Classifying client side FM organisations in the United Kingdom – 2 : How my in‐house FM organisation compares to my competitors and others?

Purpose – To present the development and results of the classification system based on the preceding paper ( Journal of Facilities Management ; Vol. 4, No. 2), which has highlighted ten patterns for the identification of similarity and dissimilarity of FM organisations (FMOs). Design/methodology/approach – This paper reports on the application of these ten patterns onto 22 in‐house FMOs in the UK, and tests the applicability and the validity of the classification system. Pattern recognition's unsupervised clustering is used for measuring the similarities between the sample population. Two particular statistical methods have been used in hybrid: principal component analysis and k ‐means. Findings – As a result of the analysis, out of 22 samples, three classes of FMOs are found. The two of these (w 1 and w 3 ) involve mixed market sectors and the other involves only healthcare FMOs. Research limitations/implications – The classification system enables us to group FMOs according to their similarities for identification and description. Ore specifically there are three implications of the system: networking for best practice sharing and learning, development of demand side market intelligence, and comparison of performance in respective groups. Originality/value – The classification system introduces a systematic approach to understand and classify FMO, and hence describe their characteristic features. It has been demonstrated in this paper that results of such as system lead to knowledge and practice exchange between two FMOs.