Integrating Risk Management and Quality Management- Juniper Publishers

  Annals of Social Sciences & Management Studies-Juniper Publishers

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The International Organization for Standardization (ISO) is a not-for-profit organization, recognized as an independent non-governmental international organization with memberships in 161 national standards bodies that makes International Standards. Through the contributions of its members, ISO brings experts together to develop international standards that are aimed at meeting global challenges. The standards are developed in a voluntary, consensus-based and market relevant manner. Members are divided into three categories, with varying access and influence over the ISO system. Its vision is the worldwide acceptance and use of the ISO products. This would enable trading locally and globally and contribute to progress and prosperity on the individual and the organizational levels. The goals of ISO/TC 176 are centered around widening the acceptance of their standardization of the quality management principles, continuing to evolve the standards to meet the global challenges, and lead the discussion on issues related to management systems. The ISO quality management international standards are based on seven quality management principles: customer focus, leadership, engagement of people, process approach, improvement, evidence-based decision making, and relationship management. There are other quality management frameworks, Baldridge Criteria for Performance, Excellence, The European Foundation for Quality Management Excellence Award, and Total Quality Management.

A risk-based decision-making methodology is a decision-making process that integrates risk assessment in some form into the decision-maker’s point of view regarding the favorability of a decision alternative so as not consider the perceived performance of the alternative as the sole basis on which to decide. Hence, risk-based decision-making considers both comparative performance and comparative risk. Multi-Criteria Decision Analysis (MCDA) is a suitable integrative decision analytic process that allows for this two-dimensional evaluation of decision alternatives. There are two broad approaches to MCDA; multiple attribute decision making (MADM) and mathematical programming problems. The focus in this work is on MADM problems. MADM techniques have two large families; outranking and multiple attribute utility theory (MAUT). The decision-making methodology proposed is based on a MAUT technique called Analytical Hierarchical Process (AHP). Though MAUT method vary, a common structure includes the following steps;

1) define alternatives and attributes,

2) evaluate each alternative with respect to each attribute,

3) estimate relative importance weights to the attributes,

4) aggregate weights and attributes evaluations,

5) conduct sensitivity analysis and recommend a solution.

The output of a MADM problem solution is the selection of a specific decision alternative, the ranking of all decision alternatives, or some other form of 1()()niiiivxwvx==Σ, where ()iivx is the value of alternative x with respect to the ith attribute, wi is the importance weight of the ith attribute, and n is the number of attributes. AHP is used for setting up a performance criteria tree and determining their importance and utilizes pairwise comparison which allows for comparing pairs of alternatives on a 1-9 scale with regards to each criterion. AHP transforms value preferences into ratio scale weights that are combined into a linear additive weight for each alternative. AHP has three functions. The first is structuring complexity. AHP uses hierarchy to structure the factors that are relevant to the decision problem. This is in-line with how people classify information and naturally structure problems. The second function is measuring on a ratio scale, which are higher than other measurement scales and is also used by MAUT. The third function is synthesizing a decision analysis of multiple dimensions [1]. Furthermore, AHP has three basic principles. The first principle is decomposition, which refers to decomposing the decision problem into a structure of hierarchy of clusters, sub clusters, and so on. The second principle is comparative judgments, which is the utilization of pairwise comparison to compare each pair of criteria and derive local priorities in their level of the hierarchy with respect to their parent in the higher level. Finally, AHP has three axioms. The first axiom is reciprocity of comparison pairs. This means that if A has 5 times the value that B has, then B has 1/5 the value that A has. The second axiom is homogeneity, which means that the elements being locally compared in terms of importance or value should not differ by more than an order of magnitude. The third and final axiom is that the judgement made regarding the value or importance of an element, does not depend on its child elements, but on the elements within its cluster, and with regards to their parent element. Zahedi [2] conducted a study that shows that utilizing AHP’s pairwise comparison and MAUT’s value functions can be compatible and coherent as long as the interpretation of the DM’s preferences regarding the attributes and their weights is coherent. The implication of Zahedi’s work is that it is possible to utilize pairwise comparison and value functions within the same framework in an integrated way.

Furthermore, based on the identified performance criteria and their importance, risk assessment is conducted, and a comparative risk score is determined for the decision alternatives. The QMS is a framework that governs the processes of an organization. Hence, it should also govern and be relevant for the organization during a decision-making process. Particularly, the decision problem that is most relevant to ISO 9001 and the strategic direction of the organization is products and services selection. The proposed methodology discusses the integration of ISO 9001 with the decision-making process. Specifically, three points will be discussed in the context of developing a process that supports factual-based decision making within ISO 9001; extracting data and information from QMS for developing a decision-making process, the documentation of the decision process in an ISO 9001 compatible way, and strategic mapping of the decision performance criteria and the organizational context. The decisionmaking methodology proposed in this study is based on Analytical Hierarchical Process (AHP) and the Multi-Attribute Utility Method (MAUT). MAUT is a technique for measuring values of a set of important attributes for a set of alternatives and weighing the relative importance of these attributes from the decision-maker’s perspective to generate a multi-attribute utility score. It has 5 steps;

a) Define alternatives and attributes.

b) Evaluate value of each alternative.

c) Assign importance weights.

d) Aggregate weights and values to obtain overall utility evaluation of alternatives.

e) Sensitivity analysis.

Risk assessment holds a central place in ISO 9001, with the requirement of adopting ‘risk-based thinking’ as the hallmark of the role risk assessment plays in the new ISO 9001 edition. This paper will discuss the role of risk assessment in QMS that is mandated by ISO 9001 and how this role needs to also be present when making decisions. The terminology and conceptualization of risk assessment will be based on ISO 9001 as well as ISO 31000, which is a designated risk management framework that is referenced by ISO 9001.

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