FEEDBACK BASED MODEL VALIDATION AND SERVICE DELIVERY OPTIMIZATION USING MULTIPLE MODELS

• US 20130173323A1
• Filed: 01/03/2012
• Published: 07/04/2013
• Est. Priority Date: 01/03/2012
• Status: Abandoned Application

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Diao, Yixin, Heching, Aliza R., Northcutt, David M., Stark, George E.
• Application Number:
  US13/342,229
• Publication Number:
  US 20130173323A1
• Time in Patent Office: Days
• US Class Current: 705/7.13
• CPC Class Codes: G06Q 10/04 Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem" market predictions or forecasting for commercial activities G06Q30/0202
• CPC Class Codes: G06Q 10/06 Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
• CPC Class Codes: G06Q 10/063112 Skill-based matching of a person or a group to a task
• CPC Class Codes: G06Q 10/06315 Needs-based resource requirements planning or analysis
• CPC Class Codes: G06Q 10/08 Logistics, e.g. warehousing, loading or distribution; Inventory or stock management

Abstract

An approach for validating a model is presented. Data from a system being modeled is collected. First and second models of the system are constructed from the collected data. Based on the first model, a first determination of an aspect of the system is determined. Based on the second model, a second determination of the aspect of the system is determined. A variation between the first and second determinations is determined. An input for resolving the variation is received and in response, a model of the system that reduces the variation is derived.

Claims

1-3. -3. (canceled)

4. A method of modeling a service delivery system, the method comprising the steps of:

a computer system collecting data from the service delivery system;

the computer system constructing first, second and third models of the service delivery system from the collected data, the first model being a discrete event simulation model based work types, arrival rate, and service times for the work types, the second model being a queuing model based on a queuing formula that uses Little'"'"'s theorem, arrival time, service time, and a mean arrival rate divided by a mean service rate, and the third model being a system heuristics model based on pool performance and agent behaviors;

based on the discrete event simulation model, the computer system determining a first measure of a utilization of staffing by the service delivery system;

based on the queuing model, the computer system determining a second measure of the utilization of staffing by the service delivery system;

based on the system heuristics model, the computer system determining a third measure of the utilization of staffing by the service delivery system;

the computer system determining first variations among the first, second and third measures of the utilization of staffing by the service delivery system;

the computer system determining a first utilization error that indicates the first variations among the first, second and third measures of the utilization of staffing by the service delivery system;

based on the first utilization error, the computer system determining a problem that causes the first variations among the first, second and third measures of the utilization of staffing, and in response, determining adjustments to the discrete event simulation, queuing, and system heuristics models;

based on the adjustments, the computer system adjusting the discrete event simulation, queuing, and system heuristics models to correct the problem that causes the variations;

based on the adjusted discrete event simulation model, the computer system determining a fourth measure of the utilization of staffing by the service delivery system;

based on the adjusted queuing model, the computer system determining a fifth measure of the utilization of staffing by the service delivery system;

based on the adjusted system heuristics model, the computer system determining a sixth measure of the utilization of staffing by the service delivery system;

the computer system determining second variations among the fourth, fifth and sixth measures of the utilization of staffing by the service delivery system;

the computer system determining a second utilization error that indicates the second variations among the fourth, fifth and sixth measures of the utilization of staffing by the service delivery system;

based on the second utilization error, the computer system determining a consistency among the adjusted discrete event simulation, queuing, and system heuristics models, and in response, deriving an initial recommended model of the service delivery system, the initial recommended model having a service level agreement attainment level that makes the initial recommended model substantially similar to the adjusted discrete event simulation model, the adjusted queuing model, and the adjusted system heuristics model;

subsequent to the step of deriving the initial recommended model, the computer system receiving performance indicating factors indicating measures of performance across multiple pools of resources utilized by the service delivery system;

the computer system determining a variation between the performance indicating factors and a first capacity release of the service delivery system modeled by the initial recommended model, the first capacity release indicating a difference between current staffing and to-be staffing based on the initial recommended model;

the computer system determining trend differences that indicate the variation between the performance indicating factors and the first capacity release of the service delivery system modeled by the initial recommended model; and

based on the trend differences, the computer system deriving a subsequent recommended model of the service delivery system, wherein the subsequent recommended model reduces the trend differences; and

based on the subsequent recommended model, the computer system recommending a level of staffing required to optimize the service delivery system.

6. The method of claim 4, further comprising the steps of:

the computer system determining the trend differences indicate a lack of consistency between the discrete event simulation, queuing, and system heuristic models;

based on the lack of consistency, the computer system determining one or more adjustments to the discrete event simulation model; and

the computer system adjusting the discrete event simulation model based on the one or more adjustments, wherein the step of the computer system deriving the subsequent recommended model based on the trend differences includes deriving the subsequent recommended model from the adjusted discrete event simulation model, and wherein the subsequent recommended model reduces the trend differences.

