Multivariate control charts are becoming more important in the monitoring of processes in manufacturing industries because the quality of a process is usually determined by several correlated variables (quality characteristics). The most popular multivariate process control procedure is based on the Hotelling control chart. It is used to monitor the mean vector of a process. A nonrigorous approach of using four sensitizing rules is introduced to improve the performance of a conventional Hotelling chart. The use of these rules on a conventional Hotelling chart do not require a transformation of the T2 statistics into normal random variables. Thus, the T2 statistics incorporating these rules can be plotted on the same scale as they are plotted on a Hotelling chart. Numerous SAS and Mathematica programs are given to aid quality control practitioners in implementing these rules in real life problems. The aim of this article is to make the implementation of sensitizing rules appealing and user friendly to practitioners.