ABSTRACT
This chapter describes the multilevel emergence of the Lean Brain as a scale-free complex networked organizational design configuration. Mike Rother explains to Markus that his understanding of what Lean is, based on the research of R. Shah and P. T. Ward, who explain it as an integrated socio-technical system whose main objective is to eliminate waste by concurrently reducing or minimizing process variability. Mike explains how the Principal Component Analysis (PCA) is a standard statistical method that is used to extract important information from a multivariate data table and to express the information as a set of new variables called principal components (PCs). The PCA breaks down the raw data into two parts: uncorrelated PCs that best explain the system’s variability and the residual error, or how good this variability explanation really is. There are several management implications and conclusions that can be drawn from the PCA-based approach to key performance indicator analysis.
