A run sum Hotelling’s χ
2 control chart is proposed and its average run length (ARL) performance is evaluated using the Markov chain approach. A fast initial response (FIR) feature of this chart is also considered. In the optimization of the run sum χ
2 chart, computer programs are used to compute the chart’s optimal parameters. It is shown that the run sum χ
2 chart is superior to the various χ
2 charts with runs rules and the synthetic χ
2 chart, for all sizes of shifts in the mean vector, but less sensitive than the multivariate EWMA (MEWMA) chart toward small shifts. The sensitivity of the run sum χ
2 chart in detecting small shifts can be further enhanced by adding more regions and scores, so that this chart is as competitive as the MEWMA chart. We reckon that the run sum χ
2 chart is a relatively easy and effective tool for practitioners, as the χ
2 chart’s statistics can be plotted in its original scale of measurement, in contrast to the MEWMA chart which plots the transformed measurements.
