Abstract: Systems and methods for reconciling a forecast are presented. A method can be used that receives a plurality of hierarchical forecast data sets. An output child data set including an index value and a status indicator representing an unprocessed state is generated. A particular parent data set forecast is identified from a parent data set. Locations for a group of one or more child data set forecasts that are children of the particular parent data set forecast are identified and accessed. A reconciliation operation is performed, a particular child data set forecast is adjusted and stored in a record, and a status indicator for the record is modified.

Abstract: Systems and methods for reconciling a forecast for a dimension based upon data that is associated with the dimension. A method can be used that includes generating a plurality of forecasts for the dimensions such that the forecast of a first dimension is generated independently of a forecast of a second dimension. The forecast of the first dimension has a constraint that is influenced by the forecast of the second dimension. A reconciliation is performed between the forecast of the first dimension and the forecast of the second dimension in order to determine how the constraint of the first dimension's forecast is to influence the first dimension's forecast.

Abstract: Systems and methods for reconciling a forecast for a dimension based upon data that is associated with the dimension. A method can be used that includes generating a plurality of forecasts for the dimensions such that the forecast of a first dimension is generated independently of a forecast of a second dimension. The forecast of the first dimension has a constraint that is influenced by the forecast of the second dimension. A reconciliation is performed between the forecast of the first dimension and the forecast of the second dimension in order to determine how the constraint of the first dimension's forecast is to influence the first dimension's forecast.

Abstract: Systems and methods are provided for handling time-stamped data. The one or more GUIs are used to define properties of an event and to associate the event with time-stamped data. The properties of the event defined using the one or more GUIs includes one or more statistical properties that indicate how the event statistically affects the time-stamped data. A time series analysis program uses the time-stamped data and the associated event to generate a mathematical model.