System and method for customizable granularity for forecasts in user interface drilldown

A non-transitory machine-readable medium having instructions stored therein, which when executed by a processor, causing the processor to perform operations, the operations comprising:

• querying for entity data of a user from a first data source;
• displaying a display panel in a user interface (UI), the display panel comprising measurement metrics for an account entity of the user from the entity data of the first data source;
• determining mode chaining information that specifies a chain of entity relationships between a plurality of entities in the entity data, wherein the relationships include one-to-one or one-to-many relationships, wherein the mode chaining information includes a sequence of modes connected through mode references, the sequence of modes specifies a customizable sequence of a plurality of customizable modes;
• and
• determining forecast information corresponding to the measurement metrics for the plurality of entities of the user from a second data source, the forecast information including entity-based forecast values following the chain of entity relationships between the plurality of entities in the entity data;
• displaying the forecast information as entity-based forecast values in the UI based on the mode chaining information, wherein the entity-based forecast values comprise corresponding actionable drill downs of forecast values for the plurality of entities of the user to be displayed in the UI for customizable forecast granularities.

A system comprising:

• one or more processors;
• and
• a non-transitory storage medium comprising executable instructions, which when executed by the one or more processors, causes the one or more processors to perform operations, the operations comprising:
• querying for entity data of a user from a first data source;
• displaying a display panel in a user interface (UI), the display panel comprising measurement metrics for an account entity of the user from the entity data of the first data source;
• determining mode chaining information that specifies a chain of entity relationships between a plurality of entities in the entity data, wherein the relationships include one-to-one or one-to-many relationships, wherein the mode chaining information includes a sequence of modes connected through mode references, the sequence of modes specifies a customizable sequence of a plurality of customizable modes;
• and
• determining forecast information corresponding to the measurement metrics for the plurality of entities of the user from a second data source, the forecast information including entity-based forecast values following the chain of entity relationships between the plurality of entities in the entity data;
• displaying the forecast information as entity-based forecast values in the UI based on the mode chaining information, wherein the entity-based forecast values comprise corresponding actionable drill downs of forecast values for the plurality of entities of the user to be displayed in the UI for customizable forecast granularities.