Automatic determination and location of product support infrastructure resources

• US 8,285,579 B2
• Filed: 09/02/2004
• Issued: 10/09/2012
• Est. Priority Date: 09/02/2004
• Status: Expired due to Fees

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Dineen, Lisbeth Ann, Johnson, Verlyn Mark, Laskowski, John Edward, Olausen, Janet Rooney, Roscher, Clark Lewis, Stockey, Christina Anne
• Primary Examiner(s): Sterrett, Jonathan G
• Assistant Examiner(s): Lan, Tzu-Hsiang
• Application Number:
  US10/932,703
• Publication Number:
  US 20060047550A1
• Time in Patent Office: 2,959 Days
• Field of Search: None
• US Class Current: 705/7.25
• 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 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G06Q 30/0201 Market modelling; Market analysis; Collecting market data

Abstract

A method and system for enabling an automatic determination and allocation of product support resources. The automated process allocates support resources based on a combination of product and market requirements and historical data on resources used by similar products in similar markets. Projects requiring a support infrastructure are algorithmically classified by a combination of product complexity metrics and target market maturity metrics. Then, support infrastructure requirements are calculated based on the combined classification along with historical usage records for similarly classified products. The classification and allocation process is automated so that a product (or multiple products competing for available resources) can self-provision/request its resource requirement as a part of the product development and go-to-market process.

Claims

1. A computer-implemented method for automatically determining post-release resource allocation for a consumer product, the method comprising a computer system performing the functions of:

calculating product complexity of the consumer product utilizing a plurality of product characteristics, including release number of the product, amount of change being made in the release, length of development cycle, and number of different development and support organizations involved;

evaluating target market maturity of the consumer product utilizing a plurality of market characteristics, including revenue growth or decline rate, and at least one of;

(a) educational classes in place, (b) a number of new classes, and (c) updates to existing classes required, and number of product demonstrations;

analyzing historical usage of similar products to the consumer product;

the computer system performing an automatic determination of a best allocation of post-release product support resources for the consumer product from a combination of the calculated product complexity, the target market maturity, the historical usage, and a consumer awareness of the post-release product support resources, wherein the best allocation of post-release product support resources correlates to a level of post-release product support resources utilized by consumers, and wherein the post-release product support resources include support for one or more of set-up, implementation, and maintenance of the consumer product;

providing the best allocation of post-release product support resources to the consumers;

wherein the calculating step further comprises;

identifying the product;

determining a list of characteristics for use in assessing classifications of the product complexity and market maturity, the determining further comprising;

defining a weighting factor for each complexity classification; and

determining data sources to be evaluated for each classification;

assigning a first value to each characteristic attributable to the product and a second value to each characteristic not attributable to the product; and

evaluating a relative rating of the product against a normalized rating chart based on a calculation involving at least one of the first value and the second value assigned to each characteristic, wherein evaluating the relative rating of the product based on the calculation further comprises;

determining whether each classification among multiple classifications for a product utilize a same set of characteristics;

in response to the same set of characteristics being utilized for each classification, calculating both a product complexity score and a market maturity score as an average of a weighted score; and

in response to different characteristics being used for different classifications, calculating the product complexity score as weighted sums of a percentage match of each classification, and calculating the market maturity score as a maximum of the percentage match of each classification.

2. The method of claim 1, performing the automatic determination further comprises:

importing data about the historical usage from a database of historical usage;

receiving a series of responses to questions about characteristics of the product and the target market;

evaluating the responses; and

determining the best allocation of post-release product support resources for the consumer product utilizing the evaluation of the responses and the historical usage data.

3. The method of claim 1 further comprising

outputting via an output device a result of the automatic determination, wherein the output represents a resource allocation that is implemented for the product when the product is released, the resource allocation including a number of personnel, an associated cost, and a level of marketing required for the product, and wherein the resource allocation is self-provisioned by a product developer within a development and go-to-market process for the product;

and

wherein the post-release product support resources include one or more of;

support personnel;

computer systems; and

equipment required for interfacing with portions of the product.

4. The method of claim 1, further comprising:

receiving one or more updates to product characteristics and market maturity from an external source; and

in response to receiving updates to data associated with the product characteristics and the market maturity post-release of the product, initiating a re-analysis of the product for an updated resource allocation calculation, wherein the resource allocation is periodically updated based on real-time application of the product in a customer environment.

