Al-Bazi, Ammar

Kassem, M.

We present a simulation-based risk model to analyse the impact of multiple risks on the cost performance of portfolios. The model considers the combined impact of risks affecting the work packages of portfolio\u27s projects and the probabilistic occurrence of each risk. We test the model in a portfolio composed of four construction projects and we show that the model is able to: predict the effect of identified risks on the portfolio cost performance and aid the decision making process of responding to risks. The limitation of the proposed model is that it calculates the impact of risks at a specific date when each risk has a defined probabilistic distribution. In future work we will consider the dynamic nature of risks to enable the model to cope with the changing attributes of risks

Kassem M

Al-Bazi A

Newcastle University E-Prints

Portfolio risk management: A simulation-based model for portfolio cost management

We present a simulation-based risk model to analyse the impact of multiple risks on the cost performance of portfolios. The model considers the combined impact of risks affecting the work packages of portfolio’s projects and the probabilistic occurrence of each risk. We test the model in a portfolio composed of four construction projects and we show that the model is able to: predict the effect of identified risks on the portfolio cost performance and aid the decision making process of responding to risks. The limitation of the proposed model is that it calculates the impact of risks at a specific date when each risk has a defined probabilistic distribution. In future work we will consider the dynamic nature of risks to enable the model to cope with the changing attributes of risks

