Executing an Uncertain Schedule:

1. Executing an Uncertain Schedule: Adapting to Reality to Maximize Target Completion Attainment Annaka Kalton Stottler Henke Associates, Inc. www.stottlerhenke.com

2. Orientation • Background • Executing a schedule – the problem • Possible approaches, CCPM overview • Simulation framework • Empirical simulation results • Conclusions • Questions PMI College of Scheduling “PMI” is a registered trade and service mark of the Project Management Institute, Inc.

3. Executing to a Schedule: Challenges • A schedule allows for planning, but is brittle • The more the resource contentions impact a schedule, the more brittle it becomes • It is easier to go over than under for most jobs • Following a schedule minimizes the likelihood of catching up • Ambitious schedules and high-variance jobs aggravate these attributes PMI College of Scheduling “PMI” is a registered trade and service mark of the Project Management Institute, Inc.

4. Possible Solutions • Reschedule frequently to maximize responsiveness • Pros: Highly responsive • Cons: Difficult to plan for • Build contingency time into the schedule • Pros: Increases likelihood of meeting schedule • Cons: Potentially wasteful • Consolidate contingency time (e.g. CCPM) • Pros: Flexible, dynamic, ambitious • Cons: Difficult to plan for, limited in handling of high-density schedules PMI College of Scheduling “PMI” is a registered trade and service mark of the Project Management Institute, Inc.

5. Topic for Exploration • Empirically consider what combinations work best for a specific domain • Posit extrapolations from that domain • Consider possible improvements based on performance PMI College of Scheduling “PMI” is a registered trade and service mark of the Project Management Institute, Inc.

6. Execution Methodologies • Schedule-Based Methodologies • Work to the schedule or a schedule derivative • Strong planning advantage • Psychological • Practical • Analysis-Based Methodologies • Work based on properties derived from the schedule • Robust and flexible in the face of change • Abstraction reduces brittleness • Abstraction allows broader comparisons • Focus on CCPM methodologies PMI College of Scheduling “PMI” is a registered trade and service mark of the Project Management Institute, Inc.

7. Introduction to CCPM • Developed by Eliyahu M. Goldratt • Introduced in 1997 • Derived from the Theory of Constraints • Differs from CPM in focus on resource requirements • Focuses on protecting the project’s critical chain • Gathers contingency time into pooled buffers protecting the critical chain PMI College of Scheduling “PMI” is a registered trade and service mark of the Project Management Institute, Inc.

8. Critical Chain: Nature and Importance • The shortest causal path through a schedule • Takes resource requirements, contention into account • Slippage in the critical chain causes slippage in the delivery date PMI College of Scheduling “PMI” is a registered trade and service mark of the Project Management Institute, Inc.

9. Critical Chain: Example PMI College of Scheduling “PMI” is a registered trade and service mark of the Project Management Institute, Inc.

10. Buffering the Critical Chain PMI College of Scheduling “PMI” is a registered trade and service mark of the Project Management Institute, Inc.

11. Execution Methodologies: Schedule-Based • 1. Work to aggressive schedule • Each job duration set such that it can be completed in the time specified 50% of the time • Very aggressive, very brittle • 2. Work to safe schedule • Each job duration set such that it can be completed in the time specified 85% of the time • Potentially wasteful, still somewhat brittle, people involved in later jobs will not be ready PMI College of Scheduling “PMI” is a registered trade and service mark of the Project Management Institute, Inc.

12. Schedule-Based Prioritization: Detail PMI College of Scheduling “PMI” is a registered trade and service mark of the Project Management Institute, Inc.

13. Execution Methodologies: Analysis-Based • 3. Prioritize based on scheduled slack • 4. Prioritize based on standard CCPM, default buffer placement • 5. Prioritize based on standard CCPM, fenced buffer placement • 6. Prioritize based on projected completion CCPM PMI College of Scheduling “PMI” is a registered trade and service mark of the Project Management Institute, Inc.

14. Slack-based Prioritization: Detail • Slack reflects how much a job could shift without impacting the schedule • Slack can consider temporal constraints, or actual schedule position (i.e. resource contention) • For this test, we used schedule-based slack, rather than abstract slack (see below) PMI College of Scheduling “PMI” is a registered trade and service mark of the Project Management Institute, Inc.

