Abstract: A computer-implemented decision management process for evaluating a customer having more than one account. An iterative function, such as an iterative decision tree, is provided to evaluate the customer and each of the accounts interactively and interchangeably in a single pass. The iterative function has virtual attributes for accessing customer data and/or account data. The process iterates through the iterative function in accordance with the number of accounts of the customer.

Abstract: A computer implemented process including (a) storing first and second strategy versions for application by a computer-implemented decision management system, the second strategy version being an edited version of the first strategy version and including a function; (b) storing first and second function versions of the function; (c) selecting the stored, second strategy version with one of the first and second function versions; and (d) applying the selected second strategy version.

Abstract: A computer-implemented decision management system which provides qualitative client assessment via point in time simulation. More specifically, the decision management system (a) simulates the effect of a strategy by applying the strategy to client data, and (b) tracks what type of client traveled through a respective decision point in the strategy during the simulation. Simulation parameters can be selected without technical intervention via, for example, a GUI and a relational data model. Such parameters can include which customers and which client data sample will be used for the simulation, and which inbound events will trigger the strategy. Moreover, detailed and aggregate results can be consolidated to determine expected results from the simulated strategies, and traditional and OLAP reporting facilities can be applied to analyze/view the consolidated results.

Abstract: A computer-implemented rules based decision management system which is cross-platform, cross-industry and cross-function. The decision management system has a software architecture which includes a common code layer, a processing platform layer and a data architecture layer. The common code layer includes a common code kernel simultaneously operable on first and second hardware platforms which are different from each other, and provides software processing to interpret and apply the strategies. The processing platform layer includes a first software module supporting a processing mode for the first hardware platform, and a second software module supporting a processing mode for the second hardware platform. The data architecture layer includes a first data module supporting data storage and access by the first software module, and a second data module supporting data storage and access by the second software module.

Abstract: An apparatus and method for automatically optimizing a strategy of a decision management system. More specifically, a computer-implemented decision management system applies a strategy to determine actions to be taken, monitors performance based on the taken actions, and refines the strategy in accordance with the monitored performance. An end user of the system selects a part of the strategy for optimization, and selects criteria for optimizing the selected part of the strategy. The decision management system then automatically optimizes the selected part of the strategy in accordance with the selected criteria. The end user can decide whether or not to implement the optimized strategy in production.

Abstract: A computer-implemented decision management system which provides qualitative client assessment via point in time simulation. More specifically, the decision management system (a) simulates the effect of a strategy by applying the strategy to client data, and (b) tracks what type of client traveled through a respective decision point in the strategy during the simulation. Simulation parameters can be selected without technical intervention via, for example, a GUI and a relational data model. Such parameters can include which customers and which client data sample will be used for the simulation, and which inbound events will trigger the strategy. Moreover, detailed and aggregate results can be consolidated to determine expected results from the simulated strategies, and traditional and OLAP reporting facilities can be applied to analyze/view the consolidated results.

Abstract: An apparatus and method for automatically optimizing a strategy of a decision management system. More specifically, a computer-implemented decision management system applies a strategy to determine actions to be taken, monitors performance based on the taken actions, and refines the strategy in accordance with the monitored performance. An end user of the system selects a part of the strategy for optimization, and selects criteria for optimizing the selected part of the strategy. The decision management system then automatically optimizes the selected part of the strategy in accordance with the selected criteria. The end user can decide whether or not to implement the optimized strategy in production.

Abstract: A computer-implemented decision management system which provides qualitative client assessment via point in time simulation. More specifically, the decision management system (a) simulates the effect of a strategy by applying the strategy to client data, and (b) tracks what type of client traveled through a respective decision point in the strategy during the simulation. Simulation parameters can be selected without technical intervention via, for example, a GUI and a relational data model. Such parameters can include which customers and which client data sample will be used for the simulation, and which inbound events will trigger the strategy. Moreover, detailed and aggregate results can be consolidated to determine expected results from the simulated strategies, and traditional and OLAP reporting facilities can be applied to analyze/view the consolidated results.

Abstract: A computer-implemented, software based, decision management system which automatically searches for a respective strategy component through a strategy to identify where the strategy component is being used in the strategy, and to determine the strategy component's inter-relationships in the strategy. For example, an end user of the system selects a respective strategy component to be searched. A plurality of selectable inquiries are then automatically presented to the end user, where the plurality of selectable inquiries are context sensitive to correspond to the selected strategy component. The end user then selects a respective inquiry. Then, the system automatically searches for the selected strategy component through the strategy in accordance with the selected inquiry to identify where the strategy component is being used in the strategy. The strategy can be searched, for example, by analyzing linked tables of a relational data model for implementing the strategy.

Abstract: A computer-implemented rules based decision management system which is cross-platform, cross-industry and cross-function. The decision management system has a software architecture which includes a common code layer, a processing platform layer and a data architecture layer. The common code layer includes a common code kernel simultaneously operable on first and second hardware platforms which are different from each other, and provides software processing to interpret and apply the strategies. The processing platform layer includes a first software module supporting a processing mode for the first hardware platform, and a second software module supporting a processing mode for the second hardware platform. The data architecture layer includes a first data module supporting data storage and access by the first software module, and a second data module supporting data storage and access by the second software module.