8. The method of claim 4, further comprising the step of the computer system validating the recommended level of staffing required to optimize the service delivery system.

9. The method of claim 4, further comprising the steps of:

subsequent to the step of recommending the level of staffing required to optimize the service delivery system, the computer system determining that the service delivery system requires feedback that indicates how well an implementation of the recommended level of staffing satisfies business goals;

using a functional prototype of the service delivery system, the computer system implementing the recommended level of staffing required to optimize the service delivery system;

subsequent to the step of implementing the recommended level of staffing required to optimize the service delivery system, the computer system obtaining the feedback indicating how well the implemented recommended level of staffing satisfies the business goals;

based on the obtained feedback, the computer system determining one or more additional adjustments to the discrete event simulation model;

the computer system further adjusting the discrete event simulation model based on the one or more additional adjustments; and

based on the further adjusted discrete event simulation model, the computer system validating the recommended level of staffing required to optimize the service delivery system.

10. The method of claim 4, wherein the step of the computer system collecting data from the service delivery system includes the computer system collecting operation data of the service delivery system and workflow data of the service delivery system, and wherein the step of determining the problem that causes the first variations among the first, second and third measures of the utilization of staffing includes determining that arrival patterns or service time distributions are not correctly derived from the operation data and the workflow data.

27. The method of claim 4, further comprising the steps of:

subsequent to the step of constructing the first, second and third models and prior to the step of determining the first variations, the computer system running the discrete event simulation, queuing and system heuristics models simultaneously, wherein the step of running the discrete event simulation, queuing and system heuristics simultaneously includes performing simultaneously the steps of determining the first, second and third measures of the utilization of staffing by the service delivery system; and

subsequent to the step of adjusting the discrete event simulation, queuing and system heuristics models and prior to the step of determining the second variations, the computer system running the adjusted discrete event simulation, the adjusted queuing and the adjusted system heuristics models simultaneously, wherein the step of running the adjusted discrete event simulation, the adjusted queuing and the adjusted system heuristics models simultaneously includes performing simultaneously the steps of determining the fourth, fifth and sixth measures of the utilization of staffing by the service delivery system.

5. (canceled)

7. (canceled)

11-12. -12. (canceled)

13. A computer system comprising:

a central processing unit (CPU);

a memory coupled to the CPU;

a computer-readable, tangible storage device coupled to the CPU, the storage device not being a transitory form of signal transmission, and the storage device containing program instructions that, when executed by the CPU via the memory, implement a method of modeling a service delivery system, the method comprising the steps of;

the computer system collecting data from the service delivery system;

the computer system constructing first, second and third models of the service delivery system from the collected data, the first model being a discrete event simulation model based work types, arrival rate, and service times for the work types, the second model being a queuing model based on a queuing formula that uses Little'"'"'s theorem, arrival time, service time, and a mean arrival rate divided by a mean service rate, and the third model being a system heuristics model based on pool performance and agent behaviors;

based on the discrete event simulation first model, the computer system determining a first measure of a utilization of staffing by the service delivery system;

based on the queuing model, the computer system determining a second measure of the utilization of staffing by the service delivery system;

based on the system heuristics model, the computer system determining a third measure of the utilization of staffing by the service delivery system;

the computer system determining first variations among the first, second and third measures of the utilization of staffing by the service delivery system;

the computer system determining a first utilization error that indicates the first variations among the first, second and third measures of the utilization of staffing by the service delivery system;

based on the first utilization error, the computer system determining a problem that causes the first variations among the first, second and third measures of the utilization of staffing, and in response, determining adjustments to the discrete event simulation, queuing, and system heuristics models;

based on the adjustments, the computer system adjusting the discrete event simulation, queuing, and system heuristics models to correct the problem that causes the variations;

based on the adjusted discrete event simulation model, the computer system determining a fourth measure of the utilization of staffing by the service delivery system;

based on the adjusted queuing model, the computer system determining a fifth measure of the utilization of staffing by the service delivery system;

based on the adjusted system heuristics model, the computer system determining a sixth measure of the utilization of staffing by the service delivery system;

the computer system determining second variations among the fourth, fifth and sixth measures of the utilization of staffing by the service delivery system;

the computer system determining a second utilization error that indicates the second variations among the fourth, fifth and sixth measures of the utilization of staffing by the service delivery system;

based on the second utilization error, the computer system determining a consistency among the adjusted discrete event simulation, queuing, and system heuristics models, and in response, deriving an initial recommended model of the service delivery system, the initial recommended model having a service level agreement attainment level that makes the initial recommended model substantially similar to the adjusted discrete event simulation model, the adjusted queuing model, and the adjusted system heuristics model;

