In trading off the polite chit-chat with your friendly neighborhood teller, you got reliable convenience, reliably availability, (pretty) short lines, and reliable accuracy.  A net plus.

Such is often the case with automation, CRM, the cloud, and other technologies. What we lose in one part of trust, we gain with another.

The Multi-part Solution.

The least obvious offsetting benefit is that all the technologies above have not affected by one iota the basic biology of humans. We still are complex,  non-linear, and emotionally-driven in our fundamental approach to people, risks, relationships, and business. Neither Steve Jobs nor Stephen Hawking have come anywhere near close to rewiring humans.

And humans have always resisted purely logical reasoning. Whether you prefer the observations of Daniel Kahnemann or of StarTrek’s Dr. Spock, we like to make decisions based on emotion – then rationalize them after the fact with linear logic.

–We buy with the heart, and justify it with the brain.

–We don’t care what people know until we know that they care.

–The fastest way to make a man trustworthy is to trust him.

What does this mean for the technology v. trust conundrum? Plenty. It means that it’s impossible to engineer out all “soft” trust in most situations – we humanly resist it.  And if we have less of an opportunity for ‘soft trust’ creation, then the entire weight of the soft trust creation will rest on the few remaining opportunities for interaction.

In other words – fewer trust opportunities does NOT mean lower trust – it means more trust weight and emphasis being placed on fewer personal interactions. The trust-importance of those interactions is actually increased, not decreased.

Trust Design Implications

What’s to be done? There are two false solutions, and two better ones.

  1. The technical temptation. It’s tempting to ask technology to solve its own problem, but it’s nearly always the wrong answer. More metrics won’t help if your values are wrong (see Fargo, Wells). Customer sat surveys are as bloodless as the technologies they’re deployed to measure. And no matter our Hals, Siris, and Alexas, we know they’re not ‘soft,’ they’re just software. You can’t get intimate with an avatar (yet, anyway).
  1. The specialist temptation. Similarly, it’s tempting to view technologists as hopeless cases, and to bring in a special squad (group, team, unit) whose job it is to do trust. Wrong: you’re far better off training technologists to get a little better at trust than you are training poetry majors to talk to technology clients. Anyway, you can’t fix a technologist’s low trust by pointing to someone else’s high trust.
  1. The transparency solution. However, technology can help in two particular ways. One is simply to leverage the informational power of technology, and move radically in the direction of transparency.

The reason is simple. A big component of people’s trust is whether they think you have something to hide. That is true at the personal and the institutional level. If we sense that the person, process or organization has no axe to grind, no hidden agendas, and no secrets, then we are inclined to trust them.

This kind of transparency is evident even before we meet someone – in our website designs, in our employee and customer policies, in our public responses.  In an evolving world, when we start by assuming confidentiality, we are setting ourselves up for failure. The right beginning question is “Why shouldn’t we be sharing this?”

  1. The design solution. A technical world is one in which users have power. Users include employees, customers, suppliers, neighbors. Most cases are not like the ATM, where zero contact is required. In most cases, some contact is required.  The key is to give the participant maximum power over the timing and nature of that contact.

In a sales process, this means make everything feasible available without personal contact – eg. online. Then, when the customer gets to the inevitable point where they actually need, and want, a real-person interaction, make that interaction available:

  1. immediately (e.g. within a click for text support, two rings if phone)
  2. with high quality (i.e. a qualified, unscripted support person authorized to talk.

Digitization is not immutably opposed to trust – we’re just not thinking about it rightly. The challenge is for us to get better at trust in the remaining interpersonal situations, and to design the non-personal interactions in ways that respect our analog nature.

 

 

 

Trust Takes a Long Time to Create, a Short Time to Destroy. Not.

There are two kinds of mistakes we make with trust. One is to trust mistakenly – the other is to fail to trust at all. One is a failure of commission, the other a failure of omission.

The former gets all the press – but it’s the latter that is the bigger problem.

Let me explain.

——

One of the bigger myths about trust this one: “Trust takes a long time to create, but only a moment to destroy.” There’s no need to name names here, but you can see examples of it here and here and here and here.

Here’s why that myth isn’t merely annoying, but positively harmful as well.

The Truth.

Let’s start with the truth. Most human relationships, like most emotions, take roughly as long to get over as they took to develop. Marriages or friendships don’t end overnight. There may be a flash point, a straw that breaks the camel’s back. But we cut slack for people we trust. We don’t dump them abruptly.

If trust were lost in a minute, many victims of relationship abuse would leave their abuser at the first incident; but things are often a little more complicated than that.

If trust died quickly, the SEC would have investigated Bernie Madoff when Harry Markopolos first lodged charges against him. If trust died quickly, the steady drip drip drip of evidence at Penn State, Enron, and Wells Fargo would have ended at the first drip.

