Big-M to the extreme

A major issue in MIP modeling is choosing good values for big-M constants. The poorly chosen name 'big-M' indicates we should use a really big value which is exactly the opposite of what we should do, Here we see an extreme example:

It is my conjecture that just because of this name 'big-M' we have a lot of models ill-behaving as a result of bad numerics. If textbooks just would call this 'small-m' instead, new modelers would not have the urge to use these ridiculously large numbers.  

As indicated in the comments some solvers support indicator constraints (Cplex, as well as Scip and Xpress I believe) which allow you to formulate implications without big-M constants.