Don’t Confuse Your KPIs with Your CSFs

I spoke with BigCo, Inc. They wanted their B2B salespeople to become trusted advisors.

They felt (correctly) that greater trust levels with their customers would result in greater intra-customer market share and greater profitability. And they were right – as far as that goes.

But they then described to me their implementation plan. It consisted of breaking down the objectives into finer and finer components and matching them up with accountable business units – pretty standard practice.

As we dug deeper, a pattern emerged. The higher penetration levels, for example, were broken into more sales calls, more proactive ideas, and greater time spent up front. On the face of it, that sounds perfectly reasonable: if penetration were to increase, you’d probably see these changes in activities.

But there’s a causation/correlation problem here. Simply increasing the number of sales calls won’t do a thing; they have to be good calls. Simply offering more ideas won’t do a thing; they have to be decent ideas. Simply spending more time up front won’t do a thing; the time has to be well-spent. And simply assuming good calls, decent ideas, and well-spent time does not make it so.

This sounds perfectly obvious in the telling, but I have found that BigCo’s story (which is a composite of several clients) is common. It may even be the norm.

BigCo confused key performance indicators (KPIs) with critical success factors (CSFs). They confused correlation with causation. They confused measurements with the things being measured. And since we live in a management world that uncritically worships metrics (“if you can’t measure it, you can’t manage it”), this confusion has critical and strategic implications.

That’s especially true when you’re trying to implement a values-driven strategy – such as becoming trusted advisors.

Measurement and Management

Just because something sounds obvious in the retelling, it doesn’t mean it’s obvious when you’re in the middle of it. Case in point: BigCo’s flawed logic in their approach to trust-based selling.

Increasing penetration requires more sales calls, they thought, and they’re probably right. Their mistake lay in thinking that “more sales calls” was a cause. It’s not – it’s an effect.

“More sales calls” may be a KPI, but it’s not a CSF. It may be an outcome, but it’s not a driver. “More sales calls” is a metric. It is not the thing that “more sales calls” is intended to measure. That “thing” is something like “more high-quality interactions driven by mutual curiosity.”

This confusion between actions and measurements, causes and effects, and KPIs and CSFs is not just common – it’s becoming rampant. It’s a real issue for digital age businesses in some ways even more than old-line businesses. Let’s look at some examples.

Gaming the Numbers

We’re all familiar with the salesperson who knows how to tweak an imperfect system to maximize his commissions at the expense of, say, the company’s gross margins. “Hey, I’m just following the incentives you built in,” he might say. That salesperson seized on a metric that imperfectly measured the company’s intended sales behaviors. (The proper management response would be not to change the metric, but to insist on a higher set of principles that overrule one misguided number.)

The next time you get a customer service operator on the line, check to see whether they conclude by saying something like, “May we say that I gave you excellent customer service today?” You are experiencing a system that is driven by metrics to the point where operators shamelessly beg for ratings. The metrics have been pimped out to serve a goal other than the customer service they were meant to measure.

See for yourself. Go to Amazon, and search for books under any significant topic you like (e.g., sales). Make sure you sort on relevance. It’s amazing how many books are rated over four stars (out of five). The reason is simple: we have been taught to look for ratings. Of course, the emphasis on ratings suborns all kind of perjury, misleading comments, and even outright falsehoods.

It’s not just books. Look at the flood of “recommendations” on LinkedIn. Look at the massive follow-me-I-follow-you dynamic on Twitter and other media. Or just look at your own behavior. What do you do when a friend asks you to rate a book, promote a blog post, or recommend them? There is monstrous grade inflation in most customer-rated aspects of business today.

Much of this comes down to our obsession in business with metrics. It goes back to the invention of the spreadsheet and the success of books such as Reengineering the Corporation. Numbers-all-the-time is today’s secular business religion.

The Wages of Confusion

The “so what” is big indeed. Assume any metric, almost by definition, has to be a pale reflection of the “thing” that is to be measured. We accept anniversary gifts as tokens of our love, market share as an indicator of competitive success, and, in the case of BigCo, numbers of sales calls as indicators of trusted advisor relationships. But we all know an anniversary gift does not a marriage make.

The only way to become trusted advisors to your customers is to gain the trust of your customers. You do not cause trust by increasing the number of sales calls; rather, greater trust causes more invitations for you to call on prospects. Doing the dishes doesn’t cause a great marriage; instead, a great marriage results in your doing the dishes willingly.

