Managing “long running” stories

Sometimes, if you work in a iterative and time boxed development process, you are struggling with stories which include a long running operational task. Normally the actual implementation and reporting costs you not much time, the problem is that the operational task, such as import of large data sets, needs a lot of time and only the complete completition of the task will close the story. The first chalange is, how to estimate such stories? If you only take in account the actual work, your estimation is very low, but you know you cannot compare it to other stories estimated. On the other hand, if you estimate somehow the effort and the duration of the story, you are also not telling the real truth, because most of the time until the story is finished, you are not working actively on it. Sometimes the situation is event worse if such a story takes longer as your timeboxed iteration and extreme extension is no option. So what to to? My solution so far:

  • Split the story in two, one which covers your upfront work and implementation, the second covers the tasks for completing the story (check results, write reports …)
  • Leave the actual operation task uncovered, the initial story starts in one iteration, the finishing story in any following iteration if you are damned sure the task will be finished
  • Estimate not the duration of the lung running part, only the tasks itself
  • Optional, watcher stories/tasks can be defined

With the splitting of stories, you can handle the tasks inside a iteration, make a commitment to them and finish them in time. I’ve had this problem actually with really long running database imports which somehow were to long for short sprints (2-4 weeks). So I was looking if someone had the same problems with this kind of stories but found no solution. If anyone knows a better method or has knowldge this specific ideom was described already in the literature, give me a word.

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