Autonomic determination and location of product support infrastructure resources

• US 20060047550A1
• Filed: 09/02/2004
• Published: 03/02/2006
• Est. Priority Date: 09/02/2004
• Status: Active Grant

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Johnson, Verlyn Mark, Olausen, Janet Rooney, Dineen, Lisbeth Ann, Laskowski, John Edward, Roscher, Clark Lewis, Stockey, Christina Anne
• Granted Patent: US 8,285,579 B2
• 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 10/06311 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 autonomic 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 method for autonomic determination of resource allocation for a product, said method comprising:

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;

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;

analyzing historical usage of similar products; and

performing an autonomic determination of best allocation of product support resources from a combination of said product complexity, target market maturity and historical usage metrics from said calculating, evaluating and analyzing steps.

2. The method of claim 1, wherein said performing step further comprises:

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

entering a series of responses to questions about the characteristics of the product and the target market in an algorithm designed to produce a result of said best allocation of product support resources with said responses an the historical usage data.

3. The method of claim 1 further comprising

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

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

5. The method of claim 1, wherein said calculating step further comprises:

identifying the product;

determining a list of characteristics for use in assessing classifications of said product complexity and market maturity, wherein said determining step includes;

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 that is attributable to said product and a second value to each characteristic not attributable to said product; and

evaluating a relative rating of said product against a normalized rating chart based on a calculation involving said values assigned to each characteristic.

6. The method of claim 5, wherein said identifying step further includes:

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

7. The method of claim 5, wherein said calculation within said identifying step includes:

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

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

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

8. The method of claim 1, wherein when multiple products are being developed for later release, said performing step comprises:

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

9. A system for autonomic determination of resource allocation for a product, said system comprising:

means for algorithmically classifying products that requiring a support infrastructure based on a combination of determined product complexity and target market maturity;

means for determining support resource allocations based on that combined classification along with historical usage records for similarly classified products; and

means for automating said classifying and determining means, whereby the support resource allocations are returned in an autonomic format comprising a series of variables and associated values.

10. The system of claim 9 wherein:

said means for algorithmically classifying products comprises;

means for 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

means 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

said means for determining support resource allocations comprises;

means for analyzing historical usage of similar products; and

means for performing an autonomic determination of best allocation of product support resources from a combination of said product complexity, target market maturity and historical usage metrics from said calculating, evaluating and analyzing means, said means for performing includes;

means for importing data about said historical usage from a database of historical usage, and

means for a user to enter a series of responses to questions about the characteristics of the product and the target market in an algorithm designed to produce a result of said best allocation of product support resources with said responses an the historical usage data.

11. The system of claim 9, further comprising

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

12. The system of claim 9, further comprising:

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

when updates to data concerning said product characteristics and said market maturity are received post-release of said product, means for initiating a re-analysis of said product for an updated resource allocation calculation, wherein said resource allocation is periodically updated based on real-time application of the product in the customer environment.

13. The system of claim 10, wherein said calculating means further comprises:

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

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

means for defining a weighting factor for each complexity classification; and

means for determining data sources to be evaluated for each classification;

means for assigning a first value to each characteristic that is attributable to said product and a second value to each characteristic not attributable to said product; and

means for evaluating a relative rating of said product against a normalized rating chart based on a calculation involving said values assigned to each characteristic.

14. The system of claim 13, wherein said calculation within said means for identifying includes:

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

means, when the same set of characteristics are utilized for each classification, for calculating both a product complexity score and a market maturity score as an average of the weighted score; and

means, when different characteristics are used for different classifications, for calculating the product complexity score as the weighted sums of the percentage match of each classification, and calculating the market maturity score as a maximum of the percentage match of each classification.

15. A computer program product comprising:

a computer readable medium; and

instruction means on said computer readable medium for autonomic determination of resource allocation for a product, said instruction means including;

instruction means for algorithmically classifying products that requiring a support infrastructure based on a combination of determined product complexity and target market maturity;

instruction means for determining support resource allocations based on that combined classification along with historical usage records for similarly classified products; and

instruction means for returning said support resource allocations in an autonomic format comprising a series of variables and associated values.

16. The computer program product of claim 15, further comprising:

instruction means for providing a graphical user interface (GUI) that includes a display of product characteristics for each classification and receives user responses to each of said product characteristics;

instruction means for calculating said product complexity and market maturity from said user responses; and

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

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

17. The computer program product of claim 15 wherein:

said instruction means for algorithmically classifying products comprises;

instruction means for 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

instruction means 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

said instruction means for determining support resource allocations comprises;

instruction means for analyzing historical usage of similar products; and

instruction means for performing an autonomic determination of best allocation of product support resources from a combination of said product complexity, target market maturity and historical usage metrics from said calculating, evaluating and analyzing instruction means.

18. The computer program product of claim 17, wherein said autonomic determination comprises:

instruction means for importing data about said historical usage from a database of historical usage;

instruction means for a user to enter a series of responses to questions about the characteristics of the product and the target market in an algorithm designed to produce a result of said best allocation of product support resources with said responses an the historical usage data;

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

when updates to data concerning said product characteristics and said market maturity are received post-release of said product, instruction means for initiating a re-analysis of said product for an updated resource allocation calculation, wherein said resource allocation is periodically updated based on real-time application of the product in the customer environment.

19. The computer program product of claim 18, wherein said calculating comprises:

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

instruction means for identifying the product;

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

instruction means for defining a weighting factor for each complexity classification;

instruction means for determining data sources to be evaluated for each classification;

instruction means for assigning a first value to each characteristic that is attributable to said product and a second value to each characteristic not attributable to said product; and

instruction means for evaluating a relative rating of said product against a normalized rating chart based on a calculation involving said values assigned to each characteristic.

20. The computer program product of claim 19, wherein said calculation includes:

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

instruction means, when the same set of characteristics are utilized for each classification, for calculating both a product complexity score and a market maturity score as an average of the weighted score; and

instruction means, when different characteristics are used for different classifications, for calculating the product complexity score as the weighted sums of the percentage match of each classification, and calculating the market maturity score as a maximum of the percentage match of each classification.