Confusing KPIs with CSFs causes KPIs to be artificially inflated. We know this intuitively, and so we discount them – while still trying to get higher scores on more of those discounted-value KPI metrics. We all know the game is rigged, but we keep playing it faster and faster.

What’s at stake is nothing less than how we implement things like “better client relationships.” You don’t get there by measuring metrics and deluding yourself that you’re addressing root causes. You get there only by understanding what it takes to interact with your very human customers—and then doing it.

Do that, and the numbers will take care of themselves.

What Your TQ Score Really Says About You

I’m Kristin Abele, head of Trust Diagnostics at Trusted Advisor Associates.  I want to share some findings with you based on my eight years working with the TQ Trust Quotient Assessment tool.

The TQ (like IQ, and EQ, in case you didn’t catch that already), is based on the Trust Equation. The Trust Equation is a four-factor statement of the components of trustworthiness, first laid out in the book The Trusted Advisor. Here’s a brief video explaining the elements of the equation.

The TQ gives you a chance to self-assess your trustworthiness in a 20-question online format. It takes only a few minutes, and you get instant online feedback.  The basic test is free; there is a paid option for advanced results.

Go ahead, give it a go.  I’ll wait.

The assessment gives you a few key insights and numbers: your TQ score (a numerical score that says where you fall on a graph of trustworthiness), your strongest trust factor, your biggest area for opportunity, and your Trust Temperament (TM).

Let me help you interpret a few of the results.

What’s in a Number?

Your actual TQ score ranges from 0 – 15. The average score from the 70,000+ people who have taken the TQ to date, is  7.1 on the scale. So, what’s that mean? Is 7.1 the basis for deciding if you’re trustworthy? Is any score below that not-trustworthy? Is any score above that ranking among the Gods of Trust?

It’s tempting to be hard on yourself if your score is below 7.1 (or celebrate if it’s above); tempting, but not necessarily right. Your absolute score can be influenced by your tendency to be hard (or easy) on yourself.

But that’s not the end of the story. Breaking down the TQ score tells you quite a bit.

It’s All About the Factors

The big take-aways from your TQ report are your strengths, your areas for opportunity and your Trust Temperament.

Trustworthiness is made up of four key components: Credibility, Reliability, Intimacy, and Self-Orientation. After completing the TQ, you’ll be shown which factor is your greatest strength, which could use more of your attention, and a little bit about your personality when it comes to trust (your Temperament).

These results are what speak volumes about you – and your overall trustworthiness. Are you highly credible but avoid building any intimacy with your colleagues and clients? Does everyone know just how reliable your are but you tend to always put yourself before your peers?

This is what speaks volumes about the ways in which you are trustworthy – and how you are building trust with co-workers and clients.

 

 

 

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.

Clinton, Trump and the Trust Equation

Those of you following US presidential politics have been treated to a truly unique process this year. The role of the personal, of perceived character – and trustworthiness in particular – hasn’t been this central in decades.

The Trust Equation provides a simple way of articulating the several elements of trustworthiness: Credibility, Reliability, Intimacy and Self-orientation.  In short:

  • Credibility has to do with things we say – accuracy, expertise, capability, credentials
  • Reliability has to do with things we do – predictable, dependable, track record
  • Intimacy has to do with a sense of security that others feel in dealing with us – empathy, discretion, vulnerability
  • Self-orientation has to do partly with selfishness, but more to do with neurotic self-obsession. Being in the denominator of the equation, a high degree of self-orientation serves to reduce trustworthiness.

One of the things we’ve learned about the trust equation over the years is that most of us over-rate the importance of Credibility, and under-rate the importance of Intimacy.

With that as backdrop, let’s look at the key players in the election.

Credibility. In terms of credibility, Clinton has an edge. Her expertise, credentials, and history of responsibility and accomplishments, typically count for a lot. But on another part of credibility – simple truth-telling – she scores not nearly so well. She is perceived as constantly shading and tweaking the truth.

Trump, by contrast, has some business experience but very little relevant government experience, and is widely perceived as massively flip-flopping, telling one after another truth-stretchers, only to walk them back and position them as ‘opening gambits.’

Clearly credibility alone doesn’t explain why Trump is in the ascendance and Clinton in the decline.

Credibility Score: slight edge to Clinton.

Reliability. I don’t think reliability is a differentiator between the two major players. Each probably have reasonable track records.

