What possible data products can be built using this dataset I have a dataset which contains information about when do people enter and leave a premise. I have the following information in the dataset : 


Person Id
Time of Entry
Time of Leaving


The dataset has around 50 unique persons. Each person will have multiple entries corresponding to multiple visits. The data spans over a year so I have quite a lot of entries (around 1 million).

These people can be classified on the basis of the department they work under (2 departments - mutually exclusive) or on basis of  their role (4 possible roles - all mutually exclusive)

I was wondering what kind of data analysis can be done with this kind of dataset. I am not looking for straight-forward things like "who spent the most time in building". However things like finding correlation between visits of 2 people would be interesting. So if person A visits the premise, what is the probability that person B would also visit. Since I have only around 50 unique visitors, I think such an analysis is feasible. 

Another line of thought was to apply some interval-pattern mining techniques but I am not much familiar with them.

Can someone give me some pointers/ideas about what kind of data products can be build using this or what kind of techniques can be used with such data.  

Edit : As discussed in comments, I call it a product in the sense that I do not want some simple or trivial analysis. And I am not looking for any commercially viable idea - just some cool fun idea :)
You might be able to find individuals that act as anchors.  That if Abe is here, then everybody else is more likely to stay longer. Interesting to know if it was always the same people who stayed or not.

There might also be some interesting patterns with groups that arrive, are present, or leave together.

As a business owner you could look for individuals who not just work shorter hours, but arrive at their own time, and leave with a group.