This model describes a situation where for each task worked on by a worker, new issues are discovered and are added to the original number of tasks that need to be completed in order to complete the project successfully. Examples where this might arise is in the computer programming industry where each programmer or engineer takes on a whole task to work on alone, begins coding, and discovers issues that are then assigned to bitbucket as issues needing resolved. Other programmers, or the same programmers, come back later to resolve the issues. The question: under what circumstances does the project eventually get completed? When does the project continue to go on forever as issues crop up faster than they can be resolved? This model assumes that for each task discovered there are a fixed number of new issues found. Under this assumption, the simulation suggests that if the total average number of issues found per tasks completed by all employees is less than the number of employees, the project eventually gets completed.
Note: the assumption that for each task discovered there are a fixed number of new issues found is likely unrealistic since as the project starts to get perfected, we would expect the average number of issues being found per task would decrease.
At this point, there are at least two different directions one can explore to gain more insight into the Task-Issue Cycle problem: one option is to assume that the average number of issues discovered per cycle is not constant in time, but varies as a function of the specific tasks, or more simply, as a function of the number of tasks completed and that depends explicitly on time: Average Issues found per tasks completed for a given employee= F(TasksCompleted(time), time) and try to figure out the form of F and incorporate that function into the model above.
Another option is to construct a different model that describes the same Task-Issue cycle in order to get a different point of view. From this different point of view, new information is likely to be gleaned.