Computers are preferred above humans when dealing with information processing because of the great memory and fast computing times. The use of algorithms within complex planning processes is an interesting research field. These algorithms should help human planners with the planning process and therefore are called Planning Assistance Tools (PAT). However, the implementation of a PAT often fails because of the lack of acceptance by human planners. The lack of acceptance is often linked to the fact of human aspects that are missing within the PAT. This research provides a methodology to identify the missing aspects using a developed PAT, real-life planning assignments and experienced planners within the railway node planning. Based upon empirical experiments, a list of aspects is formulated that are translated to extensions that are implemented in the PAT. The application of such a method to a real-life case has not yet been mentioned in literature before. The research proves that the implementations have a positive effect on the quality of the solution provided by the PAT, while not harming the performance of the solution. Planners seem to better understand the solution of the PAT and the decisions made by the PAT, which increases the level of trust and the level of acceptance. The method used to identify aspects and implement them might be applicable within the industry for planning tools that are already developed, but not yet implemented because of missing acceptance of human planners.