SWOT Analysis as an Effective Way to Obtain Primary Data for Mathematical Modeling in Project Risk Management

EasyChair Preprint no. 4768

Abstract

The paper proposes to consider the use of such a classic risk analysis tool as a SWOT analysis in conjunction with the construction of a Markov model for further analysis of the elements of a SWOT matrix. A review of the areas of application of the SWOT analysis is suggested under the assumption that in all these cases, the approach described by the authors is also possible. It is proposed to use an extension of existing analysis methods based on the SWOT matrix, including TOWS and similar methods based on combinations of the effects of pairwise combinations of blocks of the SWOT matrix. We consider the option of constructing an adjacency matrix on the basis of the entire set of SWOT factors with its further analysis using both Markov methods and analysis of the number of connections that may arise in each particular case of applying this approach in an adjacency matrix of the corresponding order corresponding to the state when the matrix ceases to contain "empty" (equal to zero) elements. An example of a fragment of a real complex SWOT analysis implemented using Microsoft Excel software is given. It is proposed to use the described method in the management of portfolios and programs of projects of organizations

Keyphrases: adjacency matrix, applying swot analysis, Dynamic SWOT Analysis, level swot matrix, Markov Decision Process, multi level swot, Problem solving and planning, project management, risk management, SWOT analysis, SWOT Matrix, SWOT model, swot radar screen, System Landscape, telescopic observation strategic framework, TELESCOPIC OBSERVATIONS, TOWS analysis

@Booklet{EasyChair:4768,
  author = {Dmytro Lukianov and Mikhail Mazeika and Viktor Gogunskii and Kateryna Kolesnikova},
  title = {SWOT Analysis as an Effective Way to Obtain Primary Data for Mathematical Modeling in Project Risk Management},
  howpublished = {EasyChair Preprint no. 4768},

  year = {EasyChair, 2020}}