The objective in this thesis is to develop a method based on principal components analysis (PCA) to create optimal product families of artifacts, tasks, or environments intended for human use. This study formulates a procedure to estimate the levels of commonality and distinctiveness required in a product family designed to accommodate human variability. Families of products that users physically interact with are considered in this thesis with the aim of maximizing the accommodation (a product which fits the users is said to “accommodate” the user) afforded by these products. The multivariate statistical technique of PCA is employed to assess the anthropometric variability in the target user population. The usual methods of improving the accommodation of a product are: incorporating adjustability and scaling (offering different sizes). A manufacturer can offer the same product in different sizes to capture a wider market, thereby offering a family of products. Among the various components in the products, some will be similar and others will be distinct. The manufacturing costs can be reduced, and the profits can be increased if the commonality and distinctiveness are optimized such that accommodation is maximized. Since the products are intended for human use, accommodation will be governed by human variability, especially anthropometry. PCA is used to identify the underlying pattern in human variability so that the relative proportions of scaling and adjustability can be assessed and assigned appropriately to the products in the family. Three case studies are used to demonstrate the proposed method.