5. The method of claim 1, the identifying the product further comprising:

first assigning clip levels indicating a break in the normalized rating chart at which a product evaluates as having a specific classification among multiple classifications delineated by the clip levels.

6. The method of claim 1, wherein the performing an automatic determination further comprises:

in response to multiple products being developed for later release, providing the autonomic determination of best allocation of post-release product support resources for each of the multiple products based on relative metrics calculated for each of the multiple products given a total amount of support resources available for allocating to a combination of the multiple products, wherein the performing step enables early preparation of an expected next-year budget requirement for an entire product portfolio.

7. A system for automatically determining resource allocation for a consumer product, the system comprising:

a processor configured to;

algorithmically classify consumer products that requiring a support infrastructure based on a combination of determined product complexity and target market maturity for each of the consumer products by calculating product complexity of each of the consumer products utilizing a plurality of product characteristics, including release number of the consumer products, amount of change being made in the release, length of development cycle, and number of different development and support organizations involved;

determine support resource allocations based on the combined classification along with historical usage records for similarly classified products for each of the consumer products;

return the support resource allocations for each of the consumer products as one or more of a series of variables and associated values;

perform an automatic determination of a best allocation of post-release product support resources for the consumer product from a combination of a calculated product complexity, the target market maturity, a historical usage, and a consumer awareness of the post-release product support resources, wherein the best allocation of post-release product support resources correlates to a level of post-release product support resources utilized by consumers, and wherein the post-release product support resources include support for one or more of set-up, implementation, and maintenance of the consumer product; and

provide the best allocation of post-release product support resources to the consumers;

wherein the calculating product complexity further comprises;

identifying each of the consumer products including first assigning clip levels indicating a break in a normalized rating chart at which a product evaluates as having a specific classification among multiple classifications delineated by the clip levels;

determining a list of characteristics for use in assessing classifications of the product complexity and market maturity, the determining including;

defining a weighting factor for each complexity classification; and

determining data sources to be evaluated for each classification;

assigning a first value to each characteristic attributable to each of the consumer products and a second value to each characteristic not attributable to each of the consumer products; and

evaluating a relative rating of each of the consumer products against a normalized rating chart based on a calculation involving at least one of the first value and the second value assigned to each characteristic, wherein evaluating based on the calculation comprises;

determining whether each classification among multiple classifications for a product utilize a same set of characteristics;

in response to the same set of characteristics being utilized for each classification, calculating both a product complexity score and a market maturity score as an average of a weighted score; and

in response to different characteristics being used for different classifications, calculating the product complexity score as weighted sums of a percentage match of each classification, and calculating the market maturity score as a maximum of the percentage match of each classification.

8. The system of claim 7 wherein:

the algorithmically classify consumer products further comprises;

evaluating target market maturity of each of the consumer products utilizing a plurality of market characteristics, including revenue growth or decline rate, and, at least one of;

(a) educational classes in place, (b) a number of new classes, and (c) updates to existing classes required, and number of product demonstrations;

the determine support resource allocations further comprises analyzing historical usage of similar products to each of the consumer products; and

the perform an automatic determination further comprises;

importing data about the historical usage from a database of historical usage; and

receiving a series of responses to questions about characteristics of the consumer products and the target market;

evaluating the responses; and

utilizing the evaluation of the responses and the historical usage data to determine the best allocation of post-release product support resources for the consumer product.

9. The system of claim 7, wherein the processor is further configured to:

output a result of the automatic determination, wherein the output represents a resource allocation that is implemented for the consumer products when the consumer products are released, the resource allocation including a number of personnel, an associated cost, and a level of marketing required for the consumer products, and wherein the resource allocation is self-provisioned by a product developer within a development and go-to-market process for the consumer products; and

wherein the post-release product support resources include one or more of;

support personnel;

computer systems; and

equipment required for interfacing with portions of the product.

10. The system of claim 7, wherein the processor is further configured to:

receive one or more updates to product characteristics and market maturity from an external source; and

in response to receiving updates to data associated with the product characteristics and the market maturity post-release of the consumer products, extend a re-analysis of the consumer products for an updated resource allocation calculation, wherein the resource allocation is periodically updated based on real-time application of the consumer products in a customer environment.

