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Modeling of complex systems is important to decrease the risk in decision making (Cardona & Hurtado, 2000). Modeling in practice combines the experience of analysts which seeks to represent reality through the use of variables that are important in the case to be modeled (Flores, 2013). On one hand, modeling must deliver results that support the decision-making process (Flores, 2013). On the other hand, the modeling should be as objective as possible in order to reduce the uncertainty of the situation to be analyzed (Pena de Ladaga & Berger, 2006).
In practice, the situation to be modeled and the representation of its variables is based mainly on the experience of the analysts on the context under study. This process of analysis requires considerable knowledge and, above all, an active participation of experts who seek the causal relationship between the variables that affect the model (Flores, 2013). In other words, the analyst requires a lot of experience and detailed knowledge about the subject (Flores, 2013). Under this logic, models of system dynamics seek standardization of the modeling process by creating predefined structures which can generate modeling scenarios in a simpler way (Braun, 2002; Bulla, 2013). Consequently, under this type of analysis, analysts are forced to create models, which may not be fully representative of reality, limiting their use in practice. On the other hand, if the analyst does not have the necessary experience on the subject, he may discard and/or omit variables that are relevant in modeling.
Under the limitation above-mentioned and from a problem-based perspective, OTSM-TRIZ presents different tools for both modeling and analyzing in order to present the problematic situation in the most realistic and plausible way. The objective of OTSM-TRIZ, specifically of the Network of Problems (NoP), is to represent the causal-reality, looking for the associated problems in a situation, in addition to looking for solutions that allow undertaking the situation in conflict. The approach proposed by the NoP allows raising the analysis of the situation more efficiently (Savransky, 2000). From the point of view of the scenario analysis, the limitations of the OTSM-TRIZ are based on the difficulty of evaluating the effects of the solutions created in the model over time; consequently, the process of analysis and evaluation in OTSM- TRIZ is considered practically separated from the generation of solutions, which discontinues the process of analysis.
In this paper, a systematic and structured methodology that allows modeling and evaluating the resolution of a complex situation is proposed. The methodology combines the logic of OTSM-TRIZ and system dynamics, which allows generating a more holistic, complete and structured analysis process. In other words, this article proposes a combination of system dynamics and OTSM-TRIZ which allows obtaining a more holistic understanding of a future situation, given certain influencing variables by combination of real data and experts’ knowledge by using decision theory. The main advantage of the proposed methodology is explaining complex scenarios within a system of multiple variables where both qualitative and quantitative analysis are required to better understand a specific situation over time.
The methodology consists of six structured steps which are considered as an operational algorithm that the analyst must follow during the analysis process. To validate the proposed integration, a case study is presented in a real context in the city of Valparaiso, and it is related to the analysis of catastrophes, such as fires in the city.