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The Next Wave in IT Infrastructure Risk Management: A Causal Modeling Approach with Bayesian Belief Networks

The Next Wave in IT Infrastructure Risk Management: A Causal Modeling Approach with Bayesian Belief Networks
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Author(s): Daniel J. Hinz (J.W. Goethe University, Germany) and Heiko Gewald (J.W. Goethe University, Germany)
Copyright: 2006
Pages: 4
Source title: Emerging Trends and Challenges in Information Technology Management
Source Editor(s): Mehdi Khosrow-Pour, D.B.A. (Information Resources Management Association, USA)
DOI: 10.4018/978-1-59904-019-6.ch035
ISBN13: 9781616921286
EISBN13: 9781466665361

Abstract

The management of risks associated with information technology (IT) infrastructure becomes increasingly important, as companies may face severe negative outcomes in case of failures. This paper proposes a new approach to manage IT infrastructure risks even in highly dynamic environments. Currently, IT infrastructure and its risks are managed based on historical loss data, which allows very precise forecasts for potential risks in stable environments. However, this is not adequate for the increasing number of firms facing dynamic environments like outsourcing or merger scenarios. Therefore, the next wave in IT infrastructure risk management has to employ more qualitative methodologies. Based on an ongoing case study with two leading IT consultancies and a European service enterprise, this paper demonstrates, how causal modeling with Bayesian Belief Networks enables the prediction and, most important, the proactive management of IT infrastructure risks.

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