  Companies that use robotic process automation very often deal with problems
maintaining the bots in their RPA portfolio. Current key performance indicators
do not track the behavior of RPA bots or processes. For better maintainability
of RPA bots, it is crucial to easily identify problematic behavior in RPA bots.
Therefore, we propose a strategy that tracks and measures the behavior of
processes to increase the maintainability of RPA bots. We selected indicators
of statistical dispersion for measuring variability to analyze the behavior of
RPA bots. We analyzed how well statistical dispersion can describe the behavior
of RPA bots on 12 processes. The results provide evidence that, by using
statistical dispersion for behavioral analysis, the unwanted behavior of RPA
bots can be described. Our results showed that statistical dispersion can
describe the success rate with a correlation of -0.91 and outliers in the data
with a correlation of 0.42. Also, the results demonstrate that the outliers do
not influence the success rate of RPA bots. This research implies that we can
describe the behavior of RPA bots with variable analysis. Furthermore, with
high probability, it can also be used for analyzing other processes, as a tool
for gaining insights into performance and as a benchmark tool for comparing or
selecting a process to rework.
