Over the last decade, real spending in the United Kingdom NHS doubled in real terms to meet government targets including moves to increase spending rates to other EU countries and increasing health demands both as a result of increasing population of the elderly and illness related to lifestyle. However, in 2009-10 the impact of the economic and financial crises and the resulting structural deficit prompted fiscal tightening which would impact all areas of public financing including the NHS. There is evidence to suggest that billions could be saved by productivity savings and by service reconfiguration. Simulation modelling could be a powerful tool to help unlock those potential savings and inform service reconfiguration at a strategic level. Although simulation modelling has been around for many years and many health related papers have been produced, arguably there has been lack of real world benefit. Suggested reasons for lack of real world benefit include the scale, complexity and diversity of health care delivery. Other observations point to the fact that academics get rewarded for publishing large complicated models with detailed analysis rather than focusing on the requirements of the environment or the needs of implementation. This case study attempts to address some of the shortcomings of real world modelling contribution by showing that average simulation process times can act as estimators for real length of stay in health care environments. Using A&E data, this case study will illustrate how average process time models could be used to reconfigure emergency services by specific patient groups (pathways). Developed models also illustrate pathway specific information such as the effects of queues and resource utilisation. Average time simulation models have the added value that they help to simplify models, make them more transparent and reduce development time making potentially making valuable contributions towards real world impact.