Qualitative & Quantitative Analysis

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  1. 1. 2014 Alin Veronika Qualitative & Quantitative Risk Analysis
  2. 2. 2014 Alin Veronika Qualitative & Quantitative Risk Analysis Determine the project overall risk ranking Document non critical risks Determine which risk to further analyze or go directly to risk response planning Determine the probability and impact Determine which risk events warrant a response
  3. 3. 2014 Alin Veronika Qualitative & Quantitative Risk Analysis The process of prioritizing risks for further analysis or action by assessing and combining their probability of occurence and impact Assign Probability High, Medium, Low Assign Impact High, Medium, Low Calculate the Severity Probability x Impact
  4. 4. 2014 Alin Veronika Qualitative & Quantitative Risk Analysis Describe in qualitative terms: High, moderate, low Risk probability is the likelihood that a risk will occur Risk consequence is the effect on project objectives if the risk event occurs
  5. 5. 2014 Alin Veronika Qualitative & Quantitative Risk Analysis 1. Estimate Probability 10% through 90% 2. Estimate Impact High=3 Medium=2 Low=1 3. Calculate the Severity Probability x Impact = Severity 4. Use Severity to identifythe risks worth planning Risk DescriptionProbability (0.1 0.9) Impact (1 3) Severity (P * I)) Resources may be constrained due to team members working on multiple projects with conicting priorities 70%21.4 Signicant schedule delays may occur because the team is unfamiliar with the new application 80%32.4
  6. 6. 2014 Alin Veronika Qualitative & Quantitative Risk Analysis A condition based on the combined probability and impact scales Risk probability scale: General scale : 0.0 (no probability) up to 1.0 (certainly) Ordinal scale : very unlikely to almost certain Risk impact scale: Ordinal scale : very low, low, moderate, high, very high Cardinal : linear or non linear
  7. 7. 2014 Alin Veronika Qualitative & Quantitative Risk Analysis MediumHighHigh MediumMediumHigh LowMediumMedium High High Medium Medium Low Low Probability Impact
  8. 8. 2014 Alin Veronika Qualitative & Quantitative Risk Analysis Probability-Impact (P-I) matrix: the multiplication of t h e s c a l e v a l u e o f probability and impact (P x I). The result is classied into high risk, moderate risk, or low risk
  9. 9. 2014 Alin Veronika Qualitative & Quantitative Risk Analysis or numeric: Risk Score = P x IVery Low0.11 Low0.32 Moderate0.53 High0.74 Very High0.95 Negligible0.11 Low0.32 Moderate0.53 Severe0.74 Catastrophic0.95
  10. 10. 2014 Alin Veronika Qualitative & Quantitative Risk Analysis Code Risk Probability Effects R1 Organisational financial problems force reductions in the project budget. Low Catastrophic R2 Difficulties to recruit staff with the skills required for the project. High Catastrophic R3 Key staff are ill at critical times in the project. Moderate Severe R4 Software components that should be reused contain defects which limit their functionality. High Severe R5 Changes to requirements that require major design rework are proposed. Moderate Severe R6 The organisation is restructured so that different management are responsible for the project. High Severe
  11. 11. 2014 Alin Veronika Qualitative & Quantitative Risk Analysis Code Risk Probability Effects R7 The database used in the system cannot process as many transactions per second as expected. Moderate Severe R8 The time required to develop the software is underestimated. High Severe R9 CASE tools cannot be integrated. High Low R10 Customers fail to understand the impact of requirements changes. Moderate Low R11 Required training for staff is not available. Moderate Low R12 The rate of defect repair is underestimated. Moderate Moderate R13 The size of the software is underestimated. High Moderate R14 The code generated by CASE tools is inefficient. Moderate Negligible
  12. 12. 2014 Alin Veronika Qualitative & Quantitative Risk Analysis NegligibleLowModerateSevereCatastrophic Very High HighR9R13R4, R6, R8R2 ModerateR14R10, R11R12R3, R5, R7 LowR1 Very Low
  13. 13. 2014 Alin Veronika Qualitative & Quantitative Risk Analysis NegligibleLowModerateSevereCatastrophic Very High HighR9R13R4, R6, R8R2 ModerateR14R10, R11R12R3, R5, R7 LowR1 Very Low
  14. 14. 2014 Alin Veronika Qualitative & Quantitative Risk Analysis NegligibleLowModerateSevereCatastrophic Very High HighR9R13R4, R6, R8R2 ModerateR14R10, R11R12R3, R5, R7 LowR1 Very Low
  15. 15. 2014 Alin Veronika Qualitative & Quantitative Risk Analysis
  16. 16. 2014 Alin Veronika Qualitative & Quantitative Risk Analysis Approach: Expected monetary value analysis. It computes the expected monetary outcome (according to different statistical criteria) of a decision/risk Technique: Decision tree analysis. Technique that helps solving the EMV analysis. Approach: Modeling. Provide a model of the project. Technique: Sensitivity analysis. Helps determining which risks have the most impact by examining one variable at a time. (Tornado diagrams) Technique: simulation, Monte Carlo technique.
