# An Agent-Based Simulation of How Promotion Biases Impact Corporate Gender Diversity
## 5 Results
### Experiment 4: The Impact of Promotion Biases on Individual Employees  
One of the great benefits of agent-based simulations is that they make it possible to analyze at the same time the experiences of individuals and the overall company-level outcomes. This is perhaps the most powerful argument for using agent-based simulation as a core tool in managing talent in general: especially in the context of D&I, we tend to hear anecdotes about individual experiences, but most of the data reported is based on statistics measured at the company level, which hide the details of individual experiences. With agent-based simulation, we can do both: we can calculate population-level data just as we would in the real world, without losing any of the information about individual experiences. This makes it possible to explore the causal relationships that link individual experiences with company-level, emergent outcomes. To illustrate this point, we conducted one final experiment to highlight how a company-wide promotion bias manifests itself in terms of the lived experiences of individual employees. In particular, while running simulations we noticed--not surprisingly--that women were often stuck at each rank, while men with less seniority were getting promoted ahead of them. Anecdotally, this is an experience that is often reported by women. To quantify this phenomenon, we tracked how many times each simulated employee is passed over for promotion, and how much time it spends at a given rank. Specifically, each time an employee is promoted from a certain level, all other employees who are more senior increment a counter that tracks how many times they have been passed over for promotion. When an employee is promoted, we record the total amount of time it had spent at that rank (its \"tenure-in-rank\") and the number of times it was passed over, and then we reset the counter to zero before heading to the higher rank. Note that because there is no promotion beyond the executive level, this analysis can only be performed for the first three ranks (entry level, manager and VP). Because the number of employees differs at different ranks, and because the simulation tracks every promotion, entry-level employees were being passed over many more times than managers, who in turn were being passed over more times than VPs. To correct this confounding factor, we normalized the data by dividing the number of times passed over by the number of people at that rank, and multiplying by ten. This roughly corresponds to assuming that, at each rank, employees are only comparing themselves to a group of ten \"peers.\" We also normalized the passed-over data by the average number of years that employees spend at each rank, to obtain an average annual figure, which made the comparison across ranks more meaningful. Figure 9 shows the results of this analysis. The top row shows data for VPs, the middle row for managers and the bottom row for entry level. Within each row, the left chart shows the average number of times passed-over in one year, while the right chart shows the average tenure-in-rank in years. Within each chart, there are four pairs of bars representing, from left to right, the level of promotion bias (0.0, 0.1, 0.3, 0.5); each pair of bars represents data for men (dark grey) and women (light gray). As with all other experiments, each data point was obtained by running the simulation ten times with different random seeds, and error bars show one standard deviation of the mean. Several things are worth noting. First, when there is no promotion bias (the leftmost pair of bars in each plot), we see that the results for men and women are very similar, as expected. Note also that because promoted individuals are selected randomly from a promotion pool (as described in the section Simulating the Promotion Process), even in the absence of biases there will always be some employees that are passed over, which is why the leftmost bars at all three ranks are non-zero.