1. “WHY ARE PROJECTS ALWAYS LATE?” (“and what can the Project Manager DO about that?) Craig Henderson, MBA, PMP ARVEST Bank Operations

2. Why are projects always late? Introduction & Overview Planning and Errors Task duration Project duration estimating Project duration Monte Carlo approach Summary “95% Payback, BEST IN TOWN!” (Fitzgerald’s Casino, Reno, NV) “Feeling lucky, Sucker?!”

3. Introduction PM Basics FIO GID KISS Predictable Project Delivery - Quality product - On time - On budget (Figure it out) (Get it done) (Keep it simple, )sweetie

4. Planning “FIO” Detailed, precise SCOPE Create WBS structure Estimate activity durations Sequence activities Network diagram Develop schedule With all this wonderful work, WHAT COULD POSSIBLY GO WRONG??

5. Planning Estimate Errors? Scope Creep? Execution? Risks?

6. Planning Factors influencing estimate quality Planning horizon Immediate events more accurate than distant events Project duration Shorter durations more accurate than long People Resource skill levels Team experience Turnover Productive time (5-6 hours/day?) Project structure & organization Estimate padding (or Understating?!) Organization culture

7. Planning Estimate Errors? Tradeoffs “Nothing” is free (but everything else Costs!) Estimates are not free “Better” estimates are more expensive Must balance accuracy/cost tradeoff Don’ t underestimate the estimate

8. Scope Creep? (What is your Change Management Plan!)

9. Task Data What is your project duration estimate?

10. (network diagram reminder) ESIDEF SLACK LSDurLF “AON” (Arrow on Node) ESIDEF SLACK LSDurLF ESIDEF SLACK LSDurLF ESIDEF SLACK LSDurLF

11. 3C8 1 459 3B5 3 628 5E8 3 8311 3D7 0 347 14I18 1 15419 8F10 1 9211 19K26 0 19726 10H14 1 11415 J19 0 15419 7G15 0 78 0A3 0 033 Network Diagram What is the Critical Path?

12. 3C8 1 459 3B5 3 628 5E8 3 8311 3D7 0 347 14I18 1 15419 8F10 1 9211 19K26 0 19726 10H14 1 11415 J19 0 15419 7G15 0 78 0A3 0 033 Critical Path

13. Task Data What are our odds of finishing on time, P(26)? 50/50?

14. Not So Fast! Task Duration One point? Three point? Distribution? “95% Payback, BEST IN TOWN!” (Fitzgerald’s Casino, Reno, NV) “Feeling lucky, Sucker?!”

15. PERT “Program Evaluation Review Technique” Assumes activity duration is a range statistically following a beta distribution. 3 time estimates for each activity: Expected Optimistic Pessimistic Weighted average represents activity duration distribution. Weighted average and variance for each activity allows computed probability for various project durations.

16. Activity and Project Frequency Distributions

17. 7–17 Activity Time Calculations The weighted average activity time is computed by the following formula:

18. Activity Time Calculations (cont’d) Activity time estimate variability approximated by: Standard deviation for activity: Standard deviation for project: Note standard deviation of activity is squared in this equation; also called variance. This sum includes only activities on the critical path(s) or path being reviewed.

19. Task Data

20. Task Times

21. Probability of Completing the Project @ X Compute the “Z” value (Z = number of standard deviations from the mean) Then find probability of Z

22. Z Values and Probabilities

23. Possible Project Duration Probability project is completed before scheduled time ( T S ) of 67 days Probability project is completed by the 60 th day ( T S )

24. Probability of finish by Est?

25. Possible Project Duration Probability project is completed before scheduled time ( T S ) of 26 units

26. Monte Carlo Simulation Randomize task times Random normal number Adjusted for µ & σ of each task’s distribution Add resulting task times per network diagram Do this “many” times! Calculate average (expected value) and σ

27. Monte Carlo Simulation in Excel Generate random results for each task Analysis Tool Pack, Random Number Generator Following CP, add times Remember “IF” statement to check CP length! Calculate average project time/stnd dev Compare to previously computed result

28. Monte Carlo Results T e = 27.48 Stnd Deviation = 1.83 (Remember, Computed T e = 25.83 Stnd Dev = 2.0) How can this be? ????????

29. Monte Carlo CP = A-D-G-J-K BUT Monte Carlo runs showed CP finish of A-C-F-H-I-K = 61.3% Observation CP shifted from original path about 2/3 of the time! The CP shift prevented us from gaining full advantage when the original randomized CP was very early. CP Results#% A-B-E-H-I-K=151.5% A-C-F-H-I-K=61361.3% A-D-G-J-K=37237.2% What is the term for a network like this?

30. 3C8 1 459 3B5 3 628 5E8 3 8311 3D7 0 347 14I18 1 15419 8F10 1 9211 19K26 0 19726 10H14 1 11415 J19 0 15419 7G15 0 78 0A3 0 033 Critical Path, and others

31. Monte Carlo Result - Beta Distribution? CP Results#% A-B-E-H-I-K=151.5% A-C-F-H-I-K=61361.3% A-D-G-J-K=37237.2%

32. Management’s Project Target Est CP = 26, T e (computed) = 25.83, T e (simulation) = 27.57

33. Confidence and Completion 95% confidence project will complete by time “X” “95% Payback, BEST IN TOWN!” (Fitzgerald’s Casino, Reno, NV) “Feeling lucky, Sucker?!”

34. Possible Project Duration 95% confidence Project Duration

35. Probability of finish by Est? “Feeling lucky, Sucker?!” P(26)?

36. Probability of finish by Est?

37. Project Result Summary

38. Remember Activity definition and precedence Network diagram Task estimates, and ranges/distributions Calculate Expected Durations on CP Consider Monte Carlo simulation Finally: Calculate “Management Duration” based on desired confidence/predictability Add this to your Risk Plan and Risk Budget

39. “Why are projects always late?” Project Managers frequently fail to understand and account for Actual result distributions vary from (point) estimates In their Risk Plans and Budgets “Feeling lucky, Sucker?!”

40. Questions! “Feeling lucky, Sucker?!”