ІНФОРМАЦІЙНА ПІДТРИМКА ПРОЦЕСІВ МОНІТОРИНГУ ТА КОНТРОЛЮ У ПРОЕКТАХ

Abstract

The need to make grounded decisions while monitoring and managing the requirements of stakeholders is an integral part of the project management as a whole, which, in particular, determines the quality and success of the project. Known models and methods of project monitoring and control do not have a separate tool for monitoring the fulfillment of the requirements of stakeholders in projects and programs. Earlier authors suggested a model of juxtaposition of the hierarchical structure of the project with the hierarchical structure of the project requirements, the hierarchical structure of the project risks, the hierarchical structure of the project resources, and the organizational structure of the project. Thus, the "work-requirement”, "work-resource", "work-responsible", "work-risk" model (4R & WS) was established. The proposed method allows tracking the dynamics of project implementation by factors of the model (risks, requirements, resources, stakeholders, executors). The practical use of the method requires the formalization of the above relationships. If the relationship between "work-responsible" and "work-resource" can be specified explicitly, the links between "work-and-risk" and "work-requirement" should be given in the fuzzy form.The purpose of this article is to provide informational support for the 4R & WS method by constructing a process for formalizing fuzzy connections of the corresponding model.The process of formalization of fuzzy relationships was carried out to provide information support for the project monitoring and control method based on the comparison of the hierarchical structure of project activities with the hierarchical structure of project requirements, the hierarchical structure of project risks, the hierarchical structure of project resources, and the organizational structure of the project. A functional model of the process is constructed. The use of the results of expert evaluation for the construction of membership functions is suggested. The methods of constructing membership functions are analyzed; the use of the method of statistical processing of expert information is justified.