The problem of reconstructing the sky position of compact binary coalescences detected via gravitational waves is a central one for future observations with the ground-based network of gravitational-wave laser interferometers, such as Advanced LIGO and Advanced Virgo. Different techniques for sky localisation have been independently developed. They can be divided in two broad categories: fully coherent Bayesian techniques, which are high-latency and aimed at in-depth studies of all the parameters of a source, including sky position, and "triangulation-based" techniques, which exploit the data products from the search stage of the analysis to provide an almost real-time approximation of the posterior probability density function of the sky location of a detection candidate. These techniques have previously been applied to data collected during the last science runs of gravitational-wave detectors operating in the so-called initial configuration. Here, we develop and analyse methods for assessing the self-consistency of parameter estimation methods and carrying out fair comparisons between different algorithms, addressing issues of efficiency and optimality. These methods are general, and can be applied to parameter estimation problems other than sky localisation. We apply these methods to two existing sky localisation techniques representing the two above-mentioned categories, using a set of simulated inspiral-only signals from compact binary systems with total mass $\le 20\,M_⊙$ and non-spinning components. We compare the relative advantages and costs of the two techniques and show that sky location uncertainties are on average a factor $≈ 20$ smaller for fully coherent techniques than for the specific variant of the "triangulation-based" technique used during the last science runs, at the expense of a factor $≈ 1000$ longer processing time.