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Mathematical Methods of Multi-criteria Analysis and BSC Integration

Student: Anastasia Stogova

Supervisor: Tatiana Yakushkina

Faculty: Graduate School of Business

Educational Programme: Business Informatics (Bachelor)

Year of Graduation: 2017

The thesis is devoted to the studying the opportunity of application the mathematical methods of decision making during the Balanced Scorecard (BSC) implementation. The purpose of this study is to develop the scheme of application of multi-criteria methods implementing the BSC approach. In order to achieve the aim, there were assigned the tasks, including conduction of literature analysis of the main principles of BSC, the ways of its implementation and difficulties during this process, and the usage of mathematical approaches during the process of implementation. What is more, it is required to make an overview and provide an analysis of software that support both approaches. Then, it is necessary to develop the application scheme of mathematical approaches during the implementation of BSC and propose recommendations for its usage on the basis of literature review and comparative analysis of chosen multi-criteria methods. Besides, one of the main tasks is to provide the practical application of the developed scheme in the context of company’s case. The main results of this research are the developed scheme of using the mathematical methods of multi-criteria analysis with recommendations and the solution of Software Development Company’s case, which is implementing the BSC, using one of the proposed combinations of the methods described in the scheme. The results of application of the methods are presented graphically in such software as Bubble Chart Optimal Pro and SuperDecisions while the strategy map of the company was made in the program BSC Designer. The practical significance of this study lies in the possibility of application of the developed scheme during the process of creation of BSC approach in order to implement it successfully. This scheme will be of primary significance for project teams, which members do not have deep knowledge in the decision making area.

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