Abstract
This chapter presents the novel Six Sigma DMAIC generic approach to Risk Management. The method is introduced first. In The Generic Approach and Algorithms section, generic mathematical concepts are elaborated. Also, four generic classes of applications of the proposed method are identified including: 1) Portfolio Management; 2) Quality Management; 3) Project Management; and 4) Income Management. Furthermore, four generic algorithms are elaborated for the respective four classes of application of the method. The generic algorithms include description and process flow of the applications. Finally, the modelling tools used in the book's elaborations are detailed, as well as references for how to use these tools and run Simulation and Stochastic Optimisation step-by-step.
TopIntroduction
Six Sigma is not specially utilised for Risk Management on ongoing projects for process improvements considering the objective function and associated specific risk factors. Inspired by Bernstein, “the risk will always be there, so we must explore many interesting tools that can help us to control risks we cannot avoid taking” (Bernstein and Damodaran 1998), a new practical Six Sigma generic and stochastic approach to Risk Management has been devised. Considering that Six Sigma DMAIC methodology and Risk Management are generic, and very compatible and complementary processes, the proposed approach merges the two processes resulting in a powerful synergetic tool.
This approach tactically applies the DMAIC framework into Risk Management in order to improve the process focussing on the objective achievement and associated risk factors, which is a new concept. The approach applies the conventional stochastic methodologies within the DMAIC framework. The synergy of these complementary methodologies provides for an important systematic improvement to any Risk Management. In addition to conventional techniques, the new concept involves:
- 1.
Stochastic measurement of any risk management process performance by using the Six Sigma process capability metrics considering the objective achievement and major risk factors; and
- 2.
Continuous monitoring and control of process performance by iteratively and recursively applying the DMAIC framework in order to meet the objective and mitigate risks.