Find a local historian, librarian, county clerk or ward boss who knows everyone's business. You can use it for this story as well as for utilitarian jobs like finding employees in a pinch, spelling their names right, revealing the highest-paid workers, documenting outrageous overtime, etc. Analyze the decennial census data to establish work-age demographics by race, gender, ethnicity. Get a copy of the agency's hiring rules for civil service and temporary workers. If you can, get a list of the agency's consultants and their contract amounts.
Nepotism can hide in various places.
If you've got names and addresses included in your data, you're on Easy Street. The result will be a good picture of employees who cohabit. Either one of these can put you onto nepotism. To ensure you get the broadest possible number of matches, you'll want to strip out, or standardize, data that will throw the matches off. Then compare the table of surname hits with the table of street name hits.