Preventive Risk Management Model

When a stable response strategy is agreed upon, the process enters final stage, where an assessment of the risk associated to the response strategy is conducted as explained next in risk management section.

3.2 RISK MANAGEMENT

The risk is calculated as the product of its probability of occurrence and the resulting affect on the project. Each risk has three dimensions- quality-risk, cost-risk and schedule-risk. According to Gericke, risk treatment can be classified into preventive, reactive and proactive risk treatment[5]. Preventive risk treatment aims to prevent any risk by eliminating its causes. For this type of risk treatment, the pre-requisite is prior knowledge of all uncertainties. If the uncertainties are not known in advance, as in

This model cannot be used for identifying the risks involved in an innovation project. It is useful only after an uncertainty is identified and provides a suitable response option.

Future development of the model is therefore to integrate the risk identification strategies with the model. Several existing approaches like SWOT, Brainstorming or Delphi Method can be integrated with the presented ISRM model.

7. RELEVANT

There are already established methods like Failure Modes and Effect Analysis(FMEA) which aims at early identification and assessment of any uncertainty. Two other methods, Fault Tree Analysis(FTA) and Event Tree Analysis(ETA), try to trace back each fault to its root cause and effect of an event in a system respectively. The objective of all these methods is to highlight the quality aspects of a technical system.

On the other hand, change management focuses on minimising the effect of a change on costs and schedule. In order to track change propagation quantitatively, Design Structure Matrix(DSM) can be used. The Change Prediction Method(CPM), uses DSMs for tracing potential change propagation paths among the interconnected components of a technical system (Clarkson et al., 2004). Park, Kim and Choi[13], in their research proposed a risk management framework based on analytic hierarchy process (AHP) analysis and fuzzy method. For choosing the optimal response to various risk factors, they adopted the evolution strategy[10].

None of these approaches offer an integrated view by incorporating quality, cost and schedule aspects of risk. This paper focuses on meeting the above mentioned expectation by providing an integrated