Schedule Risk Analysis A large DoD Development Program

Transcription

1 Schedule Risk Analysis A large DoD Development Program

2 So, who s the dude? Jim Aksel PMP, PMI SP Microsoft MVP 35 Years experience aerospace/defense Co Author PMI Practice Standard for Scheduling Program and Scheduling Excellence Guide (PASEG) DID MGT Full EVMS capabilities Scheduling Yoda jim@projectpmo.com ProjectPMO PO Box28113 Anaheim, CA (714)

3 What is a Schedule Risk Analysis Monte Carlo Simulation of a compliant Schedule Model Assists in establishing timeframe for event completion If Schedule Model is cost/resource loaded, can predict costs too

4 The Goal Land in the red box

5 Today s Example USN Missile Program Prime with 1 subcontractor Master/Subproject file 5277 discrete nonloe tasks Requires correlation Requires probabilistic branching

6 Preliminaries Schedule Model preparation Excel/Computer preparation

7 Schedule Model Preparation Proper Schedule Model status Consider an analysis tool such as DCMA14 Point Assessment Things that were supposed to happen actual did! No time warps Everyone has a proper successor xf

8 Schedule Model Preparation Custom Fields Clear all formulas, lookup values, etc. Consider deleting data Retain only Min, Most likely, Max Level of Effort Hammock Task Pure Level of Effort Constraints Remove MFO, MSO, SNET, SNLT, FNET, FNLT Retain only those from external Monte Carlo Engine does not need custom field calculations Level of Effort should never drive a path remove it. Think very carefully about constraint dates Schedule logic may change: FS, FF, SS, SF.

9 Excel and Computer Preparation Excel Latest Service Packs Enable Multi Threaded Calculations RAM! Consider Office x64 bit Windows manages Virtual Memory Disable power management including within the BIOS It will take some time, use a different machine

10 Triple Point Estimates Remaining Duration Minimum, Most Likely, Maximum Consider these Tasks with no upside (Min close to Most Likely compared to Max) Tasks with no downside (Max close to Most likely compared to Min) Inherent high risk (Max Min exceeds 25% of Most Likely) Or better... Is data available to support more realistic distributions? Requires only a mean and standard deviation or other factor

11 More on Triple Point Estimates Banding +x/ y need not be symmetrical Simple, not very rigorous More rigor required on Critical Path tasks (1 st,2 nd,3 rd ) Historical Performance Decomposition Analogy Ratio/Parametric Units Expert opinion Effort

12 Probability Distribution Use Triangular unless you have some valid reason to use something else. Why? Has the largest Standard Deviation of the common distributions Drives uncertainty Spreads the results Easily understood and adaptable Only requires three points

13 Match the Distribution to the Data Is this triple point truly Normally Distributed?

14 @Risk Tool Hints Check Simulation Engine settings for faster results (Standard, Accelerated) Consider using Project/Excel 2007 MS Project Table ready as you want it (Remaining Duration) Save frequently

15 @Risk Tool Hints Unprotect the Tasks Sheet to apply filtering

16 Correlations Tasks split between $ and hours (EVMS Requirement) Long preparation time Long test time

17 Probabilistic Branching A choice of task paths exists after completion of a task One to Many relationship (at least 2) Each successor path has a mutually exclusive probability Must sum to 1.0 Chains can be anywhere in the Schedule Model Need not end in same place Should trace forward to final task Use Inactive Tasks Could be Risk Register Items?

18 Probabilistic Branching Prerequisite branches Choice 1a 90% Choice 2a 10%

19 Probabilistic Branching Certain material obsolescence issues (90/10) Setup logic drives both paths At least 1 day duration

20 The Main Event!

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22 Effects of Conditional Branching

23 Tornado Chart

24 Tornado Correlations

25 Did we do enough? 1000 Iterations run Desired granularity ±1 day Error Term µ

26 Did we do enough? From Statistics Z=1.96 (95 th Percentile) s=σ=31.28 from prior slide Set error = 1 day Solve for n n=3759 At n=1000, Error is about 1.93 days

27 Output Convergence At some point, output changes small enough to be ignored You can effectively stop at this point See Simulation Settings

28 What We Learned Systems Engineering has more impact to Critical Path than we thought Balloon Squeezing is difficult Mitigations on the Tornado Tasks is only one way to do it. Forces creativity to increase probabilities of reaching set dates The Golden Rule

29 For Consideration Resource Leveling not considered Leveling delays? Overloaded resources? Money constraints Mitigate through corporate funding or other cost shares? Does it produce progress gaps (standing army)? Reduce conditional branching if possible Eliminate Correlation through improved logic?

30 Jim Aksel ProjectPMO PO Box Anaheim, CA (Office) or (Cell)