In recent years, performance measurement (PM) has continued to gain increased interest from academic researchers and industry professionals as a means for improving productivity and performance. Despite the increased use of PM, evidence from the literature suggests that many of the initiatives are not successful. Scholarly research also suggests that PM initiatives fail at the implementation phase, as this is where most of the challenges are seen, which may create barriers that lead to ineffective systems. Therefore, by improving the implementation process, the chances of success for PM systems are increased. By analyzing interrelationships and interpreting the effect of the success factors, this can drive implementation success. A causal loop diagram (CLD) can be used to represent the relationships between the variables identified to give a better understanding of the process. So, establishing the interactions between the factors that affect the implementation can give an insight into executing successful systems. This study generates a CLD from a regression analysis developed through an initial investigation of variables that affect implementation success. Survey data from initial investigation was based on 124 responses from medium-sized organizations across different industries. The CLD shows that success factors have a significant positive effect on PM implementation. This paper develops a CLD that indicates causal relationships of variables that affect implementation success which can be used as the basis for future work. Using the results of this study, practitioners can leverage on the information to establish strategies that effectively enhance their processes.