  A comprehensive uncertainty estimation is vital for the precision program of
the LHC. While experimental uncertainties are often described by stochastic
processes and well-defined nuisance parameters, theoretical uncertainties lack
such a description. We study uncertainty estimates for cross-section
predictions based on scale variations across a large set of processes. We find
patterns similar to a stochastic origin, with accurate uncertainties for
processes mediated by the strong force, but a systematic underestimate for
electroweak processes. We propose an improved scheme, based on the scale
variation of reference processes, which reduces outliers in the mapping from
leading order to next-to-leading-order in perturbation theory.
