Simulating services on demand

1. A computer implemented method for analyzing a service level for services offered by a service enterprise, the method comprising a processor executing code to perform the functions of:

aggregating multiple independent streams of service demands, wherein the multiple independent streams of service demands are from multiple clients that are serviced by a single service enterprise;

identifying a constraint in a service stream provided by the single service enterprise;

defining a buffer level before the constraint, wherein the buffer level defines necessary pre-constraint levels of activity to ensure that the constraint is capable of operating at maximum efficiency;

utilizing the buffer level to trigger capacity changes to operations before the constraint, wherein triggered capacity changes cause the necessary pre-constraint levels of activity; and

simulating operation of the service stream through the use of a simulation that incorporates the multiple independent streams of service demands, the constraint, the buffer level before the constraint and the triggered capacity changes.

2. The method of claim 1 , further comprising:

in response to the buffer level straying outside the necessary pre-constraint levels of activity, changing a capacity of the constraint, thereby causing the buffer level and the constraint to be aligned such that the constraint is operating at optimal capacity.

3. The method of claim 1 , wherein the simulation is used to test a case study of the service stream.

4. The method of claim 1 , wherein the simulation is used in a “what-if” analysis of the service stream, wherein the “what-if” analysis changes at least one parameter in the service stream.

5. The method of claim 1 , wherein a same simulation is used in a test of an experimental design of the service stream, in a test of a case study of the service stream, and in a “what-if” analysis of the service stream.

6. The method of claim 1 , wherein the simulation compares elastic versus inelastic capacities of operations performed in the service stream.

7. The method of claim 1 , wherein the simulation compares balanced versus unbalanced capacities in operations performed in the service stream.

8. The method of claim 1 , wherein the simulation creates a deterministic simulation model in which variables, which describe operations performed in the service stream, are non-random.

9. The method of claim 1 , wherein the simulation creates a stochastic simulation model in which variables, which describe operations performed in the service stream, are random.

10. The method of claim 1 , further comprising:

receiving, by an Assistance Allocation Manager (AAM), a Data for Initiating Assistance (DIA) from a resource in a data processing system; and

in response to receiving the DIA, executing a rule, in the AAM, that is specific for the DIA and the resource that sent the DIA, wherein executing the rule in the AAM causes the steps described in claim 1 to be executed for the resource that sent the DIA.

11. A computer-readable storage medium embodying computer program code for analyzing a service level for services offered by a service enterprise, the computer program code comprising computer executable instructions configured for:

aggregating multiple independent streams of service demands, wherein the multiple independent streams of service demands are from multiple clients that are serviced by a single service enterprise;

identifying a constraint in a service stream provided by the single service enterprise;

defining a buffer level before the constraint, wherein the buffer level defines necessary pre-constraint levels of activity to ensure that the constraint is capable of operating at maximum efficiency;

utilizing the buffer level to trigger capacity changes to operations before the constraint, wherein triggered capacity changes cause the necessary pre-constraint levels of activity; and

simulating operation of the service stream through the use of a simulation that incorporates the multiple independent streams of service demands, the constraint, the buffer level before the constraint and the triggered capacity changes.

12. The computer-readable storage medium of claim 11 , wherein a same simulation is used in a test of an experimental design of the service stream, in a test of a case study of the service stream, and in a “what-if” analysis of the service stream.

13. The computer-readable storage medium of claim 11 , wherein the simulation compares elastic versus inelastic capacities of operations performed in the service stream.

14. The computer-readable storage medium of claim 11 , wherein the simulation compares balanced versus unbalanced capacities in operations performed in the service stream.

15. The computer-readable storage medium of claim 11 , wherein the simulation compares elastic versus inelastic capacities for operations performed in the service stream.

16. The computer-readable storage medium of claim 11 , wherein the simulation creates a deterministic simulation model in which variables, which describe operations performed in the service stream, are non-random.

17. The computer-readable storage medium of claim 11 , wherein the computer-usable medium is a component of a remote server, and wherein the computer executable instructions are deployable to a client computer from the remote server.

18. The computer-readable storage medium of claim 11 , wherein the computer executable instructions are capable of being provided by a service provider to a customer on an on-demand basis.

19. A computer-implemented method for simulating services performed on demand, wherein the method comprises a processor executing code for performing the functions of:

creating a Drum-Buffer-Rope for Services (DBRS) model of a service process; and

simulating the service process by populating the DBRS model with user-selected values for a constraint drum, a pre-constraint buffer, a service level rope, and a constraint rope.

20. The method of claim 19 , further comprising:

determining if the service process will be in compliance with a Service Level Agreement (SLA) based on a DBRS simulation of the service process.