People Frameworks

How Leaders Should Think About People

Leadership rarely fails because leaders lack intelligence, experience, or even effort. One of the chief ways it fails is through the use of the interpretive shortcuts leaders take when trying to understand human behavior under pressure.

When things go well, leaders tend to credit strategy and culture. When things go poorly, they often default to stories about people. Someone didn’t care enough. Someone wasn’t capable. Someone made a bad decision. These explanations feel satisfying because they’re simple, but they are often wrong, and once institutionalized, they quietly rot organizations from the inside.

Over time, I’ve come to believe that leadership is as much about managing the mental models through which leaders interpret people as it is about managing people directly. Those models determine how leaders respond to underperformance, how much autonomy they allow, how they react to failure, and ultimately whether their organizations learn or calcify.

What follows are several frameworks I’ve found useful for thinking about people from a leader’s perspective. They are grouped into three categories: Foundational Assumptions, Interpreting Behavior, and Making Meaning From Failure. None of these frameworks eliminate accountability. They do, however, dramatically change what leaders hold people accountable for.

Foundational Assumptions

Assume Competence and Positive Intent

One of the most powerful, and most fragile, assumptions a leader can make is that people are generally competent and operating with positive intent. Put more bluntly: no one comes to work hoping to fail or to purposely mess up.

This assumption is easy to agree with in the abstract and remarkably difficult to hold onto when results disappoint. Under stress, leaders often revert to character-based explanations because they are fast and emotionally satisfying. Someone didn’t care enough. Someone wasn’t trying. Someone just isn’t very good. These explanations absolve systems and elevate judgment, but they rarely lead to improvement.

Douglas McGregor’s Theory X and Theory Y captured this divide decades ago. Theory X leaders assume people are lazy and must be controlled. Theory Y leaders assume people want to do good work and will rise to responsibility if the environment allows it. Most leaders don’t consciously choose Theory X, but pressure has a way of forcing reversion. When stakes are high and time is short, trust feels risky.

Assuming positive intent does not mean lowering standards or excusing poor outcomes. It means changing the starting point of inquiry. Instead of asking “Why did they fail?”, leaders ask “What made success difficult here?” That shift redirects energy from blame to diagnosis. Diagnosis scales. Judgment does not.

Organizations built on suspicion eventually train people to protect themselves rather than contribute fully. Organizations built on assumed competence tend to surface problems earlier, because people believe they will be met with curiosity rather than punishment. Over time, this assumption becomes self-reinforcing. Leaders who assume people are capable tend to build systems that make them so.

If Someone Isn’t Performing, They Know It

A surprisingly common leadership mistake is assuming that performance problems are primarily awareness problems. Leaders behave as though feedback is revelatory, as if the person on the receiving end had no idea things weren’t going well.

In reality, most people struggling at work are acutely aware of it. They know they’re behind. They know something isn’t working. What they often don’t know is how serious the issue is, what “good” actually looks like, or whether it’s safe to admit confusion or ask for help. Silence, in these cases, is rarely ignorance, it’s risk management.

This is why so much feedback fails. It treats awareness as the missing ingredient when clarity is usually the real problem. When leaders assume people are unaware, feedback becomes didactic and one-directional. When leaders assume people already know, the conversation becomes collaborative. The leader’s role shifts from delivering a verdict to helping close a gap.

In their book, Nine Lies About Work, Marcus Buckingham and Ashley Goodall argue that feedback should focus on outcomes and expectations rather than personal deficiencies. This aligns with what most people actually need: a clearer picture of what success looks like and what constraints are preventing it.

Leaders who internalize this framework approach performance conversations differently. They spend less time explaining that there is a problem and more time exploring why the problem persists. That distinction matters. One approach produces defensiveness. The other produces engagement. Over time, teams learn that struggling is not a moral failure, but an invitation to problem-solve.

Interpreting Behavior

Behavior Always Has a Backstory

Leaders are paid to notice behavior, but they are rarely given full visibility into the constraints shaping it. What leaders see are outcomes and moments: a missed meeting, a blunt comment, a half-finished deliverable. What they don’t see are the tradeoffs, interruptions, incentives, and cognitive load that produced those artifacts.

The danger is not observation itself, but interpretation. Daniel Kahneman, in his book Thinking, Fast and Slow, describes the fundamental attribution error as our tendency to over-attribute behavior to character while underweighting context. In leadership, this bias is particularly destructive because it masquerades as insight. A single incident becomes a story. A story becomes a label. A label becomes a reputation.

This framework demands restraint. It asks leaders to slow down their narrative impulse and gather more signal before drawing conclusions. Patterns matter. Moments rarely do. Leaders who react to isolated data points tend to create volatility, constantly whipsawing teams in response to noise. Leaders who wait for patterns create stability, because their responses feel fair and predictable.

