The usual practice for policy-makers is to see how well their models forecast economic developments and figure out the cause of any errors. Often, the errors can be considered benign white noise generated by various sources of uncertainty.
However, when the data consistently show results that are different from what the model projects, it could be a sign that something more important is at play. Because of all the interdependencies, we have to guard against the possibility of persistent problems with the model, which can lead to a biased projection and monetary policy errors.