Control charts are essential tools in the statistical process control armamentarium. Although designed for ease of use in highly structured production settings, they are in fact quite complex in nature; their proper use depends on numerous conditions that may not be clear to newer users. This article briefly contrasts the use of control charts in production and healthcare settings and highlights common sources of problems among novice users. These include misunderstandings of the type of data being charted, nonindependence of samples, the influence of natural cycles, ignoring known special influences, overlooking clear signals that a process is out of control, and calculating control limits before adequate data are available.