Aurora-CCPM was developed because the needs of companies involved in the planning and implementation of complex, large-scale manufacturing, turnaround, maintenance, and other operations were not being met by current Critical Chain solutions. Aurora-CCPM has significantly advanced the state-of-the-art in Critical Chain Project Management by expanding the Critical Chain theory to better handle large (multi-thousand) task projects, in addition to other general capabilities. For example, the initial theory of Critical Chain promoted as late as possible scheduling (backward scheduling) for all applications; this is not always practical or desired. However, Aurora-CCPM allows for backward scheduling, forward scheduling, or both (mixed-mode) on a task-by-task basis.
By using sophisticated scheduling software as the underpinning for Critical Chain reasoning, Aurora-CCPM can be applied to projects encompassing thousands of heavily constrained tasks and requiring many different kinds of resources. Giving the Critical Chain method such a solid scheduling basis also allows it to more easily handle complex situations including new tasks being inserted during the actual project execution, as well as other radical changes to the situation.
The underlying Aurora scheduling engine has allowed for up to 50% project duration reduction versus other CCPM products. CCPM has the potential to greatly enhance project efficiency, but much of this potential benefit is lost if the project is not being scheduled well. By combining Aurora with CCPM, schedules can be handled in the most efficient manner possible. Traditional scheduling systems use simple algorithms and criteria when selecting the next activity to schedule and when assigning resources and times to each activity. However, schedules generated by these simple and generic decision rules are often far from optimal. To solve complex, mission-critical scheduling problems and predict possible problem areas, organizations often rely on expert human schedulers who use their judgment, experience, and rules of thumb to determine where things should happen, whether they will happen on time, and whether the requested resources are actually available.