Most examples of “trust lost quickly” turn out to be either just the last drip in a long series of drips – or a delusion about trust’s existence in the first place (you don’t “violate the trust” of a subscriber to your email list by sending them a worthless referral; the relationship you have with a name on your email list may be many things, but “trust-based” is probably a stretch).

Trust formed quickly can be lost quickly; trust formed at a shallow level can be lost at the same level.  But trust formed deeply, or over time, takes deeper violations, or a longer time, to be lost. The pattern looks more like a standard bell curve than a cliff.

But, you might say, so what?  Why is that harmful? What’s the big deal? 

The Harm.

If you believe that trust can be lost in a moment, then you likely believe you must be cautious and careful about protecting it. You are likely to think about trust as a precious resource to be guarded against being tarnished. You are inclined to institute rules and procedures to protect it and to give cautionary lectures about the risk of losing trust.

Yet these are precisely the kinds of behavior that result in trust lost.

I don’t trust the man who talks with me while pointing a gun at me‬ – partly because he looks threatening to me, but also because he clearly does not trust me.

Trust, at a personal level, is like love and hate: you tend to get back what you put out. You empower what you fear. Those afraid of getting burned are the most likely to get burned.

This works at a corporate level too. I remember vividly the convenience store chain that gave monthly lie detector tests to store managers to prevent theft – and then wondered why the theft kept on happening.

I recently heard from a company wanting to modify the Trust Equation by “toning down” the component called Intimacy to something more bland, like affability or good manners. Why? They didn’t want to be seen as encouraging employees to have sexual liaisons with customers. This falls in the same category with multi-paragraph email signature caveats, and the fine print on retail customer receipts. Fear of trust not only doesn’t save trust – it actually causes low trust.

Trust is a Muscle.

Thinking of trust as something you can lose in a minute makes you cautious and unlikely to take risks. But the absence of risk is what starves trust. There simply is no trust without risk – that’s why they call it trust.

If your people aren’t empowered, if they’re always afraid of being second-guessed, then they will always operate from fear and never take a risk – and as a result, will never be trusted.

Trust is a muscle – it atrophies without use. And the repetition of the mantra “trust can be lost in a moment” just tells people not to use it.

Turns out the stupidest, craziest trust is the trust you never engaged in because you were too afraid of losing it. The smartest trust is the trust you create by taking a risk.

Interview with Barbara Kimmel of Trust Across America – Trust Across the World

Today’s interview is with a significant player in the world of those who seek to improve trust in the business world – Barbara Kimmel. Barbara is CEO and co-founder of Trust Across America – Trust Across the World. She is also the co-creator of the proprietary FACTS® Framework – a unique methodology measuring the trustworthiness of public companies. We focus on FACTS in this interview.

Charlie Green: Barbara, welcome to Trust Matters, and thanks for sharing your insights with us. First, you founded Trust Across America – Trust Across the World. What is that, and what do you do?

Barbara Kimmel: Thanks for having me, Charlie. TAA-TAW’s mission is to help organizations build trust. We’re in our seventh year now. Our proprietary FACTS® Framework ranks and measures the trustworthiness of over 1500 of the largest US public companies on five quantitative indicators of trust. I also run the global Trust Alliance, am the editor of the award winning TRUST INC. book series and am a Managing Member at FACTS® Asset Management, a NJ registered investment advisor.

The FACTS Model

CG: OK, let’s get into FACTS®. Just what is it (and what do the letters stand for)?

BK: FACTS® is an acronym covering Financial Stability, Accounting Conservativeness, Corporate Governance, Transparency and Sustainability. This multi-factor framework was developed by a cross-silo multidisciplinary team in the wake of the financial crisis in 2008. The Framework evolved by asking the same question of dozens of “siloized” professionals from leadership, compliance and ethics, legal, accounting, finance, HR, consulting, CSR, sustainability, etc. “What do you consider an indicator of corporate integrity or trust “worthiness” that can be independently and quantitatively measured without requiring the input of the organization itself? 

While every professional had a different perspective, the same indicators were repeatedly mentioned within each silo. The governance professionals pointed to board composition and compensation policies. Those in finance pointed to stable earnings, and so on. By blending these indicators of corporate trustworthiness into a spreadsheet, the first quantitative measure of organizational integrity and trust was created.

CG: How many metrics in total are subsumed in all those five major categories? And how did you weight the categories?

BK: In all there are approximately 200 specific distinct metrics. The five categories are equally weighted.

CG: Can you give me a current example of the model’s applicability?