15. CCPM-Based Prioritization: Detail • Gives highest priority to jobs projected to cause buffer incursion • Project buffer incursion trumps feeder buffer incursion • Feeder buffer incursion is compared as a proportion of the buffer available • The whole incurring chain may have the same priority, unless post-processed PMI College of Scheduling “PMI” is a registered trade and service mark of the Project Management Institute, Inc.

16. Projected Completion CCPM: Detail • Traditional CCPM prioritization does not reflect how much work is left vs. how much buffer is left • In some cases this can result in work that has sufficient buffer to finish in time being prioritized ahead of work that does not (see below) • Projected completion CCPM recalculates the buffer needed for the remaining work PMI College of Scheduling “PMI” is a registered trade and service mark of the Project Management Institute, Inc.

17. Simulation Framework • Generate a schedule • Derive a prioritization based on the schedule • Assign current set of randomly generated durations to all active activities • Using that prioritization, simulate the execution for a given time span by scheduling in priority order, taking resource requirements into account. • Record resulting actuals for those activities within the current update time frame (e.g. 48 hours) • Remove the priorities and revert the durations to standard for all activities beyond the current update timeframe • If all of the activities have been completed, report results; otherwise, return to step 1 and repeat. PMI College of Scheduling “PMI” is a registered trade and service mark of the Project Management Institute, Inc.

18. Simulation Detail Beta distribution for generation PMI College of Scheduling “PMI” is a registered trade and service mark of the Project Management Institute, Inc.

19. File Details • File 1 (Airplane assembly preparation): • 106 jobs • 525 resource requirements • 214 constraints • 2.1% resource-driven scheduling decisions • File 2 (Final assembly): • 1,763 jobs • 7,451 resource requirements • 4,839 constraints • 36.4% resource-driven scheduling decisions • Dense: 21% of the jobs within three hours of the critical chain, 42% within 6 hours and 59% are within ten hours PMI College of Scheduling “PMI” is a registered trade and service mark of the Project Management Institute, Inc.

20. Empirical Results: File 1 PMI College of Scheduling “PMI” is a registered trade and service mark of the Project Management Institute, Inc.

21. File 1 Commentary • Statistically insignificant differences between method 3 safe (slack determined in safe mode), method 4 (CCPM), and method 6 (projected completion) • 10% variance in quality – all approaches did reasonably well • Update period had minimal impact • All results reflect the fact that file 1 is a fairly lean, temporally-driven model PMI College of Scheduling “PMI” is a registered trade and service mark of the Project Management Institute, Inc.

22. Empirical Results: File 2 2 Results PMI College of Scheduling “PMI” is a registered trade and service mark of the Project Management Institute, Inc.

23. File 2 Commentary • Method 6 (projected completion) performed the best, although method 3 safe (slack determined in safe mode) determined quite well for such a simple methodology • Much higher variation in quality based on method and update period • All execution strategies produced results longer than the safe schedule PMI College of Scheduling “PMI” is a registered trade and service mark of the Project Management Institute, Inc.

24. Results summary PMI College of Scheduling “PMI” is a registered trade and service mark of the Project Management Institute, Inc.

25. For Further Exploration • Even the best performer did not meet the schedule for file 2 • Dense schedules are a general execution challenge • Deeper buffering or buffering to reflect the schedule’s density might produce better results • Slack-based prioritization did surprisingly well • Explicitly taking job variance into account might improve results further • Could be a useful approach in domains reluctant to try CCPM methodologies • All methodologies improved with higher period • Tradeoffs between dynamism and practical considerations PMI College of Scheduling “PMI” is a registered trade and service mark of the Project Management Institute, Inc.

26. Final Notes • Schedule execution is a major problem • Appropriate execution strategies are likely to vary across domains • Simulation gives a good option for determining the best strategy and its weak points • Estimated project completion appears to operate better than standard CCPM in at least some complex domains • Slack-based prioritization gives a very simple but effective method, in spite of its lack of sophistication PMI College of Scheduling “PMI” is a registered trade and service mark of the Project Management Institute, Inc.

27. The Authors Annaka Kalton Stottler Henke Associates, Inc. 951 Mariner’s Island Blvd, Suite 360 San Mateo, CA 94404 (650) 931-2713 kalton@stottlerhenke.com Devin Cline Stottler Henke Associates, Inc. (650) 931-2700 dcline@stottlerhenke.com PMI College of Scheduling “PMI” is a registered trade and service mark of the Project Management Institute, Inc.