Recent European legislation (Energy Efficiency Directive) has allocated some responsibility for residential end use energy efficiency to energy supply companies. In order to overcome data and modelling limitations associated with statistical and engineering modelling approaches to energy efficiency and renewable energy retrofit measures, energy suppliers and policy-makers often use simplified methods with limited data requirements to assess dwellings. One approach employed is an asset rating method (ARM); a standardised approach to residential energy demand estimation which is outlined in ISO EN 13790 (Energy Performance of Buildings Directive). Although it is a simplified method which industry is well-equipped to deliver, it is time-consuming to apply ARMs to the large domestic customer bases of energy suppliers. A small per-dwelling time saving will result in significant overall efficiencies for these users. This study examines the effect that reducing input data requirements of the ARM has on the accuracy of the methodology and comments on the trade-off between model simplification and accuracy. We find that it is possible to maintain a high degree of accuracy (similar to 95%) with 20 fewer variables than the baseline model. This is equivalent to almost 40% fewer variables than in the full model and represents a significant saving in effort (C) 2013 Elsevier B.V. All rights reserved.