The five structural columns of risk analysis techniques

The five structural columns of risk analysis techniques

(Parte 1 de 7)

The five structural columns of risk analysis techniques Essay

Antonio Fernando Navarro[1]

Presentation In this essay aims to treat the topic related to risk analyses, these risks taken here not only as a result of dangerous situations that bring or represent danger, as well as presenting, simultaneously, all the features required for a risk to be considered insurable, employing himself, figuratively, the pillars as fundamentals on which should be based on the risk analysis, to achieve the desired results. Decision makers usually are based on facts and data, experiences good or unsuccessful, but hardly contemplate the horizon at long term, prospecting the future risk. Thus, it is intended in this article present some considerations on the theme and some proposals that may be useful in the search for the future success of the enterprises or corporate continuity. It is worth mentioning that according to Hemard[2] , the risk to become

"insurable" must present the following characteristics: be uncertain, future, possible, independent of the will of the parties, capable of causing damage or loss and these are conditions they can be measured. In this way, the definition of Hemard1 already leads us to look to the future and realize that the multiple possibilities of entanglement are possible and should always be considered. Its definition includes both a mixture of concepts, adding uncertainty, i.e. the possibility of right or wrong, excluding perhaps the future State, or distant from the present moment, the direct involvement of any of the parties to the emergence of the occurrence, the certainty that the event will be able to cause loss or damage, since, to the contrary, only one study and register warrant, and adds the fact that the consequences of these risks can be assessed, because unlike, he wouldn't have policies to promote repairs and/or damages. It is necessary to emphasize the aspect of the affective value of an asset. One person received a heritage well and very fond of this. Destroyed by various causes what would be the value of the repair? No matter how much you seek to achieve the exact value still could not meet the wishes of whoever lost, since for this that well lost no "had value" or was something immeasurable. Are important concepts for anyone who wants to devote himself to the study of the risks and the analysis of consequences of same, with views on the criteria for compensation or reparation.

Introduction The technical analysis subsidiaries for the acceptance of risks and their rates must take into account the analysis not only of the risks as well as associated losses. To this end, it is necessary to a better understanding of the failure modes that generate claims, as well as the need to interrupt the process of spread of the losses, which can be by means of suitable devices and equipment, as well as altering the characteristics of the buildings and the adequacy of layout. There are several ways or procedures for analyzing a risk taken here as an enterprise, installation, manufacturing or industrial unit, or something that is important and valuable to awaken interest in insuring specific. There are from simple checks with simple notes and photographic reporting, use of forms containing the minimum information required for the underwriter to accept and taxing the risk until the employment of sophisticated computer programs. It is suggested the use of risk analysis techniques based on five pillars as follows. Also understand that for every situation there might be a more appropriate analysis. Over decades of activity we're used to talk more with those of operate and perform maintenance on equipment and installations and in the perception of the climate in the work environment. We understand that a considerable portion of claims could be avoided if there was a larger attention to employees who operate the facility. Human participation in accidents is preponderável and cannot be left aside.

1st Pillar: motivation for the risk analysis Firstly you have to have the motivation to undertake a risk assessment. The motivation may be the previous evaluation, risk behavior along a well protection contract, or contract of insurance, and even at the end of this contract. The risks are assessed, firstly with the aim of identifying its causes, and, in a second moment, its consequences, this important evaluation in order to obtain the information relating to the amount of losses. On the occasion of the materialization of the risks the final results can be translated by: ·property damage,

·financial damage,

·personal injury,

·damage to the image of the companies,

·civil liability damage

·damages for loss of market, among others. The risk analyses are structured as follows: ·Analysis for evaluation of potential losses and/or damages;

·Analysis for the identification of possible extensions of the losses and/or damages;

·Analysis for the identification of probability of occurrence and manifestation of the risks – claims. The tests usually are initiated with: ·understanding of the workplace and its surroundings, through actions of inspections, risk management or implementation of methodologies like surveys; ·carrying out technical surveys by reading specific bibliographies, addressing issues such as those existing in the environment inspected. Often a specific analysis may be subject to specific, usually also study published in scientific or technical articles; ·conducting research on databases that indicate not only the amount of events in facilities similar to the environment under study, as well as to provide data on the losses and additional information. These databases may be disclosed by specialized companies or obtained with insurers. If the statistics are appropriate and the information may be obtained through the teams of operators of facilities and equipment, as well as the maintenance of these goods can move to the next step, in which can be associated with the groups of information obtained at existing facilities. Two information are important for risk pricing: ·frequency of accidents, or interval between occurrences of faults, and

