Powered by OpenAIRE graph
Found an issue? Give us feedback
addClaim

Quality, Risk and the Taleb Quadrants

Authors: Ron S. Kenett; Charles S. Tapiero;

Quality, Risk and the Taleb Quadrants

Abstract

The definition and the management of quality has evolved and assumed a variety of approaches, responding to an increased variety of needs. In industry, quality and its control has responded to the need of maintaining an industrial process operating as “expected”, reducing the process sensitivity to uncontrolled disturbances (robustness). By the same token, in services, quality has been defined as “satisfied customers obtaining the services they expect”. Quality management, like risk management, has a general connotation of dealing with current or potential problems, instead of opportunities. Quality, just as risk, is measured as a consequence of events defined by statistical properties. In this work, we propose an approach were quality and risk converge, both conceptually and technically, expanding the areas of concern confronted by both domains. This integrated view presents new challenges and significant opportunities to modern management methodology. The paper analyzes, with examples, a prospective convergence between quality and risk, and their management. Throughout such applications, we demonstrate the merging of quality management with risk management, in order to improve both the quality and risk management processes. In the analysis we refer to four quadrants proposed by Nassim Taleb for mapping consequential risks and their probability structure. Three case studies are provided, one on risk finance, a second one on management of telecommunication systems and a third one on risk based testing of web services.

Related Organizations
  • BIP!
    Impact byBIP!
    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    4
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Average
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Average
Powered by OpenAIRE graph
Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
4
Average
Top 10%
Average
Upload OA version
Are you the author of this publication? Upload your Open Access version to Zenodo!
It’s fast and easy, just two clicks!