“American managers are stupid,” my correspondent offered, by way of explaining why so many ignore his perspectives.

I decided not to ask whether he meant that (1) all Americans are stupid and, by the laws of object inheritance and the transitive law of algebra, American managers, being Americans, are stupid; (2) American managers are stupider than the average American; or (3) it’s Sturgeon’s Law in action: 90% of everyone are stupid and that includes American managers.

To the best of my knowledge nobody has ever surveyed American managerial IQs to determine whether the mean is less than, greater than, or equal to 100 — IQ’s definitional IQ average. Also, IQ is a badly flawed metric.

Meanwhile, the American managers I’ve personally worked with have in general been a brighter than average lot. While employee dissatisfaction with management is both widespread and deserved, I’m pretty sure it isn’t because they are, as a class, dopes.

Which somehow or other brings us to this week’s topic.

Many companies conduct employee satisfaction surveys. Some are better than others, but I’ve yet to see any that move beyond warm fuzzies to the only metrics that matter in a market economy.

The KJR alternative: ask employees to express their satisfaction or dissatisfaction financially.

It will take only four questions:

Question #1: What percentage of your total compensation would you be willing to give up in exchange for a better manager?

Question #2: What is it about your manager that led to your answer to Question #1?

Question #3: What percentage of your total compensation would you be willing to give up in exchange for working in a better company?

Question #4: What is it about this company that led to your answer to Question #3?

Yes, yes, I know. The answers to questions 2 and 4 couldn’t be automatically tabulated, at least, not the first time you administer the survey. But which is more important — automated tabulation or useful information?

Even if you only ask questions #1 and #3, just knowing how much money employees would be willing to give up in exchange for a better work environment would give business leaders at all levels a lot to chew on.

Starting with this question: Does it matter?

It ought to matter a lot. It’s widely recognized that the best employees are at least twice as effective as average ones, and the gap is probably much wider than that.

The best employees are also the most mobile. Add to this another general-purpose factoid: Replacing a good employee costs the equivalent of about a year of compensation, counting recruiting costs, the costs of bringing new employees up to speed on their responsibilities, and the overall loss of team effectiveness as teams adjust to changes in their membership.

Do the math and it should be clear that losing your best employees is an expensive proposition.

And yet, I often run into companies whose employees privately tell me are utter meat grinders — horrible places to work. They have high employee turnover, as we’d predict, and yet they make so much money so quickly they have a hard time figuring out what to do with it all, and have over spans of decades.

How is this possible? The short answer is, beats me. The longer answer is nothing but speculation: The same management characteristics that make these companies bad places to work somehow make them resilient in the face of high employee turnover rates.

Take, for example, micromanagement. I’ve yet to hear anyone say they like being micromanaged. But whatever their flaws, micromanagers do know how to do the work they’re micromanaging. If they didn’t they couldn’t micromanage. And because they’re able to do the work, micromanagers can pick up the slack when an employee leaves.

Of course, picking up the slack adds pressure and workload, making the micromanager even less pleasant to work for.

Let the process play out for a few cycles and what you’ll get, I think, is a department staffed by mediocrities who can’t easily find better employment, run by managers for whom micromanagement is integral to how their department’s work gets done.

It’s a stable configuration. As long as the company does something else well enough to make it competitive in its marketplace, there are no forces in play to drive change and plenty in play to keep it as it is.

My guess is that similar dynamics govern other forms of stable, bad management.

If you’re one of the offending managers, please don’t take this as an endorsement of your management style. Explanation doesn’t equal approval.

And in any event, I’m just speculating. Maybe one of KJR’s more enlightened constituents has a better theory?

I suffer from cluster headaches. Every year and a half or so I live through a month or two of daily episodes of excruciating pain that calls for gobs of Excedrin, quite a lot of Sumatriptan, gratitude for the existence of automatic ice makers, and the inescapable sensation that I’m taking dumb pills.

No, I’m not looking for remedies, empathy, or sympathy. Let’s skip directly to pity.

Or skip it altogether. Now that I have your attention, let’s move on to pain’s relevance to your day-to-day working life.

Pain evolved to get our attention when something is wrong that needs fixing. Which is why migraines, cluster headaches and their kindred maladies are so annoying: The only thing that’s wrong is the headache itself.

Still don’t see the relevance?

Biologically speaking, pain is an indicator. It’s like a blinking light on a control panel that tells the brain something isn’t working the way it’s supposed to work. The brain needs this mechanism because the body is way too complicated for the brain to directly monitor all of its components.

So instead animal physiology includes receptors scattered throughout a critter’s anatomy. The brain doesn’t have to monitor. What requires attention calls for attention.

Only it’s easy to ignore a blinking light. Pain is designed to be hard to ignore. Pain says something isn’t working the way it’s supposed to work, so please do something about it RIGHT NOW!

KPIs (key performance indicators) and their metrics-based brethren are, for managers, what pain is for the brain. They’re a way for managers to know something needs attention without their having to directly monitor everything in their organization.

But (here’s the big tie-in! Drum roll please) … KPIs share both the blinking light’s and migraine’s limitations.

They’re blinking lights in the sense that when a KPI is out of bounds, it’s just a number on a report, easy to ignore in the press of making sure work gets out the door when it’s supposed to.

There’s nothing attention-getting about a KPI. It’s just a blinking light. Unless, that is, a manager’s boss decides to inflict some pain … perhaps “discomfort” would be in better taste … when a KPI is out of bounds.

KPIs can also be migraines, though, in the sense that it isn’t uncommon for a KPI to be out of spec without anything at all being actually wrong.

Migraine KPIs can happen for any number of reasons. Among the most important is the reason the first, and arguably best quality improvement methodology was called “statistical process control.”

Many KPIs are, that is, subject to stochastic variability, stochastic being a word every process manager should be able to use correctly in a sentence without first having to look it up on Wikipedia.

Sometimes a KPI is out of range because the effect it’s supposed to measure is the consequence of one or more causal factors that vary more or less randomly. Usually their variance is within a close enough range that the KPI is reasonably reliable.

But, stochasticism being what it is, not always. If the KPI looks bad because of simple random variation, the worst thing a process manager can do is try to fix the underlying problem.

The fixes can and often do push the KPI in question, or a different, causally connected KPI, out of range when process inputs return to normal.

As long as we’re on the subject of pain, you don’t have to have any for something to be wrong with you, which is why most of us have a medical check-up every so often, even when we feel just fine.

KPIs can be like this too. The IT trade is replete with managers who meet every service level they’ve agreed to and as a result think everything is fine when in fact it’s falling apart. Help desks are particularly prone to this phenomenon, because of a phenomenon the users to contact an offending Help Desk know about but the help desk manager doesn’t: Because they’re usually measured on ticket closures, help desk staff close tickets whether or not they’ve actually solved a user’s problem.

It’s the first rule of metrics: You get what you measure. That’s the risk you take.