Minute accumulating analysis (MAA) is Taguchi's method for analyzing life test data from designed experiments. Motivated by comparing survival curves, MAA analyzes sequences of binary data generated from the life test data. This paper explains MAA and exposes numerous pitfalls caused by ignoring or misusing information provided by the data. Examples using real and synthetic data and a simulation study demonstrate that MAA can detect spurious effects, miss real effects, and reverse the order of factor importance. Consequently, MAA cannot be recommended. Standard techniques for analyzing reliability data, which correctly handle life test data, provide a valid and flexible alternative.