Quartile distribution — what the four bands tell you that the median doesn't

The mean tells you what the average looks like. The median tells you what the typical person looks like. Neither tells you who is in which part of the pay distribution.

Article 9 requires the third view: the distribution of female and male workers across the four quartile pay bands. The quartiles divide the workforce by pay into four equal-size groups. The metric is the percentage of women and the percentage of men in each.

Where the mean and median collapse the workforce into single numbers, the quartile breakdown shows the shape. A clean overall gap can hide a heavily uneven composition. A gap that looks similar to two other companies can have a very different quartile picture underneath it.

The four bands

For each band, Article 9 metric 07 requires the percentage of women and the percentage of men. A balanced workforce would show roughly equal proportions across the four bands. An imbalanced workforce would not.

A worked example

A 100-person company. 50 women, 50 men. The overall headline gender pay gap (median): 0%. The quartile distribution:

The headline median is 0%. The quartile breakdown shows the workforce is structurally lopsided. Women are over-represented in Q1 and Q2; men are over-represented in Q4. The same number of women and men, the same median per quartile, the same headline — and yet a substantially different organisational picture.

The mean for this same data would not be 0% — it would be skewed by the Q4 over-representation of men. The mean shows magnitude; the median shows central tendency; the quartile distribution shows composition. Three views of the same data, three different answers.

What the quartile distribution reveals

Three patterns the quartile breakdown surfaces that the median misses:

Vertical segregation. Women clustered in lower quartiles, men clustered in upper quartiles. This is the most common pattern in European SMEs. The median can be close to zero per quartile (women in Q1 earn similar to men in Q1) while the overall organisational shape is strongly tilted.

Pipeline imbalance. An over-representation of one gender in Q1 with under-representation in Q2 suggests promotion or retention gaps in early career. Conversely, Q4 over-representation of men can reflect historical hiring patterns at senior level.

Role-mix effects. If women are concentrated in support functions and men in revenue-generating functions, those functions pay differently and the quartile breakdown shows the resulting composition without needing to point at the function structure explicitly.

Reading the three metrics together

The directive requires mean, median, and quartile distribution precisely because they answer different questions:

• Mean — what does the organisation pay on average, given its current shape?
• Median — what does the typical employee experience?
• Quartiles — how are women and men distributed across the pay structure?

Together they describe a workforce. The combination is what a regulator, a works council, or an Article 7 requester reads. Reading any one in isolation produces a partial conclusion.

The median says what the average person earns. The quartile distribution says which people are above and below that average.

Where the diagnostic starts

The quartile distribution can be calculated from a clean payroll export. What it reveals depends on the category structure that sits upstream — without it, the quartiles are calculated across the whole organisation and obscure the per-category patterns Article 9 requires.

The ReadinessCheck™ surfaces whether the category structure is in place. The quartile distribution becomes meaningful once the per-category lens is applied.