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The decision to retry after an exception is primarily influenced by the details and history of the exception. When a process encounters an error, understanding the specifics of that error—such as its cause, frequency, and the context in which it occurred—provides crucial information for determining whether a retry is warranted. For instance, if the exception was a temporary issue (like a network glitch) that has since resolved, then a retry may be appropriate. In contrast, if the exception indicates a more significant or systemic problem, it may be wiser to stop the process and address the underlying issue rather than attempting a retry.

The details and history of the exception allow users to assess patterns or recurring issues, which can significantly influence whether attempting another execution would likely succeed. Hence, it is vital for robotic process automation (RPA) systems like Blue Prism to capture and analyze these details to make informed retry decisions.

Other factors, while potentially impactful, do not have the same critical influence on the decision-making process. For example, the complexity of the process may indeed affect how robustly a retry can be managed, but without knowing the specifics of the exception, it is challenging to make a decision. Likewise, available resources can determine the capability to retry but do not impact the