International Business Machines Corporation

Rama K T Akkiraju

Juhnyoung Lee

David Amid

Ateret Anaby-Tavor

Salil Ahuja

Mitchell Mason

Rotem Aharonov

Jason M Leonard

Shun Jiang

Rakesh Mohan

Wei Ding

Chun Hua Tian

Anca-Andreea Ivan

Grace Y Lin

Timur Nurullaev

Sivaprashanth V Danturthy

Carl B Nordman

Hitansh Singala

Ponn Janaarthanan Sundhararajan

An intermediary server receives a resource request from a client computer for a requested resource that has a desired resource ability to optimize the client computer. The intermediary server identifies an alternative resource that has the desired resource ability to optimize the client computer, and determines that an ability of the alternative resource to provide the desired resource ability exceeds an ability of the requested resource to provide the desired resource ability. In response to determining that the ability of the alternative resource to provide the desired resource ability exceeds the ability of the requested resource to provide the desired resource ability, the intermediary server instructs a resource server to send the alternative resource instead of the requested resource to the client computer.

Providing an optimal resource to a client computer via interactive dialog

An intermediary server receives a resource request for a requested resource from a client computer. The intermediary server responds to the resource request by initiating an interactive dialog between the intermediary server and the client computer, where the interactive dialog identifies a desired resource ability of the requested resource. The intermediary server identifies, based on responses to the interactive dialog from the client computer, an alternative resource that best meets the desired resource ability, wherein the requested resource and the alternative resource are a same type of resource, and wherein the interactive dialog uses an interactive exchange that interprets interactive dialog responses from the client computer in order to identify the desired resource ability and the alternative resource that best meets the desired resource ability and then instructs a resource server to send the alternative resource to the client computer.

Financial transformation in one aspect establishes a hub and spoke network of models including at least a process model as the hub and at least components model, value driver model, applications model, solutions models as the spoke connected to the process model. A plurality of correlations is inferred among said models using daisy-chain analysis that navigate the hub and spoke network of models, and heat map is generated. Heat map analysis, application shortfall analysis, organization shortfall analysis, solution analysis, and business case analysis are performed.

System and method for financial transformation

A computer-implemented solution for managing a semantic business model is provided. In particular, one or more business area models for a business entity are obtained and transformed into intermediate model(s). Each intermediate model is represented using a substantially similar meta-modeling language. Subsequently, the semantic business model is generated by merging the set of intermediate models. In this manner, the semantic business model can be generated in a manner that reduces the overall burden on a user. The semantic business model can be provided for display to the user and/or use in performing qualitative analysis on various aspects of the business entity.

Semantic business model management

Growing community of inventors

Cupertino, CA, United States of America

Rama K T Akkiraju