  17. 17. 2014 Alin Veronika Qualitative & Quantitative Risk Analysis Example 1: You are organizing the international conference. There is 20% probability that paper prices will increase by 15%, thus costing you IDR 2 million in funding. What is the expected monetary value of the cost increase? EMV = 0.2 * 2,000,000 = 400,000 rupiahs.
  18. 18. 2014 Alin Veronika Qualitative & Quantitative Risk Analysis RiskProbability Maximum $ Impact of Risk Contingency $ required A40%(30,000)(12,000 B35%20,0007,000 C50%40,00020,000 D20%70,00014,000 Total Add $29,000 to your budget for contingency reserve needs 29,000 You are a project manager of construction project. You identify that there are four risks affect your project.
  19. 19. 2014 Alin Veronika Qualitative & Quantitative Risk Analysis If Risk C occurs, how much is left in contingency reserves? Contingency Reserves: $ 29,000 Total required for Risk C: $ 40,000 (negative risk) Remaining amount: $ -11,000 If Risk A occurs, how much is left in contingency reserves? Contingency Reserves: $ 29,000 Total required for Risk A: $ 30,000 (positive risk) Remaining amount: $ 59,000
  20. 20. 2014 Alin Veronika Qualitative & Quantitative Risk Analysis 20
  21. 21. 2014 Alin Veronika Qualitative & Quantitative Risk Analysis Choose the Vendor Vendor A will cost $70,000? Vendor B will cost $63,000 Delay will cost you $17,000 No Delay No Cost Delay will cost you $17,000 CNo Delay No Cost 10% Initial CostRisk CostProbabilityTotal Vendor A$70,000$17,000,00010%$71,700 Vendor B$63,000$17,000,00015%$65,550 90% 15% 85%
  22. 22. 2014 Alin Veronika Qualitative & Quantitative Risk Analysis
  23. 23. 2014 Alin Veronika Qualitative & Quantitative Risk Analysis 23 Sensitivity analysis is a technique used to show the effects of changing one or more variables on an outcome. For example, many people use it to determine what the monthly payments for a loan will be given different interest rates or periods of the loan, or for determining break-even points based on different assumptions. Spreadsheet software, such as Excel, is a common tool for performing sensitivity analysis.
  24. 24. 2014 Alin Veronika Qualitative & Quantitative Risk Analysis 24
  25. 25. 2014 Alin Veronika Qualitative & Quantitative Risk Analysis Negative impactPositive impact To r n a d o D i a g r a m s i s generally the result of Sensitivity Analysis A diagram to analyze project sensitivity to cost or other factors Ranks the bars from greatest to least on the projectAnalysis to dene the risk that has the most potential impact on the project
  26. 26. 2014 Alin Veronika Qualitative & Quantitative Risk Analysis
  27. 27. 2014 Alin Veronika Qualitative & Quantitative Risk Analysis Introduce Monte Carlo Analysis as a tool for managing uncertainty Demonstrate how it can be used in the policy setting Discuss its uses and shortcomings, and how they are relevant to policy making processes
  28. 28. 2014 Alin Veronika Qualitative & Quantitative Risk Analysis Copyright2004DavidM. q It is a tool for combining distributions, and thereby propagating more than just summary statistics q It uses random number generation, rather than analytic calculations q It is increasingly popular due to high speed personal computers
  29. 29. 2014 Alin Veronika Qualitative & Quantitative Risk Analysis q Monte Carlo from the gambling town of the same name (no surprise) q First applied in 1947 to model diffusion of neutrons through ssile materialsq Limited use because time consuming q Much more common since late 80s q Too easy now?
  30. 30. 2014 Alin Veronika Qualitative & Quantitative Risk Analysis Takes an equation example: Risk = probability consequence Instead of simple numbers, draws randomly from dened distributions Multiplies the two, stores the answer Repeats this over and over and over Then the set of results is displayed as a new, combined distribution
  31. 31. 2014 Alin Veronika Qualitative & Quantitative Risk Analysis A model to translate the uncertainties into potential impact to project objective. Performed using Monte Carlo techniques Monte Carlo Simulation can be used to determine how much the project or how long it will take
  32. 32. 2014 Alin Veronika Qualitative & Quantitative Risk Analysis Could write this program using a random number generator But, several software packages out there. Using Crystal Ball or @Risk user friendly customizable r.n.g. good up to about 10,000 iterations
  33. 33. 2014 Alin Veronika Qualitative & Quantitative Risk Analysis
  34. 34. 2014 Alin