# An Agent-Based Simulation of How Promotion Biases Impact Corporate Gender Diversity
## 5 Results  
### Experiment 1: The Impact of Gender Biases in Promotion  
In the first set of experiments, we wanted to establish a baseline and then test the impact of systematically increasing the degree of gender bias in the promotion process. In all these simulations, the hiring bias is set to zero. Figure 2 shows the gender balance at each rank during a 40-year simulation when there is no promotion bias or hiring bias. The figure shows that, in the absence of biases, the gender balance stays at 50-50 throughout the simulation, with only small oscillations due to the inherent randomness of the simulations. \begin{table}
\begin{tabular}{c c} \hline
**Variable Name** & **Variable Description** \\ \hline rank & The level of the employee within the organization \\ \hline start-date & The date when the employee joined the company \\ \hline start-date-in-rank & The date when the employee first reached a certain rank \\ \hline tenure-in-rank & How much time the employee has been at a certain rank \\ \hline seniority & A normalized variable [0–1.0] that reflects how long the employee has \\  & been at this rank, relative to all employees at the same rank \\ \hline promotion-score & A score that combines the employee’s seniority and promotion biases \\ \hline times-passed-over & The number of times someone from the same level with lower \\  & seniority was promoted \\ \hline hr-events & A list of HR-related events such as being hired or promoted \\ \hline \end{tabular}
\end{table} 
Table 1: List of employee agent variables tracked in the simulation. \begin{table}
\begin{tabular}{l l} \hline
**Parameter Name** & **Parameter Value** \\ \hline Simulation duration (in years) & 40 \\ \hline Number of repetitions of each simulation & 10 \\ \hline Initial company size & 300 \\ \hline Initial gender balance (male-female) & 50–50 \\ \hline Promotion bias level & 0, 0.1, 0.3, 0.5 \\ \hline Promotion bias duration & N/A (exp. 1), 10 (exp. 3) \\ \hline Hiring bias & 0 \\ \hline Promotion pool size & 15\% \\ \hline Termination pool size & 50\% \\ \hline \end{tabular}
\end{table} 
Table 2: Parameter settings for our promotion bias in Experiments 1 and 3. Next, we tested the impact of increasing the promotion bias to 0.1, 0.3 and 0.5. As mentioned earlier, in the absence of biases, each employee's promotion score is simply its seniority relative to the most senior employee at that level (rank seniority). Hence, all the promotion scores prior to the application of a gender bias are between 0.0 and 1.0. Adding a promotion bias of 0.1 thus means that while women's scores will still be in the range [0.0, 1.0], men's promotion scores will be in the range [0.1, 1.1]. Similarly, at the highest level of bias reported here (0.5), men's promotion scores will be in the range [0.5, 1.5], while women's promotion scores will stay in the range [0.0, 1.0]. As can be seen in Figure 3, a bias of 0.1 in promotions begins to show an interesting pattern: while the entry and manager levels continue to stay roughly at 50-50, the VP level (dashed line with no symbols) is starting to show an imbalance in favor of men, and men now make up roughly 60% of the executive level (solid line with diamond symbols). Figure 3: Fluctuations in gender balance across all four levels during a 40-year simulation when the promotion bias is 0.1. Figure 2: Fluctuations in gender balance across all four levels during a 40-year simulation. For this figure, the promotion and hiring biases are set to zero. The pattern becomes much more evident in Figures 4 and 5, which show the gender balance at each company level when the promotion bias is set to 0.3 and 0.5, respectively. Several interesting phenomena are worth pointing out.