Resource optimization system, method and computer program for business transformation outsourcing with reoptimization on demand

• US 7,885,848 B2
• Filed: 02/17/2005
• Issued: 02/08/2011
• Est. Priority Date: 02/17/2005
• Status: Expired due to Fees

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Kagan, Steven M., Morales, Philip J., Ricketts, John A.
• Primary Examiner(s): Jeanty; Romain
• Assistant Examiner(s): Singh; Gurkanwaljit
• Application Number:
  US11/060,022
• Publication Number:
  US 20060184412A1
• Time in Patent Office: 2,182 Days
• Field of Search: 705/7, 705/8
• US Class Current: 1/1
• 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 10/06312 Adjustment or analysis of established resource schedule, e.g. resource or task levelling, or dynamic rescheduling
• CPC Class Codes: G06Q 10/06315 Needs-based resource requirements planning or analysis
• CPC Class Codes: G06Q 10/0637 Strategic management or analysis, e.g. setting a goal or target of an organisation; Planning actions based on goals; Analysis or evaluation of effectiveness of goals
• CPC Class Codes: G06Q 10/06375 Prediction of business process outcome or impact based on a proposed change

Abstract

Disclosed are a method, a system and a computer program for managing services of human resources. The method comprises the steps of modeling human resources delivery services from a services provider to a client company to determine outputs from inputs and constraints; and constructing an objective function representative of services resources at said services provider. The method also comprises the steps of determining optimum levels of human resources based on said modeling, said constraints, and said objective function; and allocating said human resources based upon said optimum levels. Preferably, said optimum levels of resources are determined over tiers, sites and time periods. The preferred embodiment of the invention is a system and a method for resource allocation on BTO projects. This preferred system includes an optimization model, along with its inputs and outputs. This system may be used to address dynamic client needs before and during BTO projects.

Claims

1. A computer implemented method of allocating human resources to a client at a plurality of levels, across sites, tiers and time periods, on business transformation outsourcing projects, the method comprising the steps of:

modeling a human resources delivery services from a services provider to a client company to determine outputs from inputs and constraints;

constructing an objective function representative of services resources at said services provider, including the step of constructing an optimization model for optimizing one or more defined objectives, said optimization model having parameters and constraints, and being nonlinear, noninteger and smooth, said optimization model comprising a set of formulas including a number of variables, wherein said number of variables include a plurality of levels of human resources across sites, tiers, and time periods for the client;

determining optimum levels of human resources for the client based on said modeling, said constraints, and said objective function, including the steps of;

solving, using a computer system, the optimization model using determined values for the parameters and constraints of the optimization model, including adjusting some of the parameters and constraints of the optimization model, and estimating a valid range for each of the parameters and constraints of the optimization model, solving the optimization model at various points across the ranges of the constraints of the optimization model to produce a solution to the optimization model, including identifying a set of values for said plurality of levels of human resources wherein, when said set of values are used in the optimization model, the optimization model maximizes or minimizes a specified one of the defined objectives,

identifying leverage points in said solution, said leverage points being small changes in parameters and constraints that produce large changes in said one or more defined objectives, and

determining whether selected changes in the leverage points are acceptable to the client company and to the service provider according to defined criteria; and

allocating said human resources based upon said optimum levels; and

wherein;

said sites include both the client'"'"'s and the services provider'"'"'s locations;

the service tiers include experts, specialists, generalists, and self-service;

the constraints of the optimization model include;

a lower bound on full time equivalent resources (FTEs) by site and tier that the client selects to retain as employees; and

upper and lower bounds on FTEs by site and tier determined by the services provider; and

the parameters of the optimization model include;

the clients original FTEs by site and tier;

labor cost per FTE by site and tier; and

work migration costs by site and tier.

2. A method according to claim 1, wherein said determining step includes the steps of:

subjecting said inputs to said constraints; and

determining said optimum levels of resources over tiers, sites and periods.

3. A method according to claim 1, wherein said modeling step includes the step of, for at least one of said constraints, identifying the sensitivity of said one of said constraints.

4. A method according to claim 1, wherein said modeling step includes the step of, for at least one of said constraints, determining a valid range for said one of said constraints.

5. A method according to claim 1, comprising the further steps of:

repeating said modeling, constructing, and determining steps to identify new solutions to optimize said levels of unutilized services resources; and

implementing said new solutions to adjust said levels of unutilized resources based on changing business factors.

6. A method according to claim 5, wherein said business factors include at least one of:

business conditions, and business strategy.

