  The continuous progress toward more precise cosmological surveys and
experiments has galvanized recent interest into consistency tests on
cosmological parameters and models. At the heart of this effort is quantifying
the degree of inconsistency between two or more cosmological data sets. We
introduce an intuitive moment-based measure we call the \textit{index of
inconsistency} (IOI) and show that it is sensitive to the separation of the
means, the size of the constraint ellipsoids, and their orientations in the
parameter space. We find that it tracks accurately the inconsistencies when
present. Next, we show that parameter marginalization can cause a loss of
information on the inconsistency between two experiments and we quantify such a
loss using the drop in IOI. In order to zoom on a given parameter, we define
the relative residual IOI and the relative drop in IOI. While these two
quantities can provide insights on the parameters that are most responsible for
inconsistencies, we find that the full IOI applied to the whole parameter
spaces is what must be used to correctly reflect the degree of inconsistency
between two experiments. We discuss various properties of IOI, provide its
eigenmode decomposition, and compare it to other measures of discordance.
Finally, we apply IOI to current geometry data sets (i.e. an improved
Supernovae Type Ia compilation, baryon acoustic oscillations from 6dF, SDSS MGS
and Lyman-$\alpha$ forest, and high-$\ell$ CMB temperature data from
Planck-2015) versus growth data sets (i.e. Redshift Space Distortions from
WiggleZ and SDSS, Weak Lensing from CFHTLenS, CMB Lensing, Sunyav-Zeldovich
effect, and low-$\ell$ CMB temperature and polarization data from Planck-2015).
We find that a persistent inconsistency is present between the two data sets.
This could reflect the presence of systematics in the data or inconsistencies
in the underlying model.
