The Anomaly Effect: Why Success Isn't Always Replicable

When the Los Angeles Rams hired Sean McVay as their head coach, many in the NFL were skeptical. How could a 30-year-old possibly handle such a demanding role? Yet McVay quickly silenced the doubters, demonstrating exceptional leadership and coaching talent. His success sparked a league-wide frenzy, as teams with head coaching vacancies began searching for their own version of McVay. Thus began the hunt for the "next McVay."

What followed was a wave of hires from the so-called “McVay Tree,” with teams hoping to replicate his extraordinary results. But many failed to recognize an important truth: McVay is an anomaly. There is only one Sean McVay.

In the hiring world, it’s common for organizations to look for leaders from successful teams. On the surface, the logic seems sound: winners win, and learning from winners should, theoretically, breed more success. This model extends beyond the boardroom, even to horse racing.

Take Secretariat, for example. Widely regarded as the greatest racehorse of all time, Secretariat's bloodline was expected to produce offspring with similar talents. Over his career as a stud, Secretariat sired 663 named foals, including 341 winners (51.4%) and 54 stakes winners (8.1%). While those numbers are impressive, none of Secretariat’s descendants came close to his legendary prowess. As great as Secretariat was, his offspring proved that his talent was unique—an anomaly.

This concept highlights the danger of misunderstanding what success truly represents. Organizations often overlook the contextual anomalies that make someone like McVay—or Secretariat—a one-of-a-kind talent.

Contextual anomalies are data points that seem extraordinary within a specific context but may appear ordinary in another. They are particularly common in time-series data, where certain values are expected only under specific conditions. Misinterpreting these anomalies can lead to flawed decision-making.

In the case of McVay, teams chasing his success failed to account for the unique factors behind his achievements. Similarly, Secretariat’s unparalleled dominance on the racetrack did not guarantee his lineage would replicate his greatness. Both serve as reminders that true anomalies are rarely, if ever, reproducible.

To make better hiring or strategic decisions, it’s critical to understand and account for contextual anomalies. Here are three steps to help:

1. Context Definition
   Clearly define and identify the relevant context before drawing conclusions. Viewing success as an anomaly tied to unique talent allows decision-makers to analyze it more accurately. Begin by accepting that there may be only one—not two, not three, not forty.

2. Data Sparsity
   Anomalies often emerge in sparse datasets, making it difficult to detect patterns. McVay was the only 30-year-old head coach to achieve such incredible success. There wasn’t enough data to suggest that others from his "tree" would replicate his results.

3. Avoiding False Positives
   Contextual anomaly detection methods can produce false positives, leading to flawed decisions. Careful tuning, validation, and an understanding of unique variables can help mitigate this risk.

When organizations base future decisions on false anomalies, they set themselves up for failure. Acknowledging the existence of anomalies like McVay or Secretariat doesn’t mean dismissing the potential of others—it means thinking critically, searching more deeply, and making decisions rooted in context rather than assumption.

By understanding anomalies, we as leaders can approach our choices with greater clarity and ultimately improve our odds of finding the right fit—be it in the boardroom, on the field, or beyond.

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