·severity or seriousness of losses. Very simplified, the at-risk pure can be represented by the Association of these indicators.

tR = ƒ x S Following a structured process adopted in the conceptual analysis of losses in the first phase are used computer models to the reproduction of the damage. At this stage may be employed models available on the market. The following are the values obtained are entered in spreadsheets and, with the use of appropriate methodologies (there is almost a hundred methods of analysis that can be used or adapted), trace the curves that contain the points regarding the frequency and severity of losses. The curve can be called risk rates curve.

One must be attentive to the choice of the worksheets so as not to have rates directly linked to the severity of the losses or the frequency, in isolation. Frequency growth gives us an information, that the claims are frequent and common or, due to a variety of possible causes, since the lack of maintenance to the misuse of the facility. The severity of losses provides other information, of equipment or installations and have high value or are relevant to the process, as well as those losses have the possibility to expand to other environments. A risk analysis is not based solely on interpretation of the "vision" of a specialist during the recognition of risks in field activities, but rather, supported or supported by technical analysis structured and recognized. Some of the techniques and/or methodologies employed in the processes of analysis are presented below. It is worth saying that the number of methods of analysis or interpretation or growing simulation, developed by specialized companies in this area. That means that much of what you have today is the product of analyses and interpretations of scholars, developers of software companies and institutions which cast products for the development of the activities of inspection environments. These relations are established through the interference of man (operator) with the system under study or foreseen safety systems, or in situations that may generate different types of damage, according to the way in which the event occurs. Can be presented as examples of analysis and methodologies or, in addition, as statistical support for simulation of computational or events:[3] 1. AAE (event Tree analysis technique for the analysis of the consequences of an unwanted event, describing the temporal sequence of facts, which can be generated due to the occurrence of equipment failures, problems in a given system or due to operational errors during the execution of a given activity, establishing a series of relationships between the initial event and subsequent events [interference], which, when combined, result in the aftermath of the accident); 2. AAF (fault tree analysis-method of analysis of products and processes that allows for a systematic and standardized assessment of possible failures, establishing its consequences and guided the adoption of preventive or corrective maintenance); 3. AHP (Analytic Hierarchy Process-rationally understandable procedure for structuring problem, representing and quantifying the elements comprising it, relates them with the global targets and to evaluate alternative solutions. It is widely used in the most varied situations and in the most varied segments); 4. Alpha of Cronbach's alpha (validation of measurements carried out through the use of Likert scales, widely used methodology for assessing levels of process reliability); 5. AMD (Multi-criteria decision Aid method used as a tool of analysis for decision making support in conflict resolution negotiated, in trouble with multiple criteria. Is based on Newtonian and Cartesian method of thinking which seeks to treat complexity with decomposition and Division of the problem factors, which can be further decomposed into new factors to the lowest level, establishing relationships that can then be synthesized); 6. Bayesian analysis (Bayesian Approach to statistical inference is proposed to combine data obtained from observations with evaluations or subjective judgments); 7. Analysis of Clusters (a cluster is a collection of objects that are similar to each other (according to some fixed similarity criterion) and objects belonging to other dissimilar clusters); 8. Process analysis and projects (analysis that takes into account the possible associations and their results in processes and projects, aiming at the Elimination of failures); 9. Integrated analysis of scenarios (environments or scenarios are horizons that have high probability of occurrence and that can be associated with other, randomly or not, change the expected results); 10. 6 Sigma (measurement of the performance of process-metric to check the amount of defects or nonconformities from control methodologies that cause the amount of these defects remain below 3.4 defects per million of services or goods manufactured. The methodology of control – metric, is based in DMAIC and DMADV methodologies); 1. Multi-Analysis scenarios (multi-cenários analyses take into consideration that there are inferences between those and that these can be evaluated, with a view to reducing impacts of occurrences); 12. Multivariate Analysis (statistical methods that analyze multiple measures simultaneously on each individual or object under investigation); 13. Pre-task Analysis (risk analyses carried out prior to the start of tasks); 14. Cognitive Tests (cognitive design proposes a working explanation of the mind on three levels: to the physical level, neurobiological; the symbolic level distinct and irreducible to physical; and the semantic or representational level itself.); 15. ANOVA (analysis of variance -used when you want to decide whether sampling differences observed are real (caused by significant differences in populations observed) or casual (arising from mere sampling variability). Therefore, this analysis assumes that the chance only produces minor deviations, being the major differences generated by actual causes); 16. AHP (Analytic Hierarchy Process-method to assist people in making complex decisions. More than determining what the correct decision, the AHP helps people choose and justify your choice); 17. Bayesian analysis (describes uncertainties about invisible amounts of probabilistic form. Uncertainties are modified periodically after observations of new data or results. The operation that calibrates the measurement uncertainty is known as Bayesian operation employing Bayes); 18. Analysis of uncertainty or Normality of processes; 19. Integrated analysis of work (study and careful documentation of each step of the process of work, identifying existing or potential dangerous situations and determining the most appropriate way to perform activities for the reduction, elimination or mitigation of hazards); 20. Pre-task Analysis (methodology that associates employment of locks or barriers to existing risks protecting workers and working environment); 21. APR-preliminary analysis of risks; 2. Fault tree; 23. Event Tree; 24. Behavioral Audit; 25. Barrier crashes; 26. BBS (Behaviour Based Safety-application that allows, with the file information brought by security professionals in their field visits, and in workers ' behavioral analysis, identify the situations of risks and the actions needed for the changes, aimed at reducing the rates of accidents); 27. BOM (Bill of Material-groups in just one location, all static data that describe the attributes of the items used in company-identification number, name, number of engineering drawing, lead time, safety stock, among others); 28. Bowtie Analysis method (the method of analysis that represents the drawing of a bow tie, being employed to analyze and demonstrate causal relationships in high-risk scenarios); 29. BSC (Balanced Scorecard); 30. COBIT (Control Objectives for Information and Related Technology); 31. Safety culture; 32. Organizational Culture; 3. DELPHI (programming language);