Coventry University Pure Portal

  Portfolio Risk Management: A Simulation-Based Model for Portfolio Cost Management  Kassem, M & Al-Bazi, A  Published PDF deposited in Coventry University’s Repository  Original citation:  Kassem, M & Al-Bazi, A 2013, 'Portfolio Risk Management: A Simulation-Based Model for Portfolio Cost Management' Paper presented at OR55 Annual Conference, Exeter, United Kingdom, 3/09/13 - 5/09/13, pp. 110-114. http://www.theorsociety.com/DocumentRepository/Browse.aspx?DocID=347  Publisher: The Operational Research Society  Copyright © and Moral Rights are retained by the author(s) and/ or other copyright owners. A copy can be downloaded for personal non-commercial research or study, without prior permission or charge. This item cannot be reproduced or quoted extensively from without first obtaining permission in writing from the copyright holder(s). The content must not be changed in any way or sold commercially in any format or medium without the formal permission of the copyright holders. OR55 Annual Conference - Keynote Papers and Extended Abstracts, pp.110-114 University of Exeter, 3-5 September 2013 OR in Construction 114   Portfolio Risk Management: A Simulation-Based Model for Portfolio Cost Management Mohamad Kassem a and Ammar Al-Bazi b  a Teesside University, Middlesbrough, UK b Coventry University, Coventry, UK  m.kassem@tees.ac.uk, aa8535@coventry.ac.uk    Abstract We present a simulation-based risk model to analyse the impact of multiple risks on the cost performance of portfolios. The model considers the combined impact of risks affecting the work packages of portfolio‟s projects and the probabilistic occurrence of each risk. We test the model in a portfolio composed of four construction projects and we show that the model is able to: predict the effect of identified risks on the portfolio cost performance and aid the decision making process of responding to risks. The limitation of the proposed model is that it calculates the impact of risks at a specific date when each risk has a defined probabilistic distribution. In future work we will consider the dynamic nature of risks to enable the model to cope with the changing attributes of risks.   Keywords: Monte Carlo simulation; risk; risk management; portfolio   Introduction  1.Cost and time over-runs are the two major negative impacts of risks on projects in the construction, oil and gas and IT industries. Indeed risks are inherent in any project and portfolio in the construction and engineering industry (Kerzner, 2009; Xie et al, 2012). A risk is defined by the ISO 31000 as the „effect of uncertainty on objectives‟. Most organisations in the construction and engineering industry operate in portfolio environment where numerous projects are simultaneously running. All portfolio definitions (Pinto, 2010; Buttrick, 2009; Aitken et al. 2000) suggest that it is a group of projects and/or programmes and/or business activities that support organisations in meeting their strategic goals and objectives. Time and cost overruns are currently among the major negative impacts of risks on portfolios (Xie et al., 2012; Uryasev et al., 2010). According to PMI (2008) Portfolio Risk Management (PRM) includes the processes concerned with conducting risk identification, analysis, response development, as well as monitoring and control of the risks. Central to the entire discipline of Project Portfolio Management (PPM) is the concept of Portfolio Risk Management (PRM) (Aritua et al., 2009; Kerzner, 2009). Previous studies on PRM have exclusively focussed on either the selection and prioritisation of projects (Petit, 2011) or the risk identification stage (Olsson, 2008). There is still lack of quantitative PRM methodologies and tools.    M. Kassem and A. Al-Bazi / OR55 Keynote Papers and Extended Abstracts, pp.110-114 (2013) 115  In this paper we present a simulation-based model that enables the estimation of the impacts of multiple risks on the cost performance of portfolios. We also empirically test the model using a portfolio of four construction projects. The following two sections respectively describes the proposed model and illustrates the results from the case study.     Simulation Based Model 2.One of the major challenges for projects and portfolios is to meet their allocated budget and guarantee a net profit margin for the organisation involved. A portfolio‟s mark-up is defined as the different between Contract Portfolio Price (CP) and the Portfolio Cost (PC) (1).                                                       (1) For the organisation to make a profit, the total impact of all risks affecting the cost of their portfolio should be lower the mark-up of portfolio. The model considers the impacts of all risks on the cost of each project within the portfolio and compares the result with the mark up available (2).        *(     )  ,(        )  (        )    (        )-+  (2)  All the variables in (2) are considered at work package level and explained below:   Execution Cost (EPC): is the execution/expected work package cost that considers the impact of all portfolio‟s risks.  Risk Factor (RFi): It is the impact of each risk factor on the different work packages composing the portfolio‟s projects. For the proposed model, these will be expressed in terms of financial or cost impacts.  Risk Impact (Rani): is a random number extracted from a probabilistic distribution that best model the probability of occurrence of each risk.   Case Study 3.A portfolio case study of four construction projects is used to test the proposed PRM model. The total value of the portfolio is just less than $ 34.9 million. The risks affecting the different work packages and their impact on the 10% mark-up were identified using interviews with project managers. The common risks identified are: design changes; incomplete design; not meeting the client‟s specifications; weather condition; soil condition; unstable labour productivity; material and equipment delays; space clashes; equipment and device failure; installation mistakes and distributed teams. The financial impacts of risks were identified with the support of project managers. The probability of occurrence for most risks was modelled using PERT (Programme Evaluation and Review Technique) distribution as no historical data M. Kassem and A. Al-Bazi / OR55 Keynote Papers and Extended Abstracts, pp.110-114 (2013) 116  for the identified risks were available (Garlick, 2007. p.182).  Figure 1 and Figure 2 show that there is 90% of probability for making a profit of $972k (Min) and $1.741k (Max).    Figure 1 Portfolio cost‟s probabilistic distribution    Figure 2 Portfolio cost‟s cumulative probability There are risks inherent in portfolio environments and could not happen if the projects are conducted in isolation (Olsson, 2008). When these risks were included in the model, the results (Figures 3 and 4) showed that there is 90% probability of making a loss of $567k. These scenarios demonstrated that the model is capable of modelling the combined effect of risks on the financial performance of portfolio and providing meaningful data for the following risk analysis stage.    M. Kassem and A. Al-Bazi / OR55 Keynote Papers and Extended Abstracts, pp.110-114 (2013) 117    Figure 3 Portfolio cost‟s probabilistic distribution with inter-project risks    Figure 4 Portfolio cost‟s probabilistic distribution with inter-project risks   Conclusions 4.This paper proposed a simulation-based PRM model. The testing of the model in the case study demonstrated that the model can support the risk analysis stage in PRM. The main limitation of the model is in its incapability of dealing with the dynamicity of risks and needs to be applied several times during the lifecycle of a portfolio and M. Kassem and A. Al-Bazi / OR55 Keynote Papers and Extended Abstracts, pp.110-114 (2013) 118  updated every time the status of identified risks has changed in the risk register (closed, introduced, upgraded or downgraded).  References  Aitken W and O'Conor D (2000). Delivering successful projects. Broadstairs, Kent, GBR: Scitech Educational.  Aritua B, Smith NJ and Bower D (2011). What risks are common to or amplified in programmes: Evidence from UK public sector infrastructure schemes, International Journal of Project Management, 29(3): 303-312.  Buttrick R (2009). The project workout: The ultimate handbook of project and programme management. 4th ed. Harlow: Financial Times Prentice Hall. Garlick A (2007). Estimating risk: A management approach. Burlington, VT: Gower Publishing Limited.  Kerzner H (2009). Project management: A systems approach to planning, scheduling, and controlling (10th ed.) Hoboken, N.J.: Wiley.  Olsson R (2008). Risk management in a multi-project environment: An approach to manage portfolio risks, International Journal of Quality and Reliability Management, 25(1): 60-71.  Petit Y (2012). Project portfolios in dynamic environments: Organizing for uncertainty, International Journal of Project Management, 30(5): 539-553.  Pinto J K (2010). Project management: Achieving competitive advantage, International ed. Boston, Mass; London: Pearson.   Project Management Institute – PMI (2008). A guide to the project management body of knowledge: (PMBOK guide). 4th edn. Newton Square, Pa.  Uryasev S (2010). Risk-return optimization with different risk-aggregation strategies, Journal of Risk Finance, 11(2): 129-146.  Xie H, AbouRizk S and Zou J (2012). Quantitative method for updating cost contingency throughout project execution, Journal of Construction Engineering and Management -ASCE, 138(6): 759-766.  

Portfolio Risk Management:A Simulation-Based Model for Portfolio Cost Management

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Portfolio Risk Management:A Simulation-Based Model for Portfolio Cost Management

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