Reliability Score: tie.

Intimacy. In person, as individuals, both Clinton and Trump are quite personable.  But in their public persona – and by her own admission – Clinton has never managed to project intimacy. She is wooden, stiff, provoking mainly winces and eye-rolls.

Trump – as well as Bernie Sanders – both score much higher on intimacy. Sanders’ frumpiness and evident unprofessionalism make him appear genuine. For his part, Trump’s ability to voice the unspoken fears in so many people connect on a visceral, even subconscious, level.

Intimacy score: Advantage Trump (and Sanders).

Self-orientation. At first blush, Trump might appear the epitome of high self-orientation. He is not only self-promoting, but self-obsessed. But he is so open and unapologetic about his self-focus that it doesn’t hurt him (at least with his core constituency). Intimacy trumps self-orientation.

With Clinton, there is a strong sense of self-serving, disingenuous deception. And the perception of high self-orientation colors voters’ perception of all the other factors as well. If we think someone is highly self-oriented, then we suspect the truth of what they say, are skeptical of their track records, and are skeptical about portrayals of intimacy.

Self-orientation score: Advantage Trump.

If this quick profiling makes sense to you, let me add some more data. 70,000 people have taken the TQ Trust Quotient Self Assessment, based on the Trust Equation (you can take it too). You can read a full description of the results in our White Paper: Think Expertise Will Create More Trust? Think Again, but here’s a headline.

The most powerful factor of the four is not Credibility – which most people in business think – but Intimacy.

It is not surprising that Clinton is having trouble getting traction: she’s on the losing end of the most powerful factor, intimacy. She’s playing her best hand – credibility – but it’s not working. And there’s a lesson in that for all of us.

(By the way, thanks for long-time reader Martin Dalgleish for inspiring this particular blogpost)

 

 

 

 

 

That’s Not a CSF – That’s Just a KPI!

That's not a CSF – I'LL show you a CSF!!

I had a conversation with BigCo., Inc. They want their B2B salespeople to become trusted advisors.

They felt (correctly) that greater trust levels with their customers would result in greater intra-customer market share,  and greater profitability. And they’re right.

But then they described their implementation plan. It consisted of breaking down the objectives into finer and finer components, matching them up with accountable org units. Pretty standard practice.

As we dug deeper, a pattern emerged. The higher penetration levels, for example, were broken into more sales calls, more proactive ideas, and greater time spent up front.  On the face of it, that sounds perfectly reasonable: if penetration were to increase, you’d probably see these changes in activities.

Confusing Cause and Effect

The problem is – simply increasing the number of sales calls won’t do a thing; they have to be good calls. Simply offering more ideas won’t do a thing; they have to be decent ideas. Simply spending more time up front won’t do a thing; the time has to be well-spent. And simply assuming good calls, decent ideas, and well-spent time does not make it so. 

I know, it sounds perfectly obvious in the telling.  But I’ve found that BigCo’s story (actually a composite of several clients) is very common. It may even be the norm.

BigCo has managed to confus KPIs (key performance indicators) with CSFs (critical success factors). They have confused correlation with causation.  They have confused measurements with the things being measured. And since we live in a management world that uncritically worships metrics (“if you can’t measure it you can’t manage it”), this confusion has critical and strategic implications.

Especially when you’re trying to implement a values-driven strategy – like becoming trusted advisors.

Measurement and Management

Just because something looks obvious in the rear view mirror doesn’t mean it was obvious when you first came up on it. Case in point: BigCo’s flawed logic in their approach to trust-based selling.

Increasing penetration requires more sales calls, they thought; and they’re probably right. Their mistake lay in thinking that “more sales calls” was a cause. It’s not – it’s an effect.

“More sales calls” may be a KPI, but it’s not a CSF. It may be an outcome, but it’s not a driver. “More sales calls” is a metric – it is not the thing that “more sales calls” is intended to measure. That “thing” is something like “more high quality interactions driven by mutual curiosity.”

This confusion between actions and measurements, causes and effects, KPIs and CSFs, is not only common, it’s becoming rampant. It’s a real issue not only for old-line businesses, but for new era businesses as well. Let’s look at some examples.

Gaming the Numbers

We’re all familiar with the salesperson who knows how to tweak an imperfect system to maximize his commissions at the expense of, say, the company’s gross margins. “Hey, I’m just following the incentives you built in.” That salesperson seized on a metric that imperfectly measured the company’s  intended sales behaviors. (The proper management response would be not to change the metric, but to insist on a higher set of principles that overrule one misguided number).

