Cognitive and heuristics-based emergent financial management

A method, comprising:

• obtaining, by a system comprising a processor, data from internal sources, external sources, or combinations thereof, wherein the act of obtaining data integrates details of a business capacity architecture including at least two of strategy, organization, capability, process, application, project, partner, product and customer;
• creating, by the system, data sets from the data based on determined classifications of the data, wherein the act of creating data sets and establishing relationships between the data sets is facilitated by a machine learning and reasoning component that employs classifiers comprising explicitly trained classifiers, implicitly trained classifiers or a combination of explicitly and implicitly trained classifiers that infers how the data should be organized in comparison to other data, relative rankings of the data sets, and whether the data is cross-referenced between different organizational categories;
• establishing, by the system, relationships between the data sets;
• and
• determining, by the system, a recommendation based on the relationships, wherein the recommendation is based on a hypothesis that has undergone a test process.

A non-transitory computer-readable storage device that stores executable instructions that, in response to execution, cause a system comprising a processor to perform operations, comprising:

• obtaining data related to an individual, an organization, a process, or combinations thereof, wherein the act of obtaining data integrates details of a business capacity architecture including at least two of strategy, organization, capability, process, application, project, partner, product and customer;
• creating data sets from the data based on determined classifications of the data, wherein the act of creating data sets and establishing relationships between the data sets is facilitated by a machine learning and reasoning component that employs classifiers comprising explicitly trained classifiers, implicitly trained classifiers or a combination of explicitly and implicitly trained classifiers that infers how the data should be organized in comparison to other data, relative rankings of the data sets, and whether the data is cross-referenced between different organizational categories;
• establishing relationships between the data sets;
• and
• determining a conclusion based on the relationships, wherein the conclusion is based on a hypothesis that has undergone a test process.