Project management methods - Economic evaluation of investments

Project Management Methods

In recent years, the theory and practice of project management has been enriched by all possible methods of quantitative assessment of the impact of organizational and production factors on the performance of all participants in the investment project, which allow finding solutions close to optimal.

The most commonly used mathematical methods, based on the models of operations research: correlation-regression analysis, mathematical modeling and programming, the method of peer review, etc. Mathematical models allow us to find various significant indicators of the effectiveness of the project. Several different information and optimization models can be used to manage one project.

The type and structure of models are determined by the tasks of project management and the availability of reliable information to obtain reliable solutions.

Depending on how the cause-effect relationships and the requirements of project management practice are reflected, all mathematical models can be divided into deterministic and stochastic models.

Models in which the values ​​of variables are assumed to be known for rigid constraints and conditionally reliable are usually called deterministic. Among them, according to the degree of mathematical abstraction or the smoothening of the values ​​of variables, two types of economic and mathematical structures can be distinguished: and simplified. Complex economic and mathematical models provide more accurate results, but require a large amount of source information and special software. The limited time allocated for preparation and decision-making in general and in project management systems, especially, hampers the wide application of these models. Therefore, in the practice of project management, rather simple models are most often used.

A special place is occupied by network models (graphs), which are graphoanalytical, that allows in a visual form to describe the entire production process: from the origin of the idea of ​​the project to its implementation.

Typically, the implementation of a deterministic approach to modeling analysis and decision making involves, on the one hand, the obtaining of an unambiguous solution, and on the other hand, the refinement of these solutions by introducing an element of randomness in terms of probability theory. The latter makes it possible to assess the consequences of unforeseen disruptions, for example, the failure to design or build the buildings and structures planned by the previously approved plan. At the same time, mathematical modeling of deterministic processes becomes a special case of stochastic, probabilistic approaches.

Unfortunately, very often managers tend to use only those methods and models that they are familiar with, and not those that the current situation requires. However, models based on the processing of a large amount of information are rarely required by users.

One of the reasons limiting the application of the probabilistic approach in project management is the cost of implementation of the method, increased in comparison with the deterministic approach, including the costs of collecting and processing information.

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