New challenges about how to measure the performance of organizations have arisen since big data can be found everywhere. In order to make proper decisions, management needs to have strong insight into what is important to the firm and how to improve it. This study looks into logistics companies that rely heavily upon labor as the examples. While transportation and distribution are very important processes for logistics companies to meet customers‟ requirements, the process of creating appropriate measures is difficult due to the complexity of these activities. The aim of this research is to evaluate the relationship among these key performance indicators and find out the possible direction and coverage of improvement for such companies using hybrid DANP1 cause-effect and Influential Network Relation Map models. We collected data through expert questionnaires with questions based on discussions with experts (including managers and scholars). The research results help support managers‟ decision making for improvements in their firm and also can be applied in employee reward systems.