Diversity Within Groups Is Always Larger Than Between Them
TLDR; Individual variation matters more than group averages.
While grouping people and measuring differences between groups can help us evaluate items at the macro level, it's crucial to remember that the variation within groups is almost always larger than the differences between them. This insight has profound implications for leadership and decision-making.
Real-World Examples
In professional tennis, the difference between the best and worst ranked men's players is far larger than the average difference between men's and women's players.
When comparing urban and rural residents' music preferences, both groups contain individuals who deeply love and strongly dislike country music.
Why This Matters
Understanding this principle helps us avoid three common pitfalls:
- Assuming group averages apply to individuals
- Using demographic shortcuts instead of getting to know people
- Making decisions based on group stereotypes rather than individual characteristics
Putting This Into Practice
When working with individuals:
Take time to understand each person's unique characteristics, motivations, and capabilities.
Use group-level data for high-level planning, but always adapt to individual circumstances in implementation.
Conclusion
While group-level analysis has its place in understanding broad patterns, individual variation is almost always more significant. There are no shortcuts to understanding individuals; you must invest the time to know each person as they are, not as their group statistics might suggest.