Road production and maintenance can be described as a sequential, contemporary process that includes a large number of vehicles, machines, personnel, and organizations. Today, much administration and interaction takes place manually, which makes both coordination and follow-up costly and inefficient. The asphalt paving process is a mission critical task which depends on many factors that often change during the actual paving operation. The productivity, the lifespan of the final product and the environment is negatively affected by the imbalances and deviations in the flow. The hypothesis of this study is that there is a large improvement potential for usage of digitalization, optimization and control techniques in the asphalt pavement process to increase road quality, productivity and decrease environmental impact. To address the hypothesis, this study has performed a case study of an asphalt pavement process including multiple road asphalt pavement maintenance projects. The study has collected unique, simultaneous, and detailed data from the entire process and its key characteristics including asphalt plant, transportation vehicles, asphalt pavers, as well as asphalt compactors. The study has used the data to perform an assessment and quantification of productivity improvements through measurements of machine and process efficiency, and utilization during the asphalt paving process operation. The results include observations of reoccurring characteristics and lean based operative wastes such as waiting times and machine stops. The identified characteristics are quantified and productivity, efficiency and cost savings in the operation as well as road quality improvements affecting the overall lifecycle of the road pavement are assessed. In addition, the study points out important aspects and hindering factors to further implement and use real-time optimization techniques in the day-by-day operation.