Intelligent resource matching for request artifacts

1. An apparatus comprising:

at least one processing platform comprising a plurality of processing devices each comprising a processor coupled to a memory;

the processing platform being configured to implement at least a portion of one or more cloud-based systems;

wherein the processing platform further comprises:

an artifact details analysis module configured to determine one or more enterprise resource attributes required for resolving a request artifact;

an enterprise resource identification module configured to identify one or more available enterprise resources, across one or more cloud-based systems, associated with the one or more enterprise resource attributes required for resolving the request artifact; and

an artifact-resource matching module configured:

to determine one of the one or more identified available enterprise resources to assign to the request artifact based on one or more usage parameters attributed to the one or more identified available enterprise resources, wherein the one or more usage parameters attributed to the one or more identified available resources comprises a temporal parameter pertaining to how recently the identified available enterprise resources accepted request artifacts, wherein determining the one available enterprise comprises:

filtering the identified available enterprise resources based at least in part on one or more pre-determined criteria pertaining to enterprise resource position within the enterprise;

scoring the filtered enterprise resources based at least in part on one or more skills attributed thereto; and

adjusting the scores for the filtered enterprise resources by applying an adaptive model to information pertaining to the filtered enterprise resources, wherein the adaptive model is trained on enterprise resource acceptance information and enterprise resource rejection information derived from historical request information related to the request artifact; and

to route the request artifact to the determined available enterprise resource;

and wherein the artifact-resource matching module, upon receiving a rejection from the determined available enterprise resource with respect to accepting the routed request artifact, is further configured:

to determine a second of the one or more identified available enterprise resources to assign to the request artifact based on the one or more usage parameters attributed to the identified one or more available resources;

to route the request artifact to the second available enterprise resource; and

to update the adaptive model using one or more items of information learned from the rejection from the determined available enterprise resource with respect to accepting the routed request artifact.

2. The apparatus of claim 1 , wherein the artifact-resource matching module is further configured to learn one or more items of information from an outcome of routing the request artifact to the determined available enterprise resource.

3. The apparatus of claim 2 , wherein the outcome comprises at least one of the determined available enterprise resource accepting the request artifact, the determined available enterprise resource rejecting the request artifact, and the determined available enterprise resource resolving the request artifact in accordance with one or more parameters.

4. The apparatus of claim 2 , wherein the artifact-resource matching module is further configured to determine one of the one or more identified available enterprise resources to assign to the request artifact based on the one or more usage parameters attributed to the one or more identified available enterprise resources and the one or more learned items of information.

5. The apparatus of claim 1 , wherein the request artifact comprises a service request.

6. The apparatus of claim 1 , wherein the one or more enterprise resources comprises one or more technical service engineers.

7. The apparatus of claim 6 , wherein the one or more enterprise resource attributes comprises one or more technical service engineer skills required for resolving the request artifact.

8. The apparatus of claim 1 , wherein the artifact-resource matching module is further configured to route the request artifact to an exception queue upon receiving rejections from all of the one or more identified available enterprise resources.

9. The apparatus of claim 1 , wherein the processing platform further comprises a team building module configured to determine one or more additional enterprise resource attributes related to resolving the request artifact distinct from enterprise resource attributes associated with the determined available enterprise resource.

10. The apparatus of claim 9 , wherein the team building module is further configured to identify one or more additional available enterprise resources associated with the one or more additional enterprise resource attributes related to resolving the request artifact.

11. The apparatus of claim 9 , wherein the team building module is further configured to determine one of the one or more identified additional available enterprise resources to request to join a request artifact resolution team with the determined available enterprise resource, based on the one or more usage parameters attributed to the one or more identified additional available resources.

12. The apparatus of claim 9 , wherein the one or more additional enterprise resource attributes comprises one or more technical service engineer skills associated with one or more artifacts related to the request artifact.