Next time you get a customer service operator on the line, check to see whether they conclude by saying something like, “May we say that I gave you excellent customer service today?”  You are experiencing a system that is driven by metrics to the point where operators shamelessly beg for ratings.   The metrics have been pimped out to serve a goal other than the customer service they were meant to measure.

See for yourself. Go to Amazon, and search for books under any significant topic you like (e.g. sales). Make sure you’re sorting on relevance. It’s amazing how many books are rated over four stars (out of five). The reason is simple: we have been taught to look for ratings. Of course, the emphasis on ratings suborns all kind of perjury, misleading, and even outright falsehoods.

It’s not just books. Look at the flood of ‘recommendations’ on LinkedIn. Look at the massive follow-me-I-follow-you dynamic on Twitter and other media.  Or just look at your own behavior; what do you do when a friend asks you to rate a book, to promote a blogpost, or to recommend them. In Dave Eggers’ 2013 best-seller The Circle (still #2992 on Amazon as I write this – another metric), there is monstrous grade inflation on all metrics in his Facebook-Google fictional internet firm of the future.

Much of this comes down to our obsession in business with metrics. It goes back to the invention of the spreadsheet and the success of books like Reengineering the Corporation.  All numbers all the time are our secular business religion.

The Wages of Confusion

The “so what” is big indeed. Assume that any metric, almost by definition, has to be a pale reflection of the “thing” that is to be measured. We accept anniversary gifts as tokens of our love; market share as an indicator of competitive success; and, in the case of BigCo, numbers of sales calls as indicators of trusted advisor relationships. But we all know an anniversary gift does not a marriage make.

The only way to become trusted advisors to your customers is to gain the trust of your customers. You do not cause trust by increasing the number of sales calls; rather, greater trust causes more invitations for you to call on prospects. Doing the dishes doesn’t cause a great marriage; instead, a great marriage results in you doing the dishes willingly.

Confusing KPIs with CSFs causes KPIs to be artificially inflated. We know this intuitively, and so we discount them – while still trying to get higher scores on more of those discounted-value KPI metrics. We all know the game is rigged – but we keep playing it faster and faster.

What’s at stake is nothing less than how we implement things like “better client relationships.” You don’t get there by measuring metrics and deluding yourself that you’re addressing root causes. You get there only by understanding what it takes to interact with your very human customers – and then doing it.

Do that, and the numbers will take care of themselves.

This article first appeared in RainToday

 

The Math of Low Trust

Trust in business has declined in recent years. One reason why can be demonstrated with a bit of math.

Assume two streams of income, with a net present value calculation for each. (I’ll use a 10% discount rate to simplify). Income stream A has a big payment in year 2 and then pays slightly more per year – but only for 5 years, after which it all ends.

Income stream B is steady and solid, giving less income per year – but lasting 8 years.

NPV Chart

Which income stream do you choose? If you’re a dutiful MBA or financial manager, then in theory you choose B, the one with the higher NPV. In fact, in the real world, stream A is chosen far more often – for two reasons.

Reason 1. What if the example were ended after 7 years, instead of 8 years? In that case, the NPV of Income Stream B would drop to $44.72 – so presumably you’d choose Stream A, which is  unchanged at $46.17.

Timeframe makes a difference. If the average time you spend in a job is less than 8 years, and you are a rational self-maximizing business person, you’ll choose a far shorter timeframe in which to maximize your performance, because that’s what you can control. And these days, it’s more like 2 years than 8.

Reason 2. In the above example, the unspoken assumption is that it is, in fact, a solitary single example. But assume there are thousands of investment opportunities out there, with very similar payoff characteristics. In which case the smart thing would be to take Income Stream A – and then sell it after two years.  Then go find a new Income Stream A in which to invest your profits, and do it all over again. That way you’ll vastly out-perform either strategy, in virtually any time frame.

Or – would you?

Trust and Net Present Value

What’s this got to do with trust? Think back to Walter Mischel’s famed marshmallow study on deferred gratification. We do not trust people who have no self-will, who cannot defer their desire for instant gratification, because they are not in charge of their own desires. But that’s just one marshmallow incident; the rationale doesn’t go beyond Reason 1 above. What happens when one’s choices can be made over and over again?

