Features

Manual
Scheduling

Rules-Based
Scheduling

Optimized
Scheduling

Able to optimize with respect to business drivers and priorities

Partially and informally

No. The more rules are defined, the more assignments are likely to be excluded. The fewer rules are defined, the lower the quality of the schedule.

Yes. Optimizes schedules by modeling each business objective as a component of the overall cost function. Weights are used to differentiate the objectives according to importance.

Able to un-do previous sub-optimal decisions

Yes. However, the extent to which a human scheduler can explore alternative decisions is limited by the human processing capability

No. Once a slot has received its assignment, this assignment is kept even if it turns out to be sub-optimal

Yes. Optimized scheduling explores millions of alternative schedules by constantly un-doing previous sub-optimal decisions until the optimized solution is found

Able to consider multiple constraints simultaneously

Yes, to limited extend only (ability to consider multiple constraints varies depending on the ability and talent of the human scheduler)

No. For each slot, the business rules are applied successively. The impact of the decision on other slots is not considered.

Yes. For each decision, the impact of the decision on the entire schedule is considered to evaluate the quality of the decision.

Able to cope with conflicting requirements

Yes. However, only sub-set of the conflicting requirements are considered, due to the limitations of the human processing capability

No. The sequential nature of rules-based processing leads to a sub-optimal treatment of conflicting requirements.

Yes.

Able to flex or break rules

Yes

No. Once the rules are defined, they are blindly applied, even if breaking a rule would lead to an overall better solution

Yes. Soft constraints provide for a flexible treatment of business rules (emulates the processing of rules by the human brain)

Able to capture and take account of all business rules

No, human brain can only manage limited number of constraints.

No. In complex scheduling environments, it is nearly impossible to pre-define all exceptions and rules before hand

Yes, ability to emulate the process used by the human brain combined with computing power makes it possible to capture and consider all requirements

Able to assess multiple solutions to pick the best

Yes, but only tens of schedules are considered

No. Rules-based systems construct a single schedule

Yes, millions of schedules are considered per second

Quality of the generated schedule

Acceptable

Poor, in complex environments, schedules are not practically usable. Extensive human intervention is required to produce acceptable schedules.

Optimized, generates best practically achievable solution for a given set of objectives and constraints

Ability to produce feasible solution in complex and dynamic environments such as hospital

Yes, but in order to simplify the problem to a manageable level, often not all requirements are considered.

No, only suited for simple and static environment.

Yes. Optimized scheduling excels in the most complex environment and in such situations by far exceeds the performance of human schedulers.

Real-time scheduling

No.

No.

Yes.

Effort required to find acceptable solution in a complex hospital department setting

Manual schedule generation takes several days for monthly planning in complex environments.

No significant reduction in manual labor – a s rules-based schedules do not meet critical staffing objectives, they must be significantly reworked manually to generate a usable ‘solution’

Few hours, optimized scheduling needs little, if any, human intervention for generating schedules once key parameters have been defined