It has been recognized that it is profitable to apply statistical methods in quality improvement projects. The statistical methods that have been developed for that purpose in the 20th century have been made operational in the form of improvement strategies. In the literature various examples of such strategies are described. Although often presented as a uniform approach for problem solving, they are partly differing in terms of the steps and the tools they use. This paper’s objective is to place the available strategies in relation to each other and to study the differences in functionality. We discuss both global differences—differences relating to the functional objectives of the strategies—and detailed differences, that is, differences that concern the steps and the tools that are exploited to arrive at the objectives. The strategies that are taken along in the collation appear to have sufficient similarities to place them in a functional framework. This framework enables one to exploit the complementary functionalities within the strategies and to use it as a generic strategy for statistically based process improvement.
