regression analysis in excel nonnumerical data

How are variables like this worked into logistic or multiple regression analyses? It's not a numeric variable, so it doesn't work with my Logistic Regression tool. If I were to use this same workflow, I would have hundreds of additional dummy variables - one for each supervisor. Here's an example - I want to determine if certain supervisors (of which there are hundreds in our organization) are more likely to have employees quit within the first year of employment.

The problem I'm running into is when the categories extend beyond just a few classifications.

For instance, if I want to determine the effect that education level has, and that variable has four classifications - 1) no HS diploma, 2) HS grad, 3) some college, and 4) college grad, I'd wind up with four additional independent variables (all dummies) and each record would have a 1 in only one of those four columns based on their highest education level attained. The workflow is basically taking each variable's classification and making a dummy variable out of it so that it equals 1 if the record meets the criterion and 0 if it doesn't. The solution that I found (see attached workflow) works well with variables that only have two or three classifications. These non-numeric variables are categorical, e.g., male / female. I'm having a problem figuring out how my dependent variable changes as certain non-numeric independent variables change. I'm looking for the appropriate Alteryx tool to deal with non-numeric independent variables.

Regression analysis in excel nonnumerical data