This study aims to develop a side-sensitive modified group runs control chart using auxiliary information (SSMGR-AI) to enhance the speed of detecting mean shifts in a process. The average run length (ARL) and expected average run length (EARL) criteria are adopted as performance measures of the proposed chart. The performance of the proposed chart is compared to the exponentially weighted moving average chart with AI (EWMA-AI) and the run sum chart with AI (RS-AI), in terms of the ARL and EARL criteria. The results reveal that the optimal SSMGR-AI chart generally outperforms all charts under comparison for detecting shifts in the process mean. An application with numerical data is presented to elaborate the implementation of the SSMGR-AI chart.