Disruptive Change to Correct Our Myopia in Enterprise Risk Management
- Al-Haidar Ali (Kuwait Foreign Petroleum Exploration Co. KUFPEC) | Gurney David (Kuwait Foreign Petroleum Exploration Co. KUFPEC) | Williams Craig (Kuwait Foreign Petroleum Exploration Co. KUFPEC Australia)
- Document ID
- Society of Petroleum Engineers
- SPE Kuwait Oil & Gas Show and Conference, 13-16 October, Mishref, Kuwait
- Publication Date
- Document Type
- Conference Paper
- 2019. Society of Petroleum Engineers
- ERM, Enterprise Risk Management, Disruptive Change, Myopia
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- 32 since 2007
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Welcome to the future of ERM transforming from descriptive to analytic data for the risk register as the main objective because the risk register without statistical analysis equates to myopia, like a Heliographic Alphabet without the Rosetta Stone to translate. The scope of this paper is to demonstrate a statistical approach for the risk register where until now decisions have been made on descriptive data.
A proactive analysis is used in this paper to analyze the risk register data that will enhance our understanding of the risk register’s items to subsequently make better decision. The approach is to quantify the descriptive data in a statistical platform called SPSS (Statistical Package for Social Sciences). The quantified data is first tested using Coefficient Alpha analysis. Coefficient Alpha measures the reliability of the coded data, that is the accuracy level of the likelihood and impact items in the risk register. Coefficient Alpha is a matric that attempts to reflect our mindset or cognitive level during the risk assessment phase. Reliability is expressed as a number ranging between 0 and 1, where 0 indicating no reliability (much error) and 1 indicating perfect reliability (no error) (Peter 1979).
The result of Coefficient Alpha analysis is a composite score (%) to aid whether to progress to the next stage. The entire coded data is uploaded to the SPSS platform or Microsoft Excel to analyze the data for correlation and regression of the assessment items that affect the risk degree in the risk register. From observations related to the scale of likelihood with impacts levels, and the chosen items should be revised because their correlations will be in degradation mode after time. The new method is wider than the current approach, leading to better decisions about how to treat high and very high risks. In the new method the risks to be treated will be selected based on which items from the evaluation list are most affecting the risk degree.
The new method can form a comprehensive of risk management. This will enhance our understanding of the risk register in the petroleum industry, enhancing reporting, as well as removing some evaluation items that have no effect on the risk degree and adding alternative items in the risk register.
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