In this chapter the Self-Organizing Map is used to analyze data from the world pulp and paper industry. The primary focus is on the technological aspects of the industry. Another important aspect is the fusion of environmental, economical and technological data and thus the forming of a comprehensive view of the industry. All data sets were provided by the Jaakko Pöyry Consulting, who has an extensive data base of different aspects of the world pulp and paper industry.
Similar studies regarding the world pulp and paper industry have never been reported. Instead the economical aspects of the industry were investigated with the SOM by Vanharanta et al . Their results showed that the SOM is a promising tool for financial benchmarking. There are also other recent studies where the SOM has been used in financial diagnosis, for example by Serrano-Cinca who proposed a decision support system for financial diagnosis based on the SOM  and by Kiviluoto et al. who used the SOM in analysing financial statements . Other studies in which the SOM has been used in comparing organizations, countries or companies based on socioeconomical figures have been made by Varfis et al.  and Kaski et al .
In this study five data sets were used. The three primary data sets included information on over 4000 pulp and paper mills, and the over 11000 paper machines and pulp lines in them. The two other data sets included information on the financial and environmental aspects from Scandinavian paper mills and companies.
In all SOMs used in the study the vector components were preprocessed before training so that the variance of each component was equal to one. This was done with linear scaling, so it could be reversed and the original data values could be obtained.