11. A computer program product comprising:

a computer readable storage medium; and

instructions on the computer readable storage medium that execute on a processor of a computer device to enable automatic determination of resource allocation for a consumer product, the instructions including instructions for;

algorithmically classifying consumer products that require a support infrastructure based on a combination of determined product complexity and target market maturity for each of the consumer products by calculating product complexity utilizing a plurality of product characteristics, including release number of the product, amount of change being made in the release, length of development cycle, and number of different development and support organizations involved; and

determining support resource allocations based on the combined classification along with historical usage records for similarly classified products for each of the consumer products;

returning the support resource allocations for each of the consumer products as one or more of a series of variables and associated values;

performing an automatic determination of a best allocation of post-release product support resources for the consumer product from a combination of a calculated product complexity, the target market maturity, the historical usage, and a consumer awareness of the post-release product support resources, wherein the best allocation of post-release product support resources correlates to a level of post-release product support resources utilized by consumers, and wherein the post-release product support resources include support for one or more of set-up, implementation, and maintenance of the consumer product; and

providing a best allocation of post-release product support resources to consumers of each consumer product

wherein the instructions for calculating further comprises instructions for;

first assigning clip levels indicating a break in the normalized rating chart at which a product evaluates as having a specific classification among multiple classifications delineated by the clip levels;

identifying the product;

determining a list of characteristics for use in assessing classifications of the product complexity and market maturity;

defining a weighting factor for each complexity classification;

determining data sources to be evaluated for each classification;

assigning a first value to each characteristic attributable to the product and a second value to each characteristic not attributable to the product; and

evaluating a relative rating of the product against a normalized rating chart based on a calculation involving at least one of the first value and the second value assigned to each characteristic, wherein the instructions for evaluating based on the calculation further comprises instructions for;

determining whether each classification among multiple classifications for a product utilize a same set of characteristics;

in response to the same set of characteristics being utilized for each classification, calculating both a product complexity score and a market maturity score as an average of a weighted score; and

in response to different characteristics being used for different classifications, calculating the product complexity score as weighted sums of a percentage match of each classification, and calculating the market maturity score as a maximum of the percentage match of each classification.

12. The computer program product of claim 11, further comprising instructions for:

providing a graphical user interface (GUI) that includes a display of product characteristics for each classification;

receiving, via the GUI, user responses to each of the product characteristics;

calculating the product complexity and market maturity from the user responses; and

outputting on an output device a result of the automatic determination, wherein the output represents a resource allocation that is implemented for each of the consumer products when each of the consumer products is released, the resource allocation including a number of personnel, an associated cost, and a level of marketing required for each of the consumer products, and wherein the resource allocation is self-provisioned by a product developer within a development and go-to-market process for each of the consumer products; and

in response to multiple products being developed for later release, providing the automatic determination of best allocation of post-release product support resources for each of the multiple products based on relative metrics calculated for each of the multiple products given a total amount of support resources available for allocating to a combination of the multiple products, wherein the performing—

enables early preparation of an expected next-year budget requirement for an entire product portfolio;

wherein the post-release product support resources include one or more of;

support personnel;

computer systems; and

equipment required for interfacing with portions of the product.

13. The computer program product of claim 11 wherein:

the instructions for algorithmically classifying consumer products further comprises instructions for;

evaluating target market maturity utilizing a plurality of market characteristics, including revenue growth or decline rate, educational classes in place or number of new classes or updates to existing classes required, and number of product demonstrations; and

the instructions for determining support resource allocations comprises instructions for analyzing historical usage of similar products.

14. The computer program product of claim 13, wherein the instructions for automatic determination further comprises instructions for:

importing data about the historical usage from a database of historical usage;

receiving a series of responses to questions about characteristics of each of the consumer products and the target market;

evaluating the responses;

utilizing the evaluation of the responses and the historical usage data to determine the best allocation of post-release product support resources for the consumer products;

receiving one or more updates to product characteristics and market maturity from an external source; and

in response to receiving updates to data associated with the product characteristics and the market maturity post-release of the consumer products, initiating a re-analysis of the consumer products for an updated resource allocation calculation, wherein the resource allocation is periodically updated based on real-time application of the consumer products in a customer environment.