Method for real-time allocation of customer service resources and opportunities for optimizing business and financial benefit

• US 20050228707A1
• Filed: 12/21/2004
• Published: 10/13/2005
• Est. Priority Date: 12/23/2003
• Status: Abandoned Application

• Current Assignee: Robert Hendrickson
• Original Assignee: Robert Hendrickson
• Inventors: Hendrickson, Robert
• Application Number:
  US11/018,843
• Publication Number:
  US 20050228707A1
• Time in Patent Office: Days
• US Class Current: 705/8
• 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 10/06375 Prediction of business process outcome or impact based on a proposed change
• CPC Class Codes: G06Q 10/0639 Performance analysis of employees; Performance analysis of enterprise or organisation operations
• CPC Class Codes: G06Q 30/0202 Market predictions or forecasting for commercial activities
• CPC Class Codes: G06Q 30/0205 Location or geographical consideration

Abstract

A method and systems architecture for allocating and adjusting service delivery resources in real-time on the basis of predicting associated financial profits and/or benefits to an organization. The method includes the steps of: a) determining service resource costs and characteristics, b) predicting service demand, c) setting service objectives are determined at step, d) determining a service capacity, e) setting associated service delivery rules, and f) allocating resources according to the business rules. Actual resource availability and service performance are monitored in real-time, and profitability of service performance is forecast based on real-time data and simulations. Results from profitability analysis are used to adjust predicted service demand, service objectives, service delivery rules and resource allocations in real-time.

Claims

1. A method for allocating resources for delivery of a customer service, the method comprising the steps of:

a) forecasting an anticipated service demand for the customer service;

b) forecasting available resources for service delivery

c) setting desired service objectives for delivery of the customer service to each of one or more customer classes;

d) setting a service capacity according to the anticipated service demand, the desired service objectives and the available resources;

e) setting business rules for service delivery based on the desired service objectives for the one or more customer classes;

f) allocating the available resources based on the service capacity and business rules;

g) monitoring actual service demand, resource availability and service delivery performance against the desired service objectives;

h) forecasting a measure of profitability of service delivery based on the monitored service demand, resource availability and service delivery performance;

i) adjusting the desired service objectives in real-time to maximize the measure of profitability of service delivery;

j) repeating steps a)-f) in real-time based on the adjusted service objectives, the monitored service demand and the monitored resource availability.

2. The method of claim 1, wherein the anticipated service demand and available resources are forecast based on historical data.

3. The method of claim 2, wherein the anticipated service demand and available resources are forecast by means of statistical models.

4. The method of claim 1, wherein the anticipated service demand is forecast for each of a plurality of spatial service locations, service capacities are set for each of the plurality of spatial service locations, and available resources are allocated among the plurality of spatial service locations as a function of the service capacities.

5. The method of claim 1, wherein the anticipated service demand is forecast for each of the one or more customer classes.

6. The method of claim 1, wherein allocated resources include at least one of labor, equipment, products, literature, materials, customer goodwill and time.

7. The method of claim 1, wherein the anticipated service demand is forecast as a function of required service delivery skill sets, and the available resources are classified and allocated according to associated service delivery skill sets.

8. A system architecture for allocating resources for delivering customer service, the architecture comprising:

a data collection layer for collecting information from one or more data sources relating to at least one of a cost of resources for delivering services, a historical service demand, a current resource capacity, and measures of historical service delivery performance;

a data processing layer for processing the information provided by the one or more data sources to produce a set of business rules for service delivery, the business rules including service delivery objectives;

a utilization and prioritization layer for operating one or more service applications according to the business rules, including at least one service application for allocating resources for service delivery; and

an optimization and forecasting layer for evaluating service delivery performance in real-time to forecast service delivery profitability, wherein service delivery profitability is predicted as a function of a cost of allocated resources, a predicted profit based on customer value for services delivered at or above the service delivery objectives, and a predicted cost based on customer value for services delivered below the service delivery objectives.

9. The system architecture according to claim 8, wherein;

the optimization and forecasting layer forecasts future service demand and future resource availability and predicts an optimal allocation of forecast resources for maximizing service delivery profitability.

10. The system architecture according to claim 9, wherein:

forecast information from the optimization and forecasting layer is provided to the data processing layer in real-time for adjusting the business rules.

11. The system architecture according to claim 9, wherein:

the optimization and forecasting layer simulates future service demand, future resource availability and future service delivery performance to predict the optimal allocation of forecast resources for maximizing service delivery profitability.