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Schedule Risk Analysis (SRA)

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

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Schedule Risk Analysis (SRA)

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  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. Deterministic Model 10 15 20 45 Program Attention Activity 1 Activity 2 Activity 3 15 10 15 40 Activity 4 Activity 5 Activity 6 10 10 20 40 Activity 7 Activity 8 Activity 9 Probabilistic Model 9-10-12 14-15-17 19-20-2251 Activity 1 Activity 2 Activity 3 14-15-17 9-10-12 14-15-1751 Activity 4 Activity 5 Activity 6 9-10-12 9-10-12 19-20-3458 Program Attention Program Attention Activity 7 Activity 8 Activity 9 High Risk Activity Activity X Activity X Potential Critical Path Critical Path Risk Impact on 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. Input Activity Model Dependency Activity

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

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

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

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

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

  13. Process Input Output Resource Activity Model (continued) Maturity Complexity Dependency Activity Source Expectancy Environment Source Constraint 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. Most Likely Max Min Duration Spread Low Confidence Level High High Risk Activity

  19. Most Likely Min Max Duration Spread Low Confidence Level High Moderate/Medium Risk Activity

  20. Low Risk Activity Most Likely Min Max Duration Spread Low Confidence Level High

  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

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