PPM-HC: a method for helping project portfolio management based on topic hierarchy learnings
by Ricardo A.M. Pinto; Flavia Bernardini; Ricardo M. Marcacini
International Journal of Business Intelligence and Data Mining (IJBIDM), Vol. 18, No. 3, 2021

Abstract: The projects categorisation is a crucial step in the project portfolio management (PPM). Categorising projects allows the organisation to identify categories with a lack or excess of projects, according to its strategic objectives. In this work, we present a new method for project portfolio management based on hierarchical clustering (PPM-HC) to organise the projects at several levels of abstraction. In the PPM-HC, similar projects are allocated to the same clusters and subclusters. PPM-HC automatically learns an understandable topic hierarchy from the project portfolio dataset, thereby facilitating the (human) task of exploring, analysing and prioritising the projects of the organisation. We also proposed a card sorting-based technique which allows the evaluation of the projects categorisation using an intuitive visual map. We carried out an experimental evaluation based on a benchmark dataset and we also presented a real-world case study. The results show that the proposed PPM-HC method is promising.

Online publication date: Fri, 23-Apr-2021

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