Risk Management as Knowledge Production: Application to Fast-Tracked Complex Multi-Stakeholder Airport Projects

Risk Management as Knowledge Production: Application to Fast-Tracked Complex Multi-Stakeholder Airport Projects

Alasdair James Marshall, Udechukwu Ojiako, Terry Williams, Jumah Rashid Al-Mazrooie, Fenfang Lin, Maxwell Chipulu
DOI: 10.4018/978-1-5225-9377-5.ch003
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Abstract

Rapid national infrastructure growth, as witnessed today in many countries such as the United Arab Emirates, commonly makes fast-tracking demands of what are already highly complex multi-stakeholder projects. Considering the long history of airport project failures in a number of fast-growing cities, the chapter explores risk management enhancements for addressing the challenges associated with transitions from project completion to commencement of operations. The proposed solution in the pages that follow is to have in place dedicated risk management teams spanning the transitions. These teams should provide a locus for stakeholder collaboration based on a shared concern to build excellence into the customer experience from commencement of operations onwards.
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Introduction

Being comprised of stakeholders in such a way as to ensure a thorough environmental scanning mix, the risk management teams advocated for in the present chapter should approach risk management not just as a process matching identified risks to controls, but - much more ambitiously - as an active intelligence gathering and knowledge production activity which continually informs and yet also transcends that process. Accordingly it can be argued that risk management, considered in both interconnected aspects, should take operational readiness and commissioning factors as their focus for developing abstract-categorical risk knowledge.

In other words these categories should be considered important for sensitising the minds of all who manage risks on projects, to specifc risks likely to arise which might otherwise be invisible owing to the overwhelming complexity of the projects. Such practice can be explained as harnessing abstract-general risk categories for purposes of top-down risk identification to capture logically aligned subsets of concrete-specific risk. To complement this view, it can be further explained in terms of the risk management metaphor which calls for project risk radars to be pointed towards where risks are most likely to materialise.

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