Techniques for statistical process control (SPC), such as using a control chart, have recently garnered considerable attention in the software industry. These techniques are applied to manage a project quantitatively and meet established quality and process-performance objectives. Although many studies have demonstrated the benefits of using a control chart to monitor software development processes (SDPs), some controversy exists regarding the suitability of employing conventional control charts to monitor SDPs. One major problem is that conventional control charts require a large amount of data from a homogeneous source of variation when constructing valid control limits. However, a large dataset is typically unavailable for SDPs. Aggregating data from projects with similar attributes to acquire the required number of observations may lead to wide control limits due to mixed multiple common causes when applying a conventional control chart. To overcome these problems, this study utilizes a Q chart for short-run manufacturing processes as an alternative technique for monitoring SDPs. The Q chart, which has early detection capability, real-time charting, and fixed control limits, allows software practitioners to monitor process performance using a small amount of data in early SDP stages. To assess the performance of the Q chart for monitoring SDPs, three examples are utilized to demonstrate Q chart effectiveness. Some recommendations for practical use of Q charts for SDPs are provided.