Becoming a star engineer—Part I

We have a story we tell about exceptional engineers. They’re the ones who arrived already exceptional—unusually sharp, with an instinct for abstraction that most people simply don’t have. The job of management, in this story, is to identify them early and get out of their way.

Robert E. Kelley’s research, published in IEEE Spectrum in October 1999, suggests this story is wrong. Not just partially wrong—structurally wrong.

Kelley and his colleagues at Carnegie Mellon studied over a thousand engineers across Bell Laboratories, 3M, and Hewlett-Packard, trying to identify what distinguished the acknowledged stars from the solid performers. They tested cognitive ability, psychological profiles, social skills, and organizational factors. The initial results were uncomfortable: there were no quantifiable differences. Stars and average performers looked the same on paper.

This forced a different question. If stars aren’t distinguished by what they have, maybe they’re distinguished by what they do.

The study introduced two new hires—composite portraits drawn from the research—to illustrate the point. Henry and Lai joined the same team with similar credentials. Henry focused on becoming technically indispensable. He worked long hours, mastered every system he could access, and kept to himself. His code was excellent. He believed the quality of his work would speak for itself.

Lai took a different path. She balanced technical work with building relationships—volunteering to help colleagues debug problems, identifying gaps between team responsibilities and filling them, making herself useful in ways that crossed formal role boundaries. Her individual technical output was slightly below Henry’s.

Eight months in, Lai was rated the stronger performer.

The uncomfortable lesson isn’t that technical skill doesn’t matter. It does. But technical skill in isolation is necessary, not sufficient. What Lai understood—and Henry didn’t—is that engineering work is embedded in a social system. The value of a solution depends partly on whether the organization can absorb it, trust it, and act on it. Building that trust requires the kind of lateral investment Lai made and Henry skipped.

The implication is both encouraging and demanding. Encouraging because it means star performance is learnable—there’s no genetic lottery you either won or lost. Demanding because it means the work doesn’t stop at the terminal. Part II explores the specific strategies the research identified.