22. The method according to claim 1, wherein the solving the optimization model at various points includes using most likely values for the parameters and constraints;

and if no solution is found, then adjusting one or more of the constraints and parameters until a solution is found.

23. The method according to claim 22, wherein the solving the optimization model at various points includes identifying one of the constraints of the optimization model;

and starting with said most sensitive constraint identified one of the constraints, solving the optimization model, and examining results of the solving for improvement in the given objective;

the parameters of the optimization model further include currency exchange rates, and expected inflation rates by country;

a group of intermediate computations link the inputs to the outputs, and said intermediate computations include unit costs, adjusted for currency exchange rates and inflation;

FTEs by period by site by tier; and

movement of work between tiers; and

the specified one of the defined objectives is to maximize the client'"'"'s savings from outsourcing particular business processes.

7. A managing system for managing services of allocating human resources to a client at a plurality of levels, across sites, tiers and time periods, on business transformation outsourcing projects, the managing system comprising:

a computer memory;

one or more computer processors; and

a computer executable program stored on the one or more computer readable mediums, wherein the computer executable program, when executed by the one or more computer processors performs the steps of;

modeling a human resources delivery services from a services provider to a client company to determine outputs from inputs and constraints;

constructing an objective function representative of services resources at said services provider, including constructing an optimization model for optimizing one or more defined objectives, said optimization model having parameters and constraints and being nonlinear, noninteger and smooth, said optimization model comprising a set of formulas including a number of variables, wherein said number of variables include a plurality of levels of human resources across sites, tiers, and time periods for the client;

determining optimum levels of human resources for the client based on said modeling, said constraints, and said objective function, including;

solving the optimization model using determined values for the parameters and constraints of the optimization model, including adjusting some of the parameters and constraints of the optimization model, and estimating a valid range for each of the parameters and constraints of the optimization model, solving the optimization model at various points across the ranges of the constraints of the optimization model to produce a solution to the optimization model, including identifying a set of values for said plurality of levels of human resources wherein, when said set of values are used in the optimization model, the optimization model maximizes or minimizes a specified one of the defined objectives,

identifying leverage points in said solution, said leverage points being small changes in parameters and constraints that produce large changes in said one or more defined objectives, and

determining whether selected changes in the leverage points are acceptable to the client company and to the service provider according to defined criteria; and

allocating said human resources to the client company based upon said optimum levels; and

wherein;

said sites include both the client'"'"'s and the services provider'"'"'s locations;

the service tiers include experts, specialists, generalists, and self-service;

the constraints of the optimization model include;

a lower bound on full time equivalent resources (FTEs) by site and tier that the client selects to retain as employees; and

upper and lower bounds on FTEs by site and tier determined by the services provider; and

the parameters of the optimization model include;

the clients original FTEs by site and tier;

labor cost per FTE by site and tier; and

work migration costs by site and tier.

8. A managing system according to claim 7, wherein said determining includes:

subjecting said inputs to said constraints; and

determining said optimum levels of resources over tiers, sites and periods.

9. A system managing according to claim 7, wherein said modeling includes identifying the sensitivity of at least one of said constraints.

10. A system managing according to claim 7, wherein said modeling includes determining a valid range for at least one of said constraints.

11. A managing system according to claim 7, wherein the computer system is further configured for:

repeating said modeling, constructing, and determining to identify new solutions to optimize said levels of unutilized services resources; and

implementing said new solutions to adjust said levels of unutilized resources based on changing business factors, wherein;

said business factors include at least one of (i) business conditions, and (ii) business strategy.

12. A computer program storage device readable by a computer, tangibly embodying a program of instructions executable by the computer to perform method steps for allocating human resources to a client at a plurality of levels, across sites, tiers and time periods, on business transformation outsourcing projects, said method steps comprising:

modeling a human resources delivery services from a services provider to a client company to determine outputs from inputs and constraints;

constructing an objective function representative of services resources at said services provider, including the step of constructing an optimization model for optimizing one or more defined objectives, said optimization model having parameters and constraints and being nonlinear, noninteger and smooth, said optimization model comprising a set of formulas including a number of variables, wherein said number of variables include a plurality of levels of human resources across sites, tiers, and time periods for the client;

determining optimum levels of human resources based on said modeling, said constraints, and said objective function, including the steps of;

