Svevia is a company working with installation, occupancy and operation of infrastructure. They are currently testing and developing a new system called dynamic route optimization (DynOpt) in cooperation with B and M Systemutveckling. This system is able to contribute to a series of improvements for the company, such as automatization of certain processes, conclude demand on a more local level and create dynamic optimized routes which in the best way handles the determined local demands. Svevia sees great potentials of profits with the system, thereby has an interest of a support for decision-making regarding what may or may not be problematic during a potential implementation of such a system. This report regards a case study of the affects that DynOpt can have on its future users and what impact such effects might have on Svevia, with the goal of determining the drivers and barriers of DynOpt related to soft parameters. The soft parameters in this case study relate to how the changes DynOpt entails may affect the users and why or why not they may desire or be willing to accept these changes. The method used to conclude these drivers and barriers is to firstly gather information from the users by interviews and surveys, which then is analyzed in order to determine what advantages and disadvantages the users see with the system. The second step of the data processing consists of a SWOT-analysis execution. The strategic effects are determined through consultation with insight personnel. Lastly the remaining significant results are converted into drivers and barriers by firstly eliminating the information that may not pan out in any driver or barrier and secondly lumping together result describing similar effects into drivers and barriers. Eleven drivers and six barriers are concluded. Such results are for example the driver that the potential future users’ interest in technology may ease the implementation since DynOpt is a technological implementation. One of the barriers on the other hand is that the total driving distance will be reduced through optimization, which results in less available work for the chauffeurs which worsens their working conditions and can result in resistance to the implementation. This driver and barrier as well as the others in conjunction with a discussion, constitute the final result of the report and describe aspects that may hinder or make it easier to successfully implement DynOpt.