Enterprise planning

• US 7,693,737 B2
• Filed: 10/31/2006
• Issued: 04/06/2010
• Est. Priority Date: 07/31/2000
• Status: Expired due to Fees

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Their, Adam, Sandles, Jon M., Pearson, Duncan
• Primary Examiner(s): PATEL, JAGDISH
• Application Number:
  US11/591,129
• Publication Number:
  US 20070055604A1
• Time in Patent Office: 1,253 Days
• Field of Search: 705/1, 705 7- 10
• US Class Current: 705/7.31
• CPC Class Codes: G06Q 30/0202 Market predictions or forecasting for commercial activities
• CPC Class Codes: G06Q 40/00 Finance; Insurance; Tax strategies; Processing of corporate or income taxes
• CPC Class Codes: G06Q 40/02 Banking, e.g. interest calculation or account maintenance credit or loans G06Q40/03
• CPC Class Codes: G06Q 40/06 Asset management; Financial planning or analysis

Abstract

The invention is directed to a budget planning system that improves the accuracy and predictability of budget planning within large organizations by enabling organizations to reconcile corporate financial models and organizational targets with detailed spending forecasts. The budgeting system includes a database that is configured to store data defining a budgeting model for the organization. The model has a plurality of hierarchically arranged nodes, each node corresponding to a “contributor” that either provides forecast data or review data provided by contributors associated with lower level nodes. The system is configured to capture target data from a set of financial analysts, capture forecast data from the contributors and reconcile the target data and the forecast data according to the model.

Claims

1. A computer-based method for conducting an enterprise planning process by executing software on a networked computer system, the method comprising:

storing a model of an organization in a database accessible by the computer system, wherein the model that has been stored includes a plurality of nodes hierarchically arranged into a number of levels;

storing information, accessible by the computer system, that identifies a contributor for each node of the model;

capturing, with the computer system, forecast data from a first contributor associated with a first node within a first level of the model;

capturing, with the computer system, target data for the first node from one or more analysts that use at least one computing device that communicates with the computer system;

updating, with the computer system, a current level of the model from the first level to a second, higher level, wherein the second level includes a second node associated with a second contributor, and wherein the second node is a parent of the first node;

selectively presenting, with the computer system, the forecast data and the target data to the second contributor for reconciliation based on the current level of the model;

responsive to selectively presenting the forecast data and the target data to the second contributor, receiving, with the computer system, review information from the second contributor regarding reconciliation of the forecast data and the target data;

updating the current level, with the computer system, according to the review information;

determining, with the computer system, when the current level is a highest level of the model; and

generating, with the computer system, an enterprise planning report for the organization based on the forecast data when the forecast data is approved by a contributor associated with a root node within the highest level of the model.

2. The method of claim 1, wherein updating the current level includes incrementing the current level when the review information indicates an acceptance of the forecast data by the second contributor, and wherein updating the current level includes decrementing the current level when the review information indicates a rejection of the forecast data by the second contributor.

3. The method of claim 1, wherein capturing forecast data comprises receiving the forecast data from a remote computing device over a packet-based network.

4. The method of claim 3, wherein capturing the forecast data comprises communicating a template and a calculation engine to the remote computing device, wherein the template includes a data cube for storing the target data and the forecast data.

5. The method of claim 3, wherein the method further comprises repeating the selectively presenting the forecast data and the target data, the receiving review information, and the updating of the current level with the computer system until the current level reaches the highest level of the model.

6. A budgeting system for an organization comprising:

at least one database configured to store data defining a set of contributors, a set of analysts, and a multi-level model of an organization, wherein the model has a plurality of hierarchically arranged nodes, and wherein the data identifies a contributor for each node of the model; and

a server coupled to the at least one database,

wherein the server accesses the data within the at least one database, and is configured to capture forecast data from a first contributor associated with a first node within a first level of the model,

wherein the server is further configured to capture target data for the first node from one or more analysts in the set of analysts, the one or more analysts using at least one computing device that communicates with the computer system,

wherein the server is further configured to update a current level of the model from the first level to a second, higher level, wherein the second level includes a second node associated with a second contributor, and wherein the second node is a parent of the first node,

wherein the server is further configured to selectively present the forecast data and the target data to the second contributor for reconciliation based on the current level of the model,

wherein, responsive to selectively presenting the forecast data and the target data to the second contributor, the server is further configured to receive review information from the second contributor regarding reconciliation of the forecast data and the target data, and to update the current level according to the review information, and

wherein the server is further configured to determine when the current level is a highest level of the model, and to generate an enterprise planning report for the organization based on the forecast data when the forecast data is approved by a contributor associated with a root node within the highest level of the model.

7. The system of claim 6, wherein the server is configured to increment the current level when the review information indicates an acceptance of the forecast data by the second contributor, and wherein the server is configured to decrement the current level when the review information indicates a rejection of the forecast data by the second contributor.

8. The system of claim 6, wherein the server is configured to repeat the selectively presenting the forecast data and the target data, the receiving review information, and the updating of the current level until the current level reaches the highest level of the model.

9. A computer-readable storage medium comprising executable instructions for causing a processor of a computer system to:

store a model of an organization in a database accessible by the computer system, wherein the model that has been stored includes a plurality of nodes hierarchically arranged into a number of levels;

store information, accessible by the computer system, that identifies a contributor for each node of the model;

capture forecast data from a first contributor associated with a first node within a first level of the model;

capture target data for the first node from one or more analysts that use at least one computing device that communicates with the computer system;

update a current level of the model from the first level to a second, higher level, wherein the second level includes a second node associated with a second contributor, and wherein the second node is a parent of the first node;

selectively present the forecast data and the target data to the second contributor for reconciliation based on the current level of the model;

responsive to selectively presenting the forecast data and the target data to the second contributor, receive review information from the second contributor regarding reconciliation of the forecast data and the target data;

update the current level according to the review information;

determine when the current level is a highest level of the model; and

generate an enterprise planning report for the organization based on the forecast data when the forecast data is approved by a contributor associated with a root node within the highest level of the model.

10. The computer-readable medium of claim 9, wherein the instructions for causing the processor to update the current level comprise instructions for causing the processor to increment the current level when the review information indicates an acceptance of the forecast data by the second contributor and to decrement the current level when the review information indicates a rejection of the forecast data by the second contributor.

11. The computer-readable medium of claim 9, further comprising instructions for causing the processor to repeat the selectively presenting the forecast data and the target data, the receiving review information, and the updating of the current level until the current level reaches the highest level of the model.