Abstract: A computer-implemented, software based, decision management system which automatically searches for a respective strategy component through a strategy to identify where the strategy component is being used in the strategy, and to determine the strategy component's inter-relationships in the strategy. For example, an end user of the system selects a respective strategy component to be searched. A plurality of selectable inquiries are then automatically presented to the end user, where the plurality of selectable inquiries are context sensitive to correspond to the selected strategy component. The end user then selects a respective inquiry. Then, the system automatically searches for the selected strategy component through the strategy in accordance with the selected inquiry to identify where the strategy component is being used in the strategy. The strategy can be searched, for example, by analyzing linked tables of a relational data model for implementing the strategy.

Abstract: A computer-implemented rules based decision management system which is cross-platform, cross-industry and cross-function. The decision management system has a software architecture which includes a common code layer, a processing platform layer and a data architecture layer. The common code layer includes a common code kernel simultaneously operable on first and second hardware platforms which are different from each other, and provides software processing to interpret and apply the strategies. The processing platform layer includes a first software module supporting a processing mode for the first hardware platform, and a second software module supporting a processing mode for the second hardware platform. The data architecture layer includes a first data module supporting data storage and access by the first software module, and a second data module supporting data storage and access by the second software module.

Abstract: A computer implemented decision management system which provides strategy versioning. The system (a) creates different strategy versions, (b) selects, without technical intervention, a respective strategy version of the created strategy versions, (c) applies, without technical intervention, the selected strategy version to determine interaction strategies, (d) monitors performance based on the determined interaction strategies, and (e) refines the selected strategy version in accordance with the monitored performance. To select and apply strategy versions without technical intervention, a GUI is used to enter, edit and select strategy versions at a desktop. From the GUI, the strategy versions are stored in relational tables within a relational data model. A versioning level is interjected between a system level and a segment level in a definition hierarchy, so that each strategy can be referenced as being a specific strategy version.

Abstract: A computer implemented decision management system which provides strategy versioning. The system (a) creates different strategy versions, (b) selects, without technical intervention, a respective strategy version of the created strategy versions, (c) applies, without technical intervention, the selected strategy version to determine interaction strategies, (d) monitors performance based on the determined interaction strategies, and (e) refines the selected strategy version in accordance with the monitored performance. To select and apply strategy versions without technical intervention, a GUI is used to enter, edit and select strategy versions at a desktop. From the GUI, the strategy versions are stored in relational tables within a relational data model. A versioning level is interjected between a system level and a segment level in a definition hierarchy, so that each strategy can be referenced as being a specific strategy version.

Abstract: A computer-implemented decision management system which provides qualitative client assessment via point in time simulation. More specifically, the decision management system (a) simulates the effect of a strategy by applying the strategy to client data, and (b) tracks what type of client traveled through a respective decision point in the strategy during the simulation. Simulation parameters can be selected without technical intervention via, for example, a GUI and a relational data model. Such parameters can include which customers and which client data sample will be used for the simulation, and which inbound events will trigger the strategy. Moreover, detailed and aggregate results can be consolidated to determine expected results from the simulated strategies, and traditional and OLAP reporting facilities can be applied to analyze/view the consolidated results.

Abstract: A rules based decision management system using online analytical processing (OLAP) technology for dynamic assessment of strategy results. Generally, a rules based decision management system applies strategies which produce results. The results are aggregated over time, typically in accordance with values of a discrete dimension and ranges of a continuous dimension, to prepare for the application of OLAP technology. Date stamping can be used so that, when aggregating the results, different values and different ranges can be valid for different periods of time. OLAP technology is then applied to the aggregated results, to evaluate the applied strategies.

Abstract: A computer-implemented decision management system which provides qualitative client assessment via point in time simulation. More specifically, the decision management system (a) simulates the effect of a strategy by applying the strategy to client data, and (b) tracks what type of client traveled through a respective decision point in the strategy during the simulation. Simulation parameters can be selected without technical intervention via, for example, a GUI and a relational data model. Such parameters can include which customers and which client data sample will be used for the simulation, and which inbound events will trigger the strategy. Moreover, detailed and aggregate results can be consolidated to determine expected results from the simulated strategies, and traditional and OLAP reporting facilities can be applied to analyze/view the consolidated results.

Abstract: A software-based decision management system that allows an organization to monitor and evaluate client performance data relating to client interactions with the organization, and to appropriately modify organizational strategies in accordance with the performance data. More specifically, the system (a) applies different strategies to different categories of clients of the organization, (b) tracks the performance of the clients as a result of the applied strategies, and (c) refines the applied strategies based on the tracked performance to increase client value over time to the organization. For example, in a specific embodiment, clients are assigned into categories and test groups to define a data structure conceptually representable as a matrix having first and second axes with the categories on the first axis and the test groups on the second axis, the intersection of each category and test group in the matrix defining a test cell. Different strategies are applied to clients within different test cells.