1. Schedule Risk Analysis (SRA) Tariq Ashraf Systems Engineering Feb 24, 2005

2. Why SRA? Prior to program execution, management needs to know what are the potential schedule road blocks ahead of him/her –Establish warning indicators up front –Build mitigation into the IMS during planning Deterministic model fallacy –Critical path based upon linked activities with the least amount of float –Assumes all linked activities are low risk – not true in real life

3. Program Attention Program Attention Program Attention Risk Impact on Critical Path Activity X Potential Critical Path Probabilistic Model Activity 1Activity 2Activity 3 Activity 4Activity 5Activity 6 Activity 7Activity 8Activity 9 9-10-12 14-15-17 19-20-22 51 14-15-17 9-10-12 14-15-17 51 9-10-12 9-10-12 19-20-34 58 High Risk Activity Deterministic Model Activity 1Activity 2Activity 3 Activity 4Activity 5Activity 6 Activity 7Activity 8Activity 9 10 15 20 45 15 10 15 40 10 10 20 40 Activity X Critical Path

4. Brief Objective Describe a structured methodology for conducting Schedule Risk Analysis (SRA)

5. Schedule Risk Assessment Methodology Two step process: –Step 1 : Assess and determine the risk level of each IMS activity to identify activities that are high or moderate/medium risk – the most important element of SRA –Step 2 : Determine potential impact of the High/Moderate risk activities on program events using a simulation tool

6. Step 1. How to Determine the Risk Level of an Activity? Assess each activity against the elements that impact the activity –The activity model provides the answer

7. Activity Model Activity Input Dependency

8. Input Dependency – One Predecessor P s = 80% Activity 1 (P s = 80%) Activity 2 P s = Probability of Success

9. Input Dependency – Multiple Concurrent Predecessor The greater the number of concurrent predecessor activities, the lower the Cumulative Probability of Success Activity 1 (P s = 80%) Activity 2 (P s = 80%) Activity 3 (P s = 80%) Activity 4 (P s = 80%) Activity 5 Cumulative P s 80% x 80% x 80% x 80% = 41% P s = Probability of Success P s = 41%

10. Activity Model (continued) Activity Input Dependency Source Timeliness of input is dependent upon control exercised over the input source

11. Activity Model (continued) Activity Resource Input Dependency Source Constraint

12. Resource Constraint There is a loss in resource efficiency when a resource is applied to multiple concurrent activities Activity 1 Resource A Activity 2 Elapsed Time Setup Work on Task Suspend Non Productive Work Productive Work Theory of Constraint

13. Activity Model (continued) Environment Activity Resource Process InputOutput Dependency Source Constraint Maturity Complexity Expectancy Source State

14. So Now What? Develop a likelihood rating matrix for each activity element –Example: Input Dependency –1 – No Predecessor –5 – N Concurrent Predecessors Resource State –1 – Existing –5 – New development using state-of-the art

15. Likelihood Matrix EXAMPLE

16. So Now What? Now that the activity elements have been identified develop a likelihood rating matrix for each activity element –Example: Input Dependency –1 – No Predecessor –5 – N Concurrent Predecessors Resource State –1 – Existing –5 – New development using state-of-the art For each activity –Using the likelihood rating matrix, determine the level for each activity element –Determine the schedule consequence using the criteria provided in the risk plan –Determine the activity risk level by mapping highest likelihood level to schedule consequence Establish Max-Min durations criteria for high, moderate, low risk activity –Durations –+ of % of ML

17. The risk level determines the estimate confidence and duration spread (Min-ML-Max) of an activity

18. High Risk Activity Min Duration Spread Max Most Likely Confidence LevelLowHigh

19. Moderate/Medium Risk Activity Min Duration Spread Max Most Likely Confidence LevelLowHigh

20. Low Risk Activity LowConfidence LevelHigh Most Likely Duration Spread Min Max

21. Step 2. Determining the Impact of High/Moderate Risk Activities on Program Event(s) Review the IMS logic for the following: –All activities are linked –The logic makes sense Maximize FS relationships. Simulation models do not like other relationships (SS, SF, FF). Also minimize lags in the activity logic i.e. FS+20, FS-20, etc. For each activity, input estimates (Minimum, Most Likely, Maximum ) based upon the risk level of the activity and run simulations Out put generated by simulation tool –Probability vs. Time curve for each event selected for analysis –Criticality Index for each task (during the simulation, the number of times an activity fell on the critical path) Results from the first simulation may not meet expectation Adjust IMS and reiterate

22. Conclusion Risk is inherent in a complex system with multiple stakeholders Prior to execution, management must know what risks are embedded in the IMS Applying a structured methodology ensures schedule risk is identified consistently by all stakeholders Analysis is time consuming and requires input from all stakeholders but the value cannot be underestimated