A Fuzzy Multicriteria Approach for It Governance Evaluation

Abstract

This work seeks to provide a new multi-criteria approach to assess IT Governance (ITG) in the area of Strategic Alignment. The complete methodological development process is described. The evaluation model uses Fuzzy Analytic Hierarchy Process (FAHP) and it is targeted to IT processes, more specifically to the COBIT © IT maturity levels, domains and processes, thus providing a differentiated analysis of importance for each item. Its relevance is related to addressing isolated and individual evaluation criteria that are normally practiced in audits of processes. The model allows generating information that extends the guarantees of compliance and corporate governance from different organizations. This research demonstrates that the combined use of multi-criteria decision methodologies and soft computing proves to be particularly suitable for Strategic Alignment such as the focal area of COBIT. The model was applied in a big retail Brazilian company.

A multi-criteria decision making model for the selection of open data management systems

“…For the sake of simplicity, trapezoidal or triangular fuzzy numbers are the most commonly used numbers (Buckley et al, 2001;Chang, 1996;Kwong and Bai, 2003). A triangular fuzzy number is a special type of fuzzy number whose membership is defined by three real numbers, expressed as (a1, a2, a3), where a1 is the lower limit, a2 the most promising and a3 the upper limit value (Cobo et al, 2014;Dubois and Prade, 1978;Zadeh, 1975). The membership function μ(x) of this triangular fuzzy number may therefore be described as (1) (Chang, 1996):…”

“…When comparing two elements Ei and Ej, the exact value ratio aij can be approximated with a fuzzy ratio which is represented by a fuzzy triangular number. The construction of a hierarchical model in FAHP is exactly equal to the original AHP (Cobo et al, 2014). The fuzzy numbers required to form the decision matrix may be determined directly according to the decision maker or may derive from linguistic variables in a verbal scale, which can be then converted into fuzzy numbers using a suitable conversion as shown in Table 1 and the fuzzy pairwise comparison scale depicted in Figure 1.…”

“…In order to construct a positive reciprocal matrix of pairwise comparisons, a full set of n (n-1) / 2 comparison judgments are required. The pairwise comparison matrix is constructed as equation ( 2) (Cobo et al, 2014;Dubois and Prade, 1978):…”

“…On the contrary, fuzzy concept refers to those problems that are uncertain, indefinite, and abstract (Hodgkin, Belton and Koulouri, 2005;Saaty and Vargas, 1987;Zadeh, 1975). A useful decision making model should be able to handle multiple fuzzy evaluations by aggregating the information of the related decision making problem (Chang, 1996;Cobo, Vanti and Rocha, 2014). A Fuzzy Analytic Hierarchy Process (FAHP) provides both the advantages of fuzziness, which is compatible with the uncertain, vague and subjective nature of decisions, and AHP as a systematic approach to make these decisions in complex Multi-Criteria Decision Making (MCDM) problems (Buckley, 1985;Chang, 1996;Saaty and Vargas, 1987).…”

Governança de Tecnologia da Informação: Uma Análise do Nível de Maturidade em Empresas Atuantes no Brasil

“…Ele foi desenvolvido pela Information System Audit and Control Association (ISACA), constituindo-se num referencial de boas práticas reconhecidas internacionalmente que permite a avaliação do controle e da efetividade das ações da área de TI, seja por auditores ou por gestores de TI e de negócio. Fernandes e Abreu (2008) definem o Cobit como um conjunto de diretrizes para processos, envolvendo controles e auditorias, cujo foco principal estaria na redução de riscos, na confiabilidade e na segurança da TI (Cobo, Vanti, & Rocha, 2014).…”