subsequent to the step of deriving the initial recommended model, the computer system receiving performance indicating factors indicating measures of performance across multiple pools of resources utilized by the service delivery system;

the computer system determining a variation between the performance indicating factors and a first capacity release of the service delivery system modeled by the initial recommended model, the first capacity release indicating a difference between current staffing and to-be staffing based on the initial recommended model;

the computer system determining trend differences that indicate the variation between the performance indicating factors and the first capacity release of the service delivery system modeled by the initial recommended model; and

based on the trend differences, the computer system deriving a subsequent recommended model of the service delivery system, wherein the subsequent recommended model reduces the trend differences; and

based on the subsequent recommended model, the computer system recommending a level of staffing required to optimize the service delivery system.

15. The computer system of claim 13, wherein the method further comprises the steps of:

the computer system determining the trend differences indicate a lack of consistency between the discrete event simulation, queuing, and system heuristic models;

based on the lack of consistency, the computer system determining one or more adjustments to the discrete event simulation model; and

the computer system adjusting the discrete event simulation model based on the one or more adjustments, wherein the step of the computer system deriving the subsequent recommended model based on the trend differences includes deriving the subsequent recommended model from the adjusted discrete event simulation model, and wherein the subsequent recommended model reduces the trend differences.

17. The computer system of claim 13, wherein the method further comprises the step of the computer system validating the recommended level of staffing required to optimize the service delivery system.

18. The computer system of claim 13, wherein the method further comprises the steps of:

subsequent to the step of recommending the level of staffing required to optimize the service delivery system, the computer system determining that the service delivery system requires feedback that indicates how well an implementation of the recommended level of staffing satisfies business goals;

using a functional prototype of the service delivery system, the computer system implementing the recommended level of staffing required to optimize the service delivery system;

subsequent to the step of implementing the recommended level of staffing required to optimize the service delivery system, the computer system obtaining the feedback indicating how well the implemented recommended level of staffing satisfies the business goals;

based on the obtained feedback, the computer system determining one or more additional adjustments to the discrete even simulation model;

the computer system further adjusting the discrete event simulation model based on the one or more additional adjustments; and

based on the further adjusted discrete event simulation model, the computer system validating the recommended level of staffing required to optimize the service delivery system.

19. The computer system of claim 13, wherein the step of the computer system collecting data from the service delivery system includes the computer system collecting operation data of the service delivery system and workflow data of the service delivery system, and wherein the step of determining the problem that causes the first variations among the first, second and third measures of the utilization of staffing includes determining that arrival patterns or service time distributions are not correctly derived from the operation data and the workflow data.

28. The computer system of claim 13, wherein the method further comprises the steps of:

subsequent to the step of constructing the first, second and third models and prior to the step of determining the first variations, the computer system running the discrete event simulation, queuing and system heuristics models simultaneously, wherein the step of running the discrete event simulation, queuing and system heuristics simultaneously includes performing simultaneously the steps of determining the first, second and third measures of the utilization of staffing by the service delivery system; and

subsequent to the step of adjusting the discrete event simulation, queuing and system heuristics models and prior to the step of determining the second variations, the computer system running the adjusted discrete event simulation, the adjusted queuing and the adjusted system heuristics models simultaneously, wherein the step of running the adjusted discrete event simulation, the adjusted queuing and the adjusted system heuristics models simultaneously includes performing simultaneously the steps of determining the fourth, fifth and sixth measures of the utilization of staffing by the service delivery system.

14. (canceled)

16. (canceled)

20. A computer program product comprising:

a computer-readable, tangible storage device having computer-readable program instructions stored therein, the computer-readable program instructions, when executed by a central processing unit (CPU) of a computer system, implement a method of modeling a service delivery system, the method comprising the steps of;

the computer system collecting data from the service delivery system;

the computer system constructing first, second and third models of the service delivery system from the collected data, the first model being a discrete event simulation model based work types, arrival rate, and service times for the work types, the second model being a queuing model based on a queuing formula that uses Little'"'"'s theorem, arrival time, service time, and a mean arrival rate divided by a mean service rate, and the third model being a system heuristics model based on pool performance and agent behaviors;

based on the discrete event simulation model, the computer system determining a first measure of a utilization of staffing by the service delivery system;

based on the queuing model, the computer system determining a second measure of the utilization of staffing by the service delivery system;

based on the system heuristics model, the computer system determining a third measure of the utilization of staffing by the service delivery system;

the computer system determining first variations among the first, second and third measures of the utilization of staffing by the service delivery system;

the computer system determining a first utilization error that indicates the first variations among the first, second and third measures of the utilization of staffing by the service delivery system;

