摘要：Expert methods involve the application of procedures in assessing the effectiveness of the functioning of a variety of classes of organizational systems. The task of assessing the effectiveness of the functioning of organizational systems is inextricably linked with the choice of particular indicators and the development of various methods for the formation of a generalized estimate. This article analyses methods of decision-making based on expert information, its aggregation, the selection of procedures for group coordination (Arrow, 1951; Litvak, 2004). The implementation of the generalized estimate of the quality of functioning of organizational systems is proposed. The methodology for constructing the multicriteria function of the object’s efficiency is divided into the structural identification and parametric identification. Managing complex objects must be done objectively (Artim, Novosad, Selivestrov, 2009; Savras, Yurnetes, 2008). In this case, the diversity and uncertainty inherent in the processes in these objects indicate the prospects for further development of these issues. The use of means of modern information technology in diagnosis is a useful and justified tool. The sequence of the solution of the task posed includes the formation of a hierarchical structure of performance indicators, the choice of the principle of constructing a generalized estimate, and the development of procedures for constructing this estimate. The complexity of solving these problems is determined by a number of objective difficulties faced by capital construction projects. First, there is the complexity of managing large industrial, highly mechanized processes performed by various teams with a large number of cooperative ties with a high level of specialization. Secondly, the impossibility of building up the capacities of construction organizations on the basis of extensive methods because of the specific demographic conditions prevailing in Ukraine. Thirdly, the lack of planning, the lack of reliable standards and a scientifically sound methodology for resource planning at the scale of large construction organizations and the industry as a whole. In the context of solving the task of managing complex organizational systems (construction production), an important place is occupied by the problem of determining the main indicators characterizing the activity of production. There arises the problem of forming on their basis an integrated assessment of the organization’s performance. This problem is solved by improving the system of evaluation criteria for complex hierarchical organizations, based on the need to improve the final results of the production cycle operation. Methodology. The purpose of the research in this work is the application of expert methods in assessing complex organizational systems, while the basis for the decision-maker is the expert findings and the consistency of their views. In the statement of the problem, it is assumed that the procedures for obtaining expert information are iterative. To achieve this goal, the following tasks were identified: it is necessary to form a hierarchical structure of performance indicators; choose the principle of constructing a generalized estimate; develop a procedure for constructing this estimate. Complex organizational systems are considered, i.e. systems in which the formulation of the problem and the decision-making on the basis of the information received from the controlled object is carried out by the management entity. The main element of the subject of management is the group opinion of the internal expertise of the enterprise. It is assumed that the initial stage in assessing the effectiveness of the functioning of organizational systems is the selection of a subset of the most significant indicators from the set of performance indicators of the organization and determining their “weight” using the parametric identification method. This is a condition for constructing a multicriteria function of the efficiency of the selection process and the creation of problem-solving algorithms.