That pattern – endlessly taking short-term gratification and jumping off onto a new high-then-low curve – is a very familiar one. It is what characterizes alcoholism, addiction, and it explains why junk food sells. “Just one more drink; one more cigarette; one more Frito. I’ll quit tomorrow, honest.”  But there’s always another drink at hand, and cigarettes and Fritos are ubiquitous.

The connection to business? Easy. Think about the obsession with quarterly earnings. Think about Wall Street’s “IBGYBG” mantra (I’ll be gone, you’ll be gone – do the deal). Think sales quotas, weekly P&Ls, constantly refreshing online metrics for performance. A myriad of new front-end loaded opportunities for instant gratification. Running a business this way perverts strategy in favor of a series of opportunistic NPV calculations.

Business Since 1970 – One Major Trend

Biggest trend of the last 40 years?  An obsession with markets. We have pursued, especially in finance, the grail of frictionless markets, believing that the Invisible Hand will save us by converting our individual selfishness into collective good.

It’s a crock. What markets have also done is encourage NPV calculations everywhere, all the time, and everything is monetized so we can compare them. There’s always another front-end loaded curve to buy into. Buy it and flip it. Invent a new business and IPO it before it goes profitable. IBGYBG. Markets – abetted by modularization and outsourcing and communications – have enabled massive short-termism in business.

The game works until the game doesn’t work. It works if you assume your grandchildren’s world will not suffer by your focus on short-term NPV enhancement. It works if you assume that a culture of instant monetization will beat Chinese strategies from a civilization accustomed to thinking in centuries.  It works if you assume that long-term good is achieved by means of constant short-term optimization.  But it isn’t.

Trust and Short-Termism

There’s  a reason that one the Four Trust Principles is “Focus on the medium-to-long term, not the short term; develop relationships, not transactions.” It’s because trust is born from long-term commitments; the confidence that the other party is after something besides their own instant gratification. Short-termism is perhaps the most perniciously anti-trust business phenomenon of our times. We have been poisoning our corporate cultures through a relentless focus on markets, monetization, analytics and processes.

Those are not the basis of trust. A commitment to long-term principles and relationships is the basis of trust.

Who Do You Trust? Honesty Ratings by Career

Periodically, someone does a survey on the trustworthiness of various professions. Last month it was time for Gallup to do their annual poll of “Honesty and Ethical Standards of Professions.”

All the fun happens at the bottom of the list. The good news for politicians is that their ratings were up from last year. The bad news is that puts them in next to last place, just ahead of car salesmen.

Over the years, the ratings of engineers have gone steadily upward. Pharmacists and doctors rate near the top of the lists, as they have for years.

But heading the list of most honest and ethical professions are – nurses. As the article puts it:

[nurses] have scored at the top of all professions every year since they were first included in the list in 1999 — apart from 2001, when Gallup asked about “firefighters” on a one-time basis after the Sept. 11 terrorist attacks. Nurses receive a 10-percentage-point higher rating than pharmacists, who in turn are five points above medical doctors.

This finding makes perfect sense if you’ve followed the findings of Trusted Advisor Associates’ Trust Quotient Assessment, outlined in the White Paper – Think More Expertise Will Make You More Trusted?  Think Again.

The Trust-Power of Intimacy

These findings are based on the four factors of the Trust Equation – credibility, reliability, intimacy, and self-orientation. Based on 12,700 people who took the assessment (since grown to over 25,000), it turned out that the most powerful of the four factors was – intimacy.

High overall trust scores were more highly correlated with high intimacy scores than with any other component. (Intimacy in this study was defined as giving others a sense of security and willingness to confide in them).

Interestingly, women scored as more trustworthy than men. And almost all of the higher ratings for women were due to women’s higher score on one of the four factors – intimacy.

Back to nursing. Ask yourself: which of the four trustworthiness factors are most associated with nursing? Intimacy comes top of mind. We are, figuratively and literally, naked before nurses, and we trust them. It makes perfect sense that nurses consistently outrank all others in most-trusted-professions surveys.

The Soft Stuff is the Hard Stuff

If you’re interested in improving trust in your organization, or in becoming more trustworthy as an individuals, the best route there lies not just through advanced degrees, track records and testimonials – it lies in increased intimacy.

Intimacy correlates with a group of what’s commonly known as “soft” attributes – emotional intelligence, listening, empathy.  Want to move the needle? Show some hard results? This is how you do it. The soft stuff turns out to be the hard stuff.