based on the first utilization error, the computer system determining a problem that causes the first variations among the first, second and third measures of the utilization of staffing, and in response, determining adjustments to the discrete event simulation, queuing, and system heuristics models;

based on the adjustments, the computer system adjusting the discrete event simulation, queuing, and system heuristics models to correct the problem that causes the variations;

based on the adjusted discrete event simulation model, the computer system determining a fourth measure of the utilization of staffing by the service delivery system;

based on the adjusted queuing model, the computer system determining a fifth measure of the utilization of staffing by the service delivery system;

based on the adjusted system heuristics model, the computer system determining a sixth measure of the utilization of staffing by the service delivery system;

the computer system determining second variations among the fourth, fifth and sixth measures of the utilization of staffing by the service delivery system;

the computer system determining a second utilization error that indicates the second variations among the fourth, fifth and sixth measures of the utilization of staffing by the service delivery system;

based on the second utilization error, the computer system determining a consistency among the adjusted discrete event simulation, queuing and system heuristic models, and in response, deriving an initial recommended model of the service delivery system, the initial recommended model having a service level agreement attainment level that makes the initial recommended model substantially similar to the adjusted discrete event simulation model, the adjusted queuing model, and the adjusted system heuristics model;

subsequent to the step of deriving the initial recommended model, the computer system receiving performance indicating factors indicating measures of performance across multiple pools of resources utilized by the service delivery system;

the computer system determining a variation between the performance indicating factors and a first capacity release of the service delivery system modeled by the initial recommended model, the first capacity release indicating a difference between current staffing and to-be staffing based on the initial recommended model;

the computer system determining trend differences that indicate the variation the performance indicating factors and the first capacity release of the service delivery system modeled by the initial recommended model; and

based on the trend differences, the computer system deriving a subsequent recommended model of the service delivery system, wherein the subsequent recommended model reduces the trend differences; and

based on the subsequent recommended model, the computer system recommending a level of staffing required to optimize the service delivery system.

22. The program product of claim 20, wherein the method further comprises the steps of:

the computer system determining the trend differences indicate a lack of consistency between the discrete event simulation, queuing and system heuristic models;

based on the lack of consistency, the computer system determining one or more adjustments to the discrete event simulation model; and

the computer system adjusting the discrete event simulation model based on the one or more adjustments, wherein the step of the computer system deriving the subsequent recommended model based on the trend differences includes deriving the subsequent recommended model from the adjusted discrete event simulation first model, and wherein the subsequent recommended model reduces the trend differences.

24. The program product of claim 20, wherein the method further comprises the step of the computer system validating the recommended level of staffing required to optimize the service delivery system.

25. The program product of claim 20, wherein the method further comprises the steps of:

subsequent to the step of recommending the level of staffing required to optimize the service delivery system, the computer system determining that the service delivery system requires feedback that indicates how well an implementation of the recommended level of staffing satisfies business goals;

using a functional prototype of the service delivery system, the computer system implementing the recommended level of staffing required to optimize the service delivery system;

subsequent to the step of implementing the recommended level of staffing required to optimize the service delivery system, the computer system obtaining the feedback indicating how well the implemented recommended level of staffing satisfies the business goals;

based on the obtained feedback, the computer system determining one or more additional adjustments to the discrete event simulation model;

the computer system further adjusting the discrete event simulation model based on the one or more additional adjustments; and

based on the further adjusted discrete event simulation model, the computer system validating the recommended level of staffing required to optimize the service delivery system.

26. The program product of claim 20, wherein the step of the computer system collecting data from the service delivery system includes the computer system collecting operation data of the service delivery system and workflow data of the service delivery system, and wherein the step of determining the problem that causes the first variations among the first, second and third measures of the utilization of staffing includes determining that arrival patterns or service time distributions are not correctly derived from the operation data and the workflow data.

29. The program product of claim 20, wherein the method further comprises the steps of:

subsequent to the step of constructing the first, second and third models and prior to the step of determining the first variations, the computer system running the discrete event simulation, queuing and system heuristics models simultaneously, wherein the step of running the discrete event simulation, queuing and system heuristics simultaneously includes performing simultaneously the steps of determining the first, second and third measures of the utilization of staffing by the service delivery system; and

subsequent to the step of adjusting the discrete event simulation, queuing and system heuristics models and prior to the step of determining the second variations, the computer system running the adjusted discrete event simulation, the adjusted queuing and the adjusted system heuristics models simultaneously, wherein the step of running the adjusted discrete event simulation, the adjusted queuing and the adjusted system heuristics models simultaneously includes performing simultaneously the steps of determining the fourth, fifth and sixth measures of the utilization of staffing by the service delivery system.

21. (canceled)

23. (canceled)