Cowart Consulting Group

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Cowart Consulting Group

Cowart Consulting Group uses the science of psychology to produce dramatic, measurable business results.

We assist our domestic and global partners on issues of selection, individual and team performance, and people systems, providing effective consultation and expert advice on a myriad of business challenges and people performance issues. Our team of licensed Psychologists has dedicated their careers to understanding leadership, motivation, and performance - all concepts that will powerfully influence your business directives. Through our proven impact and experience in the field, we have forged partnerships with a wide variety of clients, ranging from family businesses to multinational corporations.

10/16/2026

“It’s kind of fun to do the impossible.”
-Walt Disney

Last night, Elon Musk posted six seconds of the new Tesla Roadster flipping through the air over a row of parked cars and landing like nothing happened. His caption: “Turns out the future does have flying cars.”

The comments came fast...
Not practical.
Who needs that?
You can’t take it to the grocery store.
Where would you even park it?

Notice what every one of those objections has in common... they’re all measuring the Roadster against what a car is expected to be:
Gets you from A to B.
Fits in a garage.
Behaves itself on the highway.
Does not fly.

Psychologists call mental expectations of how things ought to be schemas. Schemas are the mental templates we use to sort the world quickly so we don’t have to think everything through from scratch. They are incredibly useful, yet they’re also why the first reaction to something new is so often one of defense rather than curiosity and wonder.

The people who the designed and built Roadster this weren’t asking how to make a better car.

They were asking what a car could be if nobody had told them the rules.

That’s a different question... and it only gets asked by people who are having enough fun to play with the template instead of defend it.

Work runs on schemas too:
What a leader looks like.
How a meeting should go.
What counts as an idea versus a distraction.

Practicality matters. It just shouldn’t get the first word.
Give curiosity a chance. Have some fun at work.

So, a Friday question for you: could your work use a kickflip?

10/09/2026

16 Factors: Foundations of Evaluations

CLEAR Screen, launched in 2011, is an online personality preference assessment that takes about 20-30 minutes to complete. The 16 primary trait scales of CLEAR Screen are alternate forms of scales measured by the Sixteen Personality Factor (16PF) questionnaire. When the 16PF, itself, was launched in 1949, it was the first personality test based on systematic research into dimensions of human personality. Conducting a series of factor-analytic studies of behavior ratings, Raymond B. Cattell reduced the basic set of personality traits to 16 factors with dozens of subsequent studies supporting this structure.

The foundations of CLEAR Screen are 16 similar primary traits, yet CLEAR Screen measures much more. In various combinations and proportions, these primary traits provide insights into leadership potential, job function position fit, cognition, coachability, watchouts, boosters, and work motives. Such insights have demonstrated value for hiring, promotion, and development decisions. Using CLEAR Screen and its associated professional consultation services, client organizations have experienced a median 12% annualized employee attrition rate and a median $49 to $1 return on investment ratio.

For proven evaluation of candidates and incumbents alike, contact [email protected].

*Increase Retention *Enhance Safety *Improve Performance.

10/05/2026

Organizational L&D Myth Busting:

One of the most persistent beliefs in organizational learning is that people have distinct learning styles (e.g., visual vs. auditory), and that instruction designed to match those styles produces better outcomes. It’s a reasonable-sounding idea…it is also one of the most thoroughly debunked findings in applied psychology.

The research includes dozens of controlled studies on whether matching instruction format to a learner’s preferred style improves performance. The consistent answer is that it does not. In this case, preference does not predict performance. People may enjoy receiving information visually vs. auditorily, but that enjoyment does not translate into knowledge retention, transfer, or application. What actually predicts those outcomes is the nature of the content itself, the quality of the instructional design, and the conditions under which they are expected to apply the learnings.

Many people have experienced this myth in action, as learning style frameworks have shaped Learning & Development investments for decades. Significant spending has been justified to build curricula and train multiple cohorts based on a model that has no empirical foundation. The opportunity cost of directing resources toward learning style accommodation is essentially diverting it from the design factors that actually predict meaningful outcomes.

Those design factors that are actually well supported include:
• Spaced practice rather than massed learning
• Retrieval-based approaches over forced review
• Feedback that is specific and tied to application
• Learning experiences designed around the cognitive demands of the actual work

The myth survives because it is flattering in that it tells people that their preferences matter, but that, unfortunately, does not make it useful. Effective learning starts from a different, evidence-based premise about how humans actually acquire and retain complex skills, regardless of how comfortable it feels in the moment.

09/18/2026

"There's an inherent paradox around learning: Anxiety inhibits learning, but anxiety is also necessary if learning is going to happen at all." - Edgar Schein

Most people think resistance to change is human stubbornness. It's not. It's actually just math.

Schein describes this with two concepts, survival anxiety (the feeling that something has to change) and learning anxiety (the fear of what it'll cost you to actually change it). Change happens when the first one exceeds the second.
That's it. That's the formula.

But, most organizations invert the math. They crank up the survival anxiety. More pressure, more urgency, more "or else" subtext. And, it backfires because threatened people are not trying to learn... they are too busy avoiding and defending.