Trust Metrics: Breaking It Down

How can you measure trust?

Consider a simple equation:

Trusting  x  Trusted  =  Trust

In other words: if someone is trusting enough to take a risk (the trustor), and if someone else is trustworthy enough to be worth that risk (the trustee), then when the two parties are a “match” – and you get “trust.”

Suppose you could quantify each.  Note that there is more than one way to get the same result for “trust.”  For example:

  • a “trusting” rating of 8/10 and a “trustworthiness” rating of 3/10 might give a “trust” score of 24 out of 100 – 8×3;  and
  • a “trusting” rating of 4/10 and a “trustworthiness” rating of 6/10 would give the same “trust” result – 4×5, or 24.
But what does this mean?

Most of the Data Doesn’t Support Decisions

Most of the trust data out there (think Edelman Trust Barometer, or Pew Research) isn’t about either “trusting” or about “trustworthiness.” It’s simply about the end result, trust. And that’s not very enlightening.

Suppose we get a series of data points about trust, and that they show a decline over time, from 26, to 24, to 20. Does that mean that the trustors got more gun-shy and less willing to trust?  Or does it mean that the trustees became more shady, and less trustworthy?

Measuring only the result – trust – is like saying the results of the Yankees vs.Tigers game was 3-2 – without telling you the winner. It’s like saying that the average household income of a small town is $500,000 – without mentioning that one of the residents is a billionaire. It’s like saying that unemployment is down – without mentioning how you count those who are not looking.

If you were to pass laws about regulation – you might want to know the driver of decreased trust. If you were building a marketing campaign – you might want to know which factor shifted. And if you were observing a pattern between two firms,  you might want to know why trust declined – was it because of less trusting, or because of less trustworthiness?

There’s a lot more to be said about this rarely observed but simple distinction: let me just point out that there are in fact some sources of data that are actionable and help us get at causal drivers, rather than just identifying results.

The Trust Matrix

The matrix below shows some of these relationships.

1. In the upper left box – Individual Trusting – academics are well aware of the General Social Survey, a fifty-year database with an impeccable pedigree, which permits some fascinating conclusions about our propensity to trust others. Hint: it’s gone down. We’re becoming more and more suspicious in principle.

2. In the box Trustworthy Individuals, the pre-emininent database may be my own company’s Trust Quotient. With over 25,000 data points, a time-proven insight called the Trust Equation, we can now state categorically which gender is more trustworthy, which of the four trust factors are harder drivers of trustworthiness, and the relationship of trustworthiness to industry.

3. What about the critical question of organizational trustworthiness? This is a question  we keep trying to answer by reference to trust surveys, which are unable to yield the answer.  The best source I know of is Trust Across America’s database of publicly traded US companies (they’re working on expanding it). They have a composite definition well-grounded in commonsense and objective databases, and some compelling data about the correlation between corporate trustworthiness and economic performance.

4. The bottom left box – an organization’s propensity to trust – is something for which I’m not aware of any data.  Would someone please correct me if I’m in error?  My working hypothesis is that this box has declined considerably.

JP Morgan himself may have lent on the basis of character, but the industry he left behind lends only on secured assets. Except, of course, when they lay off risk through ever-increasingly complex transactions.

Companies routinely won’t even trust small subcontractors, insisting that they self-insure against things like falling on sidewalks. It seems to me that corporations consider a propensity to trust to be roughly tantamount to stupidity. It’s hard to be a trusted organization if you systemically and systematically distrust your stakeholders.

5. Finally, the last column – measurements of trust itself – needs conceptual clarification.  When we look at data that says “trust is down,” there are four meanings.  We might be referring to trust between individuals, trust between organizations, or trust between organization and individual (with two variations depending on which is trustor and which is trustee).

To Mean What You Say, Say What You Mean

Any of us – not just researchers or academics or survey-takers – can contribute significantly to the discussion of trust simply by being clear about what we mean. If you want to say that bankers have become banksters, then point to data about the decline of trustworthiness on the part of banks – not to composite data that blurs the trustor-trustee distinction.

If you want to say that trust is up in the sharing economy, then use data that talks about the propensity to trust, not just the end result of trustor-trustee interactions.

I have a feeling that some significant chunk of the debate about trust could be improved by simply using clearer language to reflect clearer thinking.