William H Phifer

US Patent:

20050222893, Oct 6, 2005

Filed:

Apr 5, 2004

Appl. No.:

10/818013

Inventors:

Kasra Kasravi - West Bloomfield MI, US
Reinier Aerdts - Plano TX, US
Randall Mears - Plano TX, US
William Phifer - Downingtown PA, US
Jeffrey Wacker - Plano TX, US

International Classification:

G06F017/60

US Classification:

705010000

Abstract:

A method, system, and computer program product for improving an organization's business adaptability is provided. In one embodiment, a taxonomy is created wherein the taxonomy comprises a hierarchical list of taxonomy indicators that captures organizational elements that can be used to measure an organization's responsiveness to change and wherein the taxonomy indicators are industry specific. A set of weights associated with the elements of the taxonomy, indicating a relevant contribution of each element to an overall adaptability of an organization, are assigned. The weights are industry specific. An enterprise profile for the organization is determined and an adaptability result of the organization is calculated from the weights, taxonomy, and enterprise profile. The adaptability result provides a quantitative assessment of the organization's adaptability. Recommendations for improving the adaptability of the organization are then determined using a rules engine and/or heuristics and utilizing the adaptability result, the taxonomy, the enterprise profile, and data gathered in creating the taxonomy, the enterprise profile, and the set of weights.

US Patent:

6970803, Nov 29, 2005

Filed:

Oct 25, 2002

Appl. No.:

10/280082

Inventors:

Reinier J. Aerdts - Plano TX, US
Thomas L. Hill - Dallas TX, US
Theodore M. Page - Sterling Heights MI, US
William H. Phifer - Downingtown PA, US
David J. Schmid - Rochester Hills MI, US
Brent L. Blackburn - Allen TX, US

Assignee:

Electronic Data Systems Corporation - Plano TX

International Classification:

G06F017/60

US Classification:

702179, 702186, 702183, 717101

Abstract:

Techniques are described for determining the complexity of a computing environment. The techniques include developing a model for the complexity of a computing environment based on the quantity of particular elements of the computing environment. The model includes two statistical weights for each element in the complexity model. One statistical weight is applied to each element to provide a complexity rating of the element. Another statistical weight is applied to each element to provide a complexity rating across all elements.