TY - THES

T1 - Strategic Quantitative Project Risk Analysis – Developing a Project Risk Portfolio by Using the Example of OMV’s Project Risk Management

AU - Uschold, Alexander

N1 - embargoed until 03-12-2018

PY - 2013

Y1 - 2013

N2 - A Risk Portfolio model process for the Project Risk Management of the OMV was established in this thesis. Before it is possible to work on a process the implemented structure and back-ground stories of the risk management departments have to be discovered and analysed. Examples would be the Financial Risk Management and the Enterprise Wide Risk Management – also the specific projects. Given that the risk management departments are closely linked together and are also dependent on each other, it has to be determined which records have to be conditioned for the other departments, so that they can run their calculations and simulations. Currently there is no implemented handover process between the Project Risk Management and the Enterprise Wide Risk Management – the so called “umbrella” department – and so the only problem are the overrun costs (CAPEX), the delay and the quality, in form of distribution types and scalars, for later implementation as a formatted “hand over package”. Usually the OMV assessed the specific project risks in self-made Excel tables because there wasn’t an implementation of a standardized risk processes into the Project Risk Management. So it was not possible to gain a risk portfolio, because there was no historical data stored in a standardized database. Because of that problem, the Project Risk Management implemented a risk database in 2012, which is called Easy Risk of Det Norske Veritas (DNV). Since all “Capital Projects” of OMV – these are all projects with an investment of minimum 20 million Euros – and all detected risks must be implemented into this system, for later qualitative analysis and evaluation in decision matrices. Today it is common practice that all projects detect, define and assess their risks only in a qualitative way and not in a quantitative one. So it is impossible on the one hand to gain and run a quantitative risk analysis and on the other hand to create a Risk Portfolio. As a result of this status the Model Process was generated for an aggregation of all single risks to one risk portfolio and for a risk handover process to the other risk departments (EWRM and FRM). After that the process must be attuned to available tools – like data, software and knowledge/resources of employees. The model process was obtained with the help of a common risk break down structure, the so called TECOP (technical, economical, commercial, operational and political risks), and analysed by Monte-Carlo simulation. Because of the missing data history it was impossible to take concrete and precise analysis methods, for example the calculation of correlation coefficients or the use of Copulas. It is very important to have a big database, because without a big data pool the calculations cannot produce useful outputs. Those methods can be used in seven or ten years. Finally, it has to be taken into account, that data histories are a very useful and valuable basis, however nobody is able to guaranty the course of the future through simulations of the past. It has to be maintained, that the entire analysis as well as predictions should be considered solely as a guide, because different risks of the past and the present can affect project developments in a different way; according to the motto "a risk is always a risk."

AB - A Risk Portfolio model process for the Project Risk Management of the OMV was established in this thesis. Before it is possible to work on a process the implemented structure and back-ground stories of the risk management departments have to be discovered and analysed. Examples would be the Financial Risk Management and the Enterprise Wide Risk Management – also the specific projects. Given that the risk management departments are closely linked together and are also dependent on each other, it has to be determined which records have to be conditioned for the other departments, so that they can run their calculations and simulations. Currently there is no implemented handover process between the Project Risk Management and the Enterprise Wide Risk Management – the so called “umbrella” department – and so the only problem are the overrun costs (CAPEX), the delay and the quality, in form of distribution types and scalars, for later implementation as a formatted “hand over package”. Usually the OMV assessed the specific project risks in self-made Excel tables because there wasn’t an implementation of a standardized risk processes into the Project Risk Management. So it was not possible to gain a risk portfolio, because there was no historical data stored in a standardized database. Because of that problem, the Project Risk Management implemented a risk database in 2012, which is called Easy Risk of Det Norske Veritas (DNV). Since all “Capital Projects” of OMV – these are all projects with an investment of minimum 20 million Euros – and all detected risks must be implemented into this system, for later qualitative analysis and evaluation in decision matrices. Today it is common practice that all projects detect, define and assess their risks only in a qualitative way and not in a quantitative one. So it is impossible on the one hand to gain and run a quantitative risk analysis and on the other hand to create a Risk Portfolio. As a result of this status the Model Process was generated for an aggregation of all single risks to one risk portfolio and for a risk handover process to the other risk departments (EWRM and FRM). After that the process must be attuned to available tools – like data, software and knowledge/resources of employees. The model process was obtained with the help of a common risk break down structure, the so called TECOP (technical, economical, commercial, operational and political risks), and analysed by Monte-Carlo simulation. Because of the missing data history it was impossible to take concrete and precise analysis methods, for example the calculation of correlation coefficients or the use of Copulas. It is very important to have a big database, because without a big data pool the calculations cannot produce useful outputs. Those methods can be used in seven or ten years. Finally, it has to be taken into account, that data histories are a very useful and valuable basis, however nobody is able to guaranty the course of the future through simulations of the past. It has to be maintained, that the entire analysis as well as predictions should be considered solely as a guide, because different risks of the past and the present can affect project developments in a different way; according to the motto "a risk is always a risk."

KW - Projektrisikomanagement

KW - Risikoportfoliomanagement

KW - quantitative Risikoanalyse

KW - Project Risk Management

KW - Risk Portfolio

KW - Quantitative Risk Analysis

M3 - Master's Thesis

ER -