solving the optimization model using determined values for the parameters and constraints of the optimization model, including adjusting some of the parameters and constraints of the optimization model, and estimating a valid range for each of the parameters and constraints of the optimization model, solving the optimization model at various points across the ranges of the constraints of the optimization model to produce a solution to the optimization model, including identifying a set of values for said plurality of levels of human resources wherein, when said set of values are used in the optimization model, the optimization model maximizes or minimizes a specified one of the defined objectives,

identifying leverage points in said solution, said leverage points being small changes in parameters and constraints that produce large changes in said one or more defined objectives, and

determining whether selected changes in the leverage points are acceptable to the client company and to the service provider according to defined criteria; and

allocating said human resources to the client company based upon said optimum levels; and

wherein;

said sites include both the client'"'"'s and the services provider'"'"'s locations;

the service tiers include experts, specialists, generalists, and self-service;

the constraints of the optimization model include;

a lower bound on full time equivalent resources (FTEs) by site and tier that the client selects to retain as employees; and

upper and lower bounds on FTEs by site and tier determined by the services provider; and

the parameters of the optimization model include;

the clients original FTEs by site and tier;

labor cost per FTE by site and tier; and

work migration costs by site and tier.

13. A program storage device according to claim 12, wherein said determining step includes the steps of:

subjecting said inputs to said constraints; and

determining said optimum levels of resources over tiers, sites and periods.

14. A program storage device according to claim 12, wherein said modeling step includes the step of,

for at least one of said constraints, identifying the sensitivity of said one of said constraints.

15. A program storage device according to claim 12, wherein said modeling step includes the step of,

for at least one of said constraints, determining a valid range for said one of said constraints.

16. A program storage device according to claim 12, wherein said method steps

further comprise:

repeating said modeling, constructing, and determining steps to identify new solutions to optimize said levels of unutilized services resources; and

implementing said new solutions to adjust said levels of unutilized resources based on changing business factors; and

wherein

said business factors include at least one of (i) business conditions, and (ii) business strategy.

17. A method of deploying a computer program product for allocating human resources to a client at a plurality of levels, across sites, tiers and time periods, on business transformation outsourcing projects, the method comprising the steps of:

performing the following steps via a computer;

modeling a human resources delivery services from a services provider to a client company to determine outputs from inputs and constraints;

constructing an objective function representative of services resources at said services provider, including the step of constructing an optimization model for optimizing one or more defined objectives, said optimization model having parameters and constraints, and being nonlinear, noninteger and smooth, said optimization model comprising a set of formulas including a number of variables, wherein said number of variables include a plurality of levels of human resources across sites, tiers, and time periods for the client;

determining optimum levels of human resources for the client based on said modeling, said constraints, and said objective function, including the steps of;

solving the optimization model using determined values for the parameters and constraints of the optimization model, including adjusting some of the parameters and constraints of the optimization model, and estimating a valid range for each of the parameters and constraints of the optimization model, solving the optimization model at various points across the ranges of the constraints of the optimization model to produce a solution to the optimization model, including identifying a set of values for said plurality of levels of human resources wherein, when said set of values are used in the optimization model, the optimization model maximizes or minimizes a specified one of the defined objectives,

identifying leverage points in said solution, said leverage points being small changes in parameters and constraints that produce large changes in said one or more defined objectives, and

determining whether selected changes in the leverage points are acceptable to the client company and to the service provider according to defined criteria; and

allocating said human resources to the client company based upon said optimum levels; and

wherein;

said sites include both the client'"'"'s and the services provider'"'"'s locations;

the service tiers include experts, specialists, generalists, and self-service;

the constraints of the optimization model include;

a lower bound on full time equivalent resources (FTEs) by site and tier that the client selects to retain as employees; and

upper and lower bounds on FTEs by site and tier determined by the services provider; and

the parameters of the optimization model include;

the clients original FTEs by site and tier;

labor cost per FTE by site and tier; and

work migration costs by site and tier.

18. A method according to claim 17, wherein said determining step includes the steps of:

subjecting said inputs to said constraints; and

determining said optimum levels of resources over tiers, sites and periods.

19. A method according to claim 17, wherein said modeling step includes the step of, for at least one of said constraints, identifying a sensitivity of said one of said constraints.

20. A method according to claim 17, wherein said modeling step includes the step of, for at least one of said constraints, determining a valid range for said one of said constraints.

21. A method according to claim 17, wherein said method steps further comprise:

repeating said modeling, constructing, and determining steps to identify new solutions to optimize said levels of unutilized services resources; and

implementing said new solutions to adjust said levels of unutilized resources based on changing business factors; and

wherein

said business factors include at least one of (i) business conditions, and (ii) business strategy.