  In phenomenological preparation for new measurements one searches for the
carriers of quality signatures. Often, the first approach quantities may be
difficult to measure or to provide sufficiently precise predictions for
comparisons.
  Complexity of necessary details grow with precision. To achieve the goal one
can not break the theory principles, and take into account effects which could
be ignored earlier. Mixed approach where dominant effects are taken into
account with intuitive even simplistic approach was developed.
  Non dominant corrections were controlled with the help of Monte Carlo
simulations.
  Concept of Optimal Variables was successfully applied for many measurements.
New techniques, like Machine Learning, offer solutions to exploit
multidimensional signatures. Complementarity of these new and old approaches is
studied for the example of Higgs Boson CP-parity measurements in H to
tau^+tau^-, tau^pm \to nu (3pi)^pm cascade decays.
