Risk assessment in a multilevel supply model

Jesús Francisco Escalante

Risk management is a structured approach that incorporates the uncertainty relating to a hazard, linked to a sequence of inherently human activities that include risk assessment, as well as other strategies for risk mitigation. The objective is to reduce different risks related to a pre-selected area. The classification is diverse, for example: threats by factors associated with the environment, technology, human error, organizations, among others. Risk assessment is consolidating as a support tool for the analysis of decisions in conditions of uncertainty, particularly for complex systems such as supply chains. Without a doubt, risk management is becoming a critical component in management decisions, as it is a continuous process. From this perspective, through parametric approaches and multivariate analysis, it has been possible to study and represent the data resulting from observing more than one statistical variable on a particular population. For this purpose, an instrument has been designed and validated for the collection of information through the configuration of an online interface.

Through the simulation of competitive risks, the cumulative incidence, the probabilities of occurrence and the compliance rates were estimated for a multilevel supply model. Also, an alternative and versatile solution was formulated to diversify the instruments, methods and techniques for treating risk in supply chains. The solution estimates the probability of failure for a given cause, before the specific expiration time. Finally, a case study was proposed where and through the simulation approach, the behavior of a set of instances was evaluated, whose analysis component is especially subject to sudden supply disruptions, associated with hydrometeorological phenomena. Through this analysis perspective, we contributed with a configuration that incorporates diagnostic components, their implementation and the evaluation of risk scenarios. The results in each of the different stages reveal that modeling, simulation, analysis and data processing are a vital factor in explaining the effects, as well as their ability to articulate high-value solutions for organizations.