This article deals with some techniques for analyzing ordered categorical data from industrial experiments for quality improvement. Taguchi's accumulation analysis method is shown to have reasonable power fordetecting important location effects; however, it is an unnecessarily complicated procedure. For detecting dispersion effects, it need not even be as powerful as Pearson's chi-squared test. Instead two simple and easy to use scoring schemes are suggested for identifying the location and dispersion effects separately. The techniques are illustrated on data from an experiment to optimize the process of forming contact windows in complementary metal-oxide semiconductor circuits.