Articulation Workload Metrics

• US 20090292578A1
• Filed: 05/20/2008
• Published: 11/26/2009
• Est. Priority Date: 05/20/2008
• Status: Abandoned Application

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Erickson, Thomas David, Paraszczak, Jurij Rostyslav, Danis, Catalina Maria, Gospodinoff, Pia T., Kellogg, Wendy Anne, Rosenbaum, Rhonda, Dietrich, Brenda Lynn, Helander, Mary Elizabeth
• Application Number:
  US12/123,743
• Publication Number:
  US 20090292578A1
• Time in Patent Office: Days
• US Class Current: 705/7.13
• CPC Class Codes: G06Q 10/06 Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
• CPC Class Codes: G06Q 10/06311 Scheduling, planning or task assignment for a person or group
• CPC Class Codes: G06Q 10/10 Office automation; Time management

Abstract

A method for determining an allocation of a workload includes identifying an employee in an organization having the workload, associating the employee with an articulation workload metric, and determining the allocation of the workload to the employee according to the articulation workload metric.

Claims

1. A method for determining an allocation of a workload comprising:

identifying an employee in an organization having the workload;

associating the employee with a partial articulation workload metric; and

determining the allocation of the workload to the employee according to the partial articulation workload metric.

2. The method according to claim 1 further comprising determining the partial articulation workload metric, comprising:

collecting work artifacts for the employee;

recovering input data from the work artifacts;

observing collaborative artifacts from the input data; and

creating the partial articulation workload metric for the employee from the input data and the collaborative artifacts.

3. A method for determining an allocation of a workload comprising:

identifying an employee in the organization having the workload;

associating the employee with an articulation workload metric; and

determining the allocation of the workload to the employee according to the articulation workload metric.

4. The method according to claim 3, further comprising determining the articulation workload metric, comprising:

collecting work artifacts for the employee;

recovering input data from the work artifacts;

observing collaborative artifacts from the input data; and

creating the articulation workload metric for the employee from the input data and the collaborative artifacts.

5. The method according to claim 3, further comprising determining the articulation workload metric, comprising:

collecting work artifacts for the employee;

recovering input data from the work artifacts;

observing collaborative artifacts from the input data;

creating partial articulation workload metrics for the employee and a plurality of collaborators; and

creating the articulation workload metric for the employee from the input data, the partial articulation workload metrics and the collaborative artifacts.

6. The method of claim 3, further comprising:

creating a direct collaboration network including the employee and a plurality of collaborators observed based on the collaborative artifacts; and

reporting the direct collaboration network.

7. The method of claim 6, further comprising handling a request on the employee according to the direct collaboration network.

8. The method of claim 5, further comprising:

creating an overlay network from the partial articulation workload metric of the employee and at least a second partial articulation workload metric of a collaborator.

9. The method of claim 5, further comprising weighting nodes of the overlay network based on the partial articulation workload metrics;

deriving a node articulation workload metric associated with each node of the overlay network; and

converting the node articulation workload metric into an allocation requirement.

10. The method of claim 3, further comprising:

determining a partial articulation workload metric for the employee and a plurality of collaborators;

comparing the partial articulation workload metric of the plurality of collaborators to the partial articulation workload metric of the employee to determine a level of congruence for each of the plurality of collaborators; and

creating the resource allocation requirement of the employee according to the level of congruence for each of the plurality of collaborators.

11. A method for determining an allocation requirement for assigning articulation work comprising:

collecting work artifacts for each of a plurality of employees;

recovering input data from the work artifacts;

observing collaborative artifacts from the input data;

creating a partial articulation workload metric for each employee from the input data and the collaborative artifacts;

creating a direct collaboration network for each employee including a respective employee and a list of unique collaborators relative to the respective employee observed based on the collaborative artifacts;

creating an overlay network from the partial articulation workload metrics of the employees;

weighting nodes of the overlay network based on the partial articulation workload metrics;

deriving a node articulation workload metric associated with each node of the overlay network; and

converting the node articulation workload metric into the allocation requirement for assigning articulation work.

12. The method of claim 11, further comprising:

determining a measure of efficiency for an employee of the plurality of employees; and

assigning the articulation work to the employee according to the measure of efficiency.

13. The method of claim 11, further comprising providing a predetermined list of the plurality of employees.

14. The method of claim 11, further comprising building a target population from an employee of the plurality of employees, wherein the target population includes a subset of the plurality of employees, except the employee, within a predetermined distance in the overlay network from the employee.

15. The method of claim 11, further comprising ranking the employees according to a partial articulation workload metric, an articulation workload metric, or the allocation requirement.

16. The method of claim 11, further comprising assigning a score to the employees according to a partial articulation workload metric, an articulation workload metric, or the allocation requirement.

17. The method of claim 11, further comprising:

building a decision model for the assignment of articulation work, wherein the allocation requirement is a parameter of the decision model; and

outputting the assignment of articulation work from the decision model based on values of the parameters.

18. The method of claim 16, further comprising tuning at least one of a cost function and an efficiency function of the decision model.

19. A method for determining a node articulation workload metric comprising:

collecting work artifacts for each of a plurality of employees;

recovering input data from the work artifacts;

observing collaborative artifacts from the input data;

creating a partial articulation workload metric for each employee from the input data and the collaborative artifacts;

creating a direct collaboration network for each principal including a respective principal and a list of unique collaborators relative to the respective employee observed based on the collaborative artifacts;

creating an overlay network from the partial articulation workload metrics of the employees;

weighting nodes of the overlay network based on the partial articulation workload metrics; and

deriving the node articulation workload metric associated with each node of the overlay network.

20. The method of claim 19, further comprising converting the node articulation workload metric into the allocation requirement for assigning articulation work.