Look at the AI panic consuming the news cycle this week. Researchers and former Anthropic employees warning it could end humanity, calls for emergency regulation, doomsday essays, congressional demands for action. Survival anxiety is at an absolute fever pitch... nearly every executive in America has survival anxiety about it how AI might render their business (or their own roles) obsolete. They know they need to figure it out. But, the learning anxiety is enormous. Asking a basic question about how it works feels like admitting you're a Luddite dinosaur.

So instead of learning, leaders posture. They approve budgets for tools nobody uses. They hire AI officers and then don't empower them. They nod along in board meetings and ask AI about itself afterward. The survival anxiety is sky-high, but nothing's actually changing because nobody feels safe enough to say "I don't understand this yet."

The organizations that are actually going to win are the ones willing to say "I don't know what I don't know." They're making mistakes. Experimenting. Iterating. Getting it wrong and trying again. They're not waiting for the AI apocalypse to arrive, and they're not expecting a perfectly wrapped solution to arrive with a bow and an answer.

They are, quite literally and quite simply, just learning.

09/10/2026

The Flop of AI Slop

Artificial intelligence (AI) is often promoted as a tool for creating original content, solving complex problems, and accelerating human creativity. AI can be effective at organizing, summarizing, translating, reformatting, and retrieving patterns from existing information. Treating it primarily as a tool for synthesis, rather than as an independent generator of knowledge, leads to more responsible and reliable outcomes.

AI can process large volumes of information quickly, identify recurring themes, produce document drafts, and adapt material for different audiences. It can improve productivity, support accessibility, and assist professionals with routine tasks. Used carefully, it functions like an advanced research aide or editorial assistant, helping people organize information more efficiently.

However, AI-generated material can become “AI slop”: content that is abundant yet largely devoid of context and meaning. Because AI predicts likely sequences of words rather than independently verifying facts, it can reproduce errors, bias, clichés, and/or outdated claims. Its apparent confidence (and eagerness to please its users) can conceal uncertainty. Moreover, excessive reliance on automated generation can weaken human judgment, originality, and accountability. Copyright infringement and privacy issues also remain serious concerns related to AI use.

Examples of premature full-scale adoption of and over-reliance on AI leading to negative outcomes include erroneous legal arguments submitted by lawyers, Ford Motor Company’s recent quality woes, and Pizza Hut’s reported franchisee frustration and customer dissatisfaction following AI implementation.

AI should be approached less as an expert and more as an instrument. It can retrieve, summarize, compare, and reorganize information, yet humans should supply the purposes, judgments, and final approvals. Otherwise, the risks of producing “AI Slop” increase dramatically.

For human-driven professional insight into, and oversight of, your organization’s talent evaluation and development processes, contact [email protected].

08/28/2026

Fatalism as a measurable risk attitude

Aviation named this decades ago. When the FAA built its human factors curriculum, it identified five attitudes that get pilots killed. Four of them are loud: anti-authority, impulsivity, invulnerability, macho. The fifth is quiet. Resignation. "What's the use."

Resignation does not present as a risk attitude. It presents as the guy who stopped filing near-miss reports. As the crew that quit pushing back on a bad procedure two years ago because nobody ever changed it. It looks like compliance, which is exactly why it survives an audit.

We screen for it. In our watchout framework it surfaces as Deflated: prone to discouragement, low enthusiasm, low energy for pushing on anything. And it is measurable, which matters more than it sounds. Most organizations treat fatalism as a mood, something in the water at a site with a rough history. It is not a mood. It is a stable disposition, and it predicts whether a person will intervene when they see something wrong.

The operational consequence is specific. Impulsivity and machismo produce incidents you can trace afterward. Resignation produces the incident nobody reported the setup for. It removes the last human check in the system, quietly, and the system looks fine right up until it does not.

What makes this a leadership problem rather than a screening problem: resignation is learned. Nobody arrives that way. People get there by raising something three times and watching nothing happen. The measurable attitude in the individual is often a lagging indicator of the supervisor above him.

Screen for it. Then go fix whatever is manufacturing it.

08/27/2026

The supervisor as the variable

Gallup put a number on something most operators already suspect. Managers account for at least 70% of the variance in employee engagement scores across business units. Same company, same pay scale, same posters in the breakroom. Different supervisor, different outcome.
Gallup

That figure gets misread constantly. It does not mean your boss controls 70% of how you feel about your job. It is a between-team measurement. It says that when you line up the engaged work groups against the disengaged ones inside a single organization, most of what separates them sits with the person running the group.

Our Climate and Culture Survey measures Supervision under Mood, and Development and Resources under Engagement. What we see repeatedly is that the Supervision score moves first and the Engagement scores follow. A crew can have the training budget and the equipment and still read low on Development, because the person who decides who gets tapped for the next opportunity is the supervisor, not the budget.

Which is why "we have an engagement problem" is usually the wrong diagnosis. Engagement is not issued at the corporate level and then degraded on the way down. It is manufactured locally, shift by shift, by whoever runs the shift. When a site shows a 30-point spread between its best and worst work groups, the culture is not the variable. The org chart is.

The structural problem: most organizations promote supervisors on technical mastery and then measure them on engagement. Those are different capacities. One does not produce the other, and no amount of company-wide programming closes the gap.

If you want the engagement number to move, stop surveying the organization and start assessing the supervisors.

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Roswell, GA

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http://www.cowartconsultinggroup.com/

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