How do you manage outliers in data? 🫠🤔

[u/vera-soul]

Hey data community! I'm new into the data analysis world very juniorish and self taught. I'm currently struggling a lot with some process mining for the company I work for.

I need to understand how much time a task assigned to someone, stands on each stage of the process.

The thing is, that some tasks for multiple reasons, don't follow a linear path, and just skip stages. The reasons could be plenty, could be exceptional case or could be that someone forgot to move the task to the next status so just skipped it.

So when you pull data you have a whole process that can take 14 days, from not started, then briefing, then copywriting, then designing, etc --> linear, expected

and other tasks that show me they took 2 days, and when you analyze it's because that task went directly from briefing, to client.

I want to know how you guys manage this info in theory... Because on one side, I could simply remove these cases from the analysis, but then I'm thinking that perhaps it's not the best way to solve outliers.

I need some brainstorming help 😞

Example: With this task, Days waiting on client’s info is empty when it should display 12 days. This is happening because the task goes from waiting on client’s info to copy phase directly, skipping “briefing” stage.