 Having determinant ±1 and all eigenvalues of magnitude 1 is of great benefit for numeric stability.One implication is that the condition number is 1 (which is the minimum), so errors are not magnified when multiplying with an orthogonal matrix.Many algorithms use orthogonal matrices like Householder reflections and Givens rotations for this reason.