13. A method comprising:

determining one or more enterprise resource attributes required for resolving a request artifact;

identifying one or more available enterprise resources associated with the one or more enterprise resource attributes, across one or more cloud-based systems, required for resolving the request artifact;

determining one of the one or more identified available enterprise resources to assign to the request artifact based on one or more usage parameters attributed to the one or more identified available enterprise resources, wherein the one or more usage parameters attributed to the one or more identified available resources comprises a temporal parameter pertaining to how recently the identified available enterprise resources accepted request artifacts, wherein determining the one available enterprise comprises:

filtering the identified available enterprise resources based at least in part on one or more pre-determined criteria pertaining to enterprise resource position within the enterprise;

scoring the filtered enterprise resources based at least in part on one or more skills attributed thereto; and

adjusting the scores for the filtered enterprise resources by applying an adaptive model to information pertaining to the filtered enterprise resources, wherein the adaptive model is trained on enterprise resource acceptance information and enterprise resource rejection information derived from historical request information related to the request artifact;

routing the request artifact to the determined available enterprise resource; and

upon receiving a rejection from the determined available enterprise resource with respect to accepting the routed request artifact:

determining a second of the one or more identified available enterprise resources to assign to the request artifact based on the one or more usage parameters attributed to the identified one or more available resources;

routing the request artifact to the second available enterprise resource; and

updating the adaptive model using one or more items of information learned from the rejection from the determined available enterprise resource with respect to accepting the routed request artifact;

wherein the method is implemented in at least one processing platform configured to include a plurality of processing devices each comprising a processor coupled to a memory; and

wherein the processing platform is configured to implement at least a portion of the one or more cloud-based systems.

14. The method of claim 13 , further comprising:

determining one or more additional enterprise resource attributes related to resolving the request artifact distinct from enterprise resource attributes associated with the determined available enterprise resource; and

identifying one or more additional available enterprise resources associated with the one or more additional enterprise resource attributes related to resolving the request artifact.

15. A computer program product comprising a non-transitory processor-readable storage medium having stored therein program code of one or more software programs, wherein the program code when executed by a processing platform comprising a plurality of processing devices causes the processing platform:

to determine one or more enterprise resource attributes required for resolving a request artifact;

to identify one or more available enterprise resources associated with the one or more enterprise resource attributes, across one or more cloud-based systems, required for resolving the request artifact;

to determine one of the one or more identified available enterprise resources to assign to the request artifact based on one or more usage parameters attributed to the one or more identified available enterprise resources, wherein the one or more usage parameters attributed to the one or more identified available resources comprises a temporal parameter pertaining to how recently the identified available enterprise resources accepted request artifacts, wherein determining the one available enterprise comprises:

filtering the identified available enterprise resources based at least in part on one or more pre-determined criteria pertaining to enterprise resource position within the enterprise;

scoring the filtered enterprise resources based at least in part on one or more skills attributed thereto; and

adjusting the scores for the filtered enterprise resources by applying an adaptive model to information pertaining to the filtered enterprise resources, wherein the adaptive model is trained on enterprise resource acceptance information and enterprise resource rejection information derived from historical request information related to the request artifact;

to route the request artifact to the determined available enterprise resource; and

upon receiving a rejection from the determined available enterprise resource with respect to accepting the routed request artifact:

to determine a second of the one or more identified available enterprise resources to assign to the request artifact based on the one or more usage parameters attributed to the identified one or more available resources;

to route the request artifact to the second available enterprise resource; and

to update the adaptive model using one or more items of information learned from the rejection from the determined available enterprise resource with respect to accepting the routed request artifact;

wherein the processing platform is configured to implement at least a portion of the one or more cloud-based systems.

16. The computer program product of claim 15 , wherein the program code further causes the processing platform to determine one or more additional enterprise resource attributes related to resolving the request artifact distinct from enterprise resource attributes associated with the determined available enterprise resource.

17. The computer program product of claim 15 , wherein the program code further causes the processing platform to identify one or more additional available enterprise resources associated with the one or more additional enterprise resource attributes related to resolving the request artifact.