BK: Corporate leaders who want to be proactive about building and communicating trust across all stakeholder categories, or who want to avoid the next crisis can use our data to discover their organizations’ strengths (and weaknesses). Because our data is holistic and does not rely on employee surveys or questionnaires, it makes glaringly apparent where and why the Wells Fargo and Enron-like “risk” often lays hidden in the 1500+ public companies evaluated on an annual basis.  A company might have a high score in 4 out of 5 FACTS indicators and a low score in the 5th. Digging further into our data allows us to identify the cause of the low score and often this is a red flag that should not be ignored by leadership.

Third parties including major consulting firms, investment managers and associations are also requesting information. After 7 years, the FACTS Framework continues to make a solid case for the elusive link between trustworthiness and profitability.

In 2008 The Economist published a briefing paper sponsored by Cisco, called “The Role of Trust in Business Collaboration” stating that “tens of millions of dollars had been spent evaluating corporate governance – but a definition of corporate trust continues to elude us.” We at Trust Across America took on that challenge. What if the most trust “worthy” companies could be identified? That’s what we set out to do.

What FACTS Says

CG: What does FACTS tell us?

BK: Now with seven years of unique and compelling data, FACTS® data tells us which companies are doing more than just “talking trust.” It also shows us high-risk companies that may be the next to make the news. The majority of companies and their leaders still think that integrity and trust are soft and immeasurable skills, and don’t consider integrating trust-related data from one corporate silo to the next.

Balancing long-term value creation against the need to “maximize earnings” and meet the always-looming quarterly numbers is hard work. Waiting until the next expensive corporate crisis will afford leadership the opportunity to talk about the importance of integrity and trust, and how measures will be implemented to safeguard against future missteps. Implementing measures to increase the organization’s level of trust before the crisis is a proactive business strategy requiring both a 21st century mindset and the right tools.

CG: What about the long-questioned link between Doing Good and Doing Well: does it exist? Are highly trustworthy companies more profitable, or more successful in general, than lower-trust-rated companies? Or is it just a soft fluffy wish?

BK: Good question Charlie. With over 7 years of data on the trustworthiness of 1500+ of the largest US public companies, and three years of audited performance against the S&P 500, evidence is mounting that the most trustworthy companies are in fact more profitable over the long-term, and certainly less likely to have a Wells Fargo like blow up. Our data reveals many similar patterns like CEO tenure, board diversity, a commitment to ethical business and all stakeholders, not just shareholders. You may call it Doing Good and Doing Well, we call it “Value with Values.”

Trust Research

CG: Where does FACTS fit in the scheme of trust research?

BK: I don’t know that it does “fit.” Much of the trust research appears to rely on qualitative surveys, not quantitative metrics.  We are unique in that regard.

CG: Well, let me toot your horn for you a bit. I don’t know of any other research that combines rigorous definitions, seriously vetted data, a breadth of subjects and a 7-year-plus timeframe anywhere near as much as does the FACTS data.

In what form do you make it available to researchers, companies or individuals today? How can people reach out to you?

BK: We share many free resources on our website including our findings from our FACTS research. The data itself is proprietary and available for licensing. http://trustacrossamerica.com/about.shtml

CG: What do you see as key issues facing trust in organizations today?

BK: At both the individual and organizational level, trust is not only a tangible asset but also serves as a tiebreaker in every relationship. In most organizations, leaders take this asset for granted, viewing it as a “soft” skill or ignoring it completely. The assumption is high trust simply “exists” at the individual, team and organizational level.

Yet when integrity and trust are considered tangible assets and a business imperative, the following results are achieved:

  • Decisions are made faster and less expensively
  • Employees are more engaged and retention increases
  • Innovation is higher and occurs more quickly
  • Profitability increases

Convincing leaders of this remains a key issue.

CG: Let me push on that. If merely convincing them is the problem, then the FACTS data ought to solve the problem. I suspect that’s not the whole deal, however. Some if also lies in not knowing what to do about it. Can you speak to that?

BK: There is no single “department” that “owns” trust in an organization, so it tends to be either overlooked or taken for granted until there is a crisis. Then lots of money is dumped into trying to “restore” via crisis communications something that never existed in the first place.

But I really do think the main issue isn’t knowing what to do – it is, as I said, convincing leaders that it’s a problem. How hard was it to see that a culture of “hard-selling” retail banking products to unsophisticated consumers at Wells Fargo was trust-destroying and unethical? This is not a problem of insight, metrics or technical sophistication; this was willful moral blindness.

Leadership needs to be proactive about building trust and they need to own it. Only if they, and perhaps regulators, begin to take it seriously will organizations become more trustworthy.

CG: Barbara, many thanks for your time today, and best wishes to Trust Across America – Trust Across the World.