The spatial and temporal relationships between stellar age, kinematics, and chemistry are a fundamental tool for uncovering the physics driving galaxy formation and evolution. Observationally, these trends are derived using carefully selected samples isolated via the application of appropriate magnitude, colour, and gravity selection functions of individual stars; conversely, the analysis of chemodynamical simulations of galaxies has traditionally been restricted to the age, metallicity, and kinematics of `composite' stellar particles comprised of open cluster-mass simple stellar populations. As we enter the Gaia era, it is crucial that this approach changes, with simulations confronting data in a manner which better mimics the methodology employed by observers. Here, we use the SynCMD synthetic stellar populations tool to analyse the alpha-element and iron abundance distributions of a a Milky Way-like simulated galaxy, employing an apparent magnitude, colour, and gravity selection function similar to that employed by the Gaia- ESO Survey (GES); we compare such an observationally-motivated approach with that traditionally adopted, and demonstrate the remarkable power of the former, and the equally remarkable agreement -- for the first time -- between observations and simulations.