Although HAIEFF models are unlikely to reach the level of accuracy necessary to supplant DFT-D as a final ranking approach, a terminal DFT-D calculation is meaningless if the energy models which precede it cannot deliver the correct structures for ranking. This is the case if a cheaper energy model fails to identify valid polymorphs as energy minima or if the identified minima are beyond the energetic cutoff of structures carried forward to the next stage of the hierarchical study. For this reason, continued improvement of HAIEFF model accuracy is still a valuable endeavour. A leading cause for inadequate HAIEFF model accuracy may be poor parameterization of the force-field component, for instance if the reference data used is heavily biased towards crystal geometry over crystal energy. Moreover, recognising the evolving role of HAIEFF models within the larger CSP workflow, and in the spirit of 'blind' CSP where experimental data is absent, reference data representative of the DFT-D landscape may be a more sensible yardstick for accuracy. Another contributor to the inaccuracy of HAIEFF models is the (mis)use of repulsive/dispersive parameters in a manner that is inconsistent with their derivation. For example, during a CSP search, use of ad hoc repulsive/dispersive parameters is common, even if the parameters were originally derived using electrostatic and/or intramolecular models different from the models employed in the ongoing CSP search. There is therefore a clear drive for the development of tools to reliably and efficiently obtain transferable parameter sets for this class of models.