34. DMAIC (Define Measure Analyze Improve Control-structured methodology in five phases: the first defines the problem under review from consumer feedback and the reassessment of the goals of the project; the second one has the measurement and investigation of problems relating "causes-effects; in the third stage these are the data and the map to identify the root causes, or root causes, tracing-if prognoses for the implantation of the opportunities for improvement; in the fourth step the processes in place are improved and optimized, based on usual techniques of redesigns of experiments, standardization of work processes, development of new processes; in the fifth step control processes to ensure that the variances observed and analyzed do not happen again. Stresses that such methodology pose be applied to any productive activity, including the operational activities of insurance); 35. DMADV (Design for Six Sigma-methodology supplement, support or confirmation analysis, which, following the example of the DMAIC suggests, in five stages: setting goals that are consistent and coherent with the problems observed and/or the demands of customers, the company's strategies aligned; measurement and identification of critical to quality characteristics, product capabilities, production process capability and risks; and development of alternatives to existing design; project optimization and planning and control activities tests; design review, additional production testing and analysis of results, all before the devices operate productive); 36. ECM (Engineering Change Management); 37. Electre Tri (troubleshooting ordered classification); 38. Enterprise Resource Planning (ERP-systems composed of a single data base and by modules that support various activities of business processes of the companies); 39. Behavioural Factors; 40. Human Factors; 41. FDD (Feature Driven Development); 42. FINE (Mathematical Evaluations for Controlling Hazards); 43. Fuzzy (logic based on the theory of Fuzzy sets, differing from the traditional logic systems in their characteristics and their details); 4. GUT (array of Severity, urgency and trend); 45. HAZARD (same as risk); 46. HAZID (Hazard Identification); 47. HAZOP (Hazard and Operability Studies); 48. HFACS (Human Factors Analysis and Classification System); 49. HP (Health Promotion); 50th. LCCA (Life Cycle Cost Analysis); 51. Likert scale type (psychometric response used in questionnaires, and is the most widely used scale in opinion polls. To respond to a questionnaire based on this scale, the asked specify their level of agreement with a statement); 52. MAGIC (Multi-Attribute Global Inference); 53. MAIM (The Merseyside Accident Information Model); 54. Mind maps (interpretatica and discussional analysis process where problems are laid out in diagrams for study purposes); 5. Risk Maps; 56. MASP (Method of analysis and solution of problems); 57. MCDA (Multicriteria Decision Aid);

(Parte 1 de 7)