Understanding that behavior has a backstory doesn’t mean excusing it. It means explaining it accurately. Accurate explanations lead to better interventions. Inaccurate explanations lead to performative fixes that look decisive but change nothing.

Trust by Default, Verify by Exception

Many leaders equate visibility with effectiveness. Knowing what everyone is doing feels like control, and control feels like leadership. Unfortunately, this model breaks down as soon as organizations grow beyond a handful of people.

Control scales linearly. Trust scales exponentially.

David Marquet’s experience commanding the USS Santa Fe, captured in his book Turn This Ship Around!, illustrates this vividly. Trained in the traditional “know all, tell all” leadership model, Marquet initially tried to lead through centralized decision-making. But aboard a nuclear submarine, where complexity is high and error margins are small, this approach created bottlenecks and increased risk.

Marquet reversed the model. Instead of issuing orders, he communicated intent. Authority moved to the people closest to the work. Verification didn’t disappear, but it became conditional, triggered by signals rather than anxiety. The result was not chaos, but extraordinary performance. Morale improved. Retention soared. The Santa Fe went from worst to first in the fleet.

The lesson is not that leaders should abdicate responsibility, but that they should be deliberate about where control adds value and where it subtracts it. Trust by default doesn’t mean blind trust. It means assuming competence until evidence suggests otherwise. Over time, this approach frees leaders to focus on direction rather than supervision and allows organizations to move faster with fewer handoffs.

Constraint Over Character

When performance disappoints, character explanations are tempting because they are simple. They provide emotional closure and a clear villain. Unfortunately, they are also usually wrong.

Eli Goldratt’s Theory of Constraints reminds us that systems limit performance far more often than individuals do. If someone consistently struggles, the more productive question is not “What’s wrong with them?” but “What friction are they operating under?”

Constraints can be structural, procedural, or cultural. They might be invisible to the person experiencing them or invisible to leadership. Either way, fixing constraints improves performance at scale.

Leaders who default to character explanations often create learned helplessness. People stop trying to improve systems because they believe outcomes are predetermined by personality rather than design. Leaders who default to constraint-based explanations create agency. Problems become solvable rather than personal.

This framework doesn’t deny individual responsibility. It contextualizes it. People still own their outcomes, but leaders own the environment in which those outcomes are produced. Organizations that understand this distinction improve faster and burn out fewer people along the way.

Making Meaning From Failure

Most Things Have an Upside

Leaders inevitably face failure. The question is not whether things will go wrong, but how leaders interpret those moments when they do.

Amy Edmondson distinguishes between blameworthy failures and intelligent failures, those that occur in the pursuit of learning and innovation. Organizations that treat every failure as a moral lapse quickly train people to hide information. Organizations that treat failure as data learn faster, because problems surface earlier and more honestly.

Seeing the upside in failure is not about optimism or spin. It is about optionality. What did this reveal? What assumption did it invalidate? What constraint did it expose? Leaders who ask these questions turn setbacks into assets. Leaders who don’t often repeat the same mistakes with better slide decks.

This framework also changes emotional tone. Failure stops being an identity threat and becomes a learning event. Over time, teams become more willing to take responsible risks, knowing that outcomes will be evaluated thoughtfully rather than punitively.

People Are Rational, Locally

When behavior appears irrational, it usually isn’t. It is simply rational within a context the leader does not fully see.

Dan Ariely’s work in behavioral economics shows that people respond predictably to incentives, information, and framing, even when those responses seem illogical from the outside. In organizations, this plays out constantly. People optimize for what they believe is rewarded, not what leaders say they value.

If collaboration is praised but individual heroics are promoted, people will compete. If long-term thinking is encouraged but short-term metrics drive compensation, people will optimize for the quarter. The system is always speaking, whether leaders intend it to or not. People are capable of noticing these incentives in the smallest amount.

This framework forces leaders to confront uncomfortable truths about their own designs. When behavior doesn’t align with stated values, the problem is usually not communication. Instead it is often the incentives.

The Reflection Test

Before reacting to any behavior, there is one final test worth running: If I were in their position, with their information and constraints, would this choice make sense?

Edgar Schein describes this posture as humble inquiry. It does not eliminate accountability. It sharpens it. Accountability without understanding turns into punishment. Accountability with understanding turns into improvement.

Leaders who consistently apply this test build credibility. Their responses feel fair, even when decisions are hard. Over time, people stop managing impressions and start managing outcomes.

Closing Thoughts

The stories leaders tell themselves about people become self-fulfilling systems. Leadership, in addition to managing people, is about managing those stories or interpretations of behaviors.

Cynical explanations are often faster. They feel sophisticated. They provide emotional closure. But they are rarely the most accurate models of human behavior. Generous explanations, grounded in systems, context, and incentives, tend to produce better outcomes over time, not because they are kind, but because they are true.

The leaders worth following are the ones who choose their assumptions carefully, knowing that whatever they assume today will quietly become the organization they are leading tomorrow.