Gamma Distribution

In advanced talent management, not all organizational phenomena follow symmetric patterns. There are other variables that do not behave like a normal curve and whose distribution shows a clear asymmetry. In these cases, the Gamma Distribution becomes a particularly useful tool for interpreting reality with greater precision.

The Gamma Distribution is a continuous statistical distribution characterized by:

• Only taking positive values.
• Showing right-skewed asymmetry (long positive tail).
• Adapting to phenomena where concentration occurs at low or medium values, but extreme high cases exist.

In Human Resources, many variables do not follow a normal distribution. For example:

• Time to promotion.
• Accumulated sick days.
• Seniority in certain positions.
• Time needed to achieve objectives.
• Number of completed trainings.
• Time spent in recruitment processes.

In these cases, it is common that:

• The majority of people are concentrated at low or medium values.
• There is a minority with significantly higher values.
• The distribution is clearly asymmetric.

Practical example: time to promotion

Imagine an organization analyzing the time it takes employees to receive their first promotion.

The data shows that:

• The majority are promoted within 2 to 4 years.
• A small group takes 8, 10, or even more years.
• No one has a negative value (time is always positive).

If we plot this data, we see an initial concentration and a long “tail” to the right. This pattern fits a Gamma Distribution.

Understanding this shape allows:

• Identifying development bottlenecks.
• Detecting possible inequalities.
• Analyzing if there are systematically delayed groups.
• Setting realistic career expectations.

Practical example: absenteeism

In the analysis of absence days:

• The majority of employees may have 0 to 3 days.
• A small group may accumulate 20 or more.
• The average may be distorted by these extreme values.

Here, using only the mean can be misleading. Modeling the variable with a Gamma Distribution allows a better understanding of overall behavior and the probability of extreme cases.

Strategic value

Applying this approach allows:

• Adjusting more realistic predictive models.
• Designing policies based on real probabilities.
• Avoiding simplistic interpretations of the mean.
• Identifying risk patterns.
• Improving resource planning.

In People Analytics, understanding the shape of the distribution is as important as knowing the average value.

This way, we can determine that the Gamma Distribution is a statistical tool that allows analyzing positive and asymmetric variables in talent management. It provides a more accurate view of phenomena where concentrations and extreme cases exist.