Systems and methods for resolving over multiple hierarchies

• US 9,892,370 B2
• Filed: 06/25/2015
• Issued: 02/13/2018
• Est. Priority Date: 06/12/2014
• Status: Active Grant

• Current Assignee: SAS Institute Incorporated
• Original Assignee: SAS Institute Incorporated
• Inventors: Richard, Victor H, Haxholdt, Christian, Good, Glenn
• Primary Examiner(s): Lu, Charles E
• Application Number:
  US14/750,886
• Publication Number:
  US 20160171089A1
• Time in Patent Office: 964 Days
• CPC Class Codes: G06F 16/9027 Trees
• CPC Class Codes: G06Q 10/00 Administration; Management
• CPC Class Codes: G06Q 10/063 Operations research, analysis or management
• CPC Class Codes: G06Q 10/067 Enterprise or organisation modelling
• CPC Class Codes: G06Q 30/0202 Market predictions or forecasting for commercial activities

Abstract

Techniques and systems for adjusting multiple hierarchies for consistency within levels of the hierarchies, using an optimization-based approach that results in an accurate projection across dimensions and levels in hierarchies. The systems and methods may include receiving data associated with nodes of two or more hierarchies, wherein nodes are associated with original node values, identifying a common level node and a target level node for each of the hierarchies, identifying a linking constraint, wherein the linking constraint includes a rule to a node from a hierarchy to make it consistent with a node from another hierarchy, applying the linking constraint to the common level node of each of the hierarchies, wherein applying the linking constraint includes generating updated common node values associated with the common level nodes, and wherein updated common node values are the same node values, applying the updated common node values to the target level node of each of the hierarchies, wherein applying the updated common node values includes generating updated target node values, and generating a resolved hierarchy using the updated target node values.

Claims

1. A computer-program product tangibly embodied in a non-transitory machine-readable storage medium, including instructions configured to cause a data processing apparatus to perform operations including:

receiving data associated with nodes of a first hierarchy and a second hierarchy separate from the first hierarchy, wherein the first and second hierarchies each include data associated with forecasting needs of an organization, and wherein the first hierarchy and second hierarchy each include a plurality of levels and one or more nodes on each level of the plurality of levels;

identifying a common level and a target level for the first hierarchy and identify a common level and a target level for the second hierarchy;

identifying a linking constraint, wherein the linking constraint includes a rule to adjust values at a node from a level in the first hierarchy to make it consistent with values at a node from a corresponding level in the second hierarchy, wherein the rule limits how values at nodes in the first and second hierarchies may be changed;

generating an optimized first hierarchy and an optimized second hierarchy using the first hierarchy, the second hierarchy, and the linking constraint, wherein generating the optimized first hierarchy and the optimized second hierarchy includes;

generating first updated common node values associated with nodes in the common level of the first hierarchy using the linking constraint and generating second updated common node values associated with nodes in the common level of the second hierarchy using the linking constraint, wherein the first updated common node values and the second updated common node values are a same set of values, and wherein the first updated common node values and second updated common node values are generated to minimize changes in first updated target node values associated with nodes in the target level of the first hierarchy and second updated target node values associated with nodes in the target level of the second hierarchy;

updating, using the first updated common node values, values associated with nodes in the target level of the first hierarchy to generate the first updated target node values and updating, using the second updated common node values, values associated with nodes in the target level of the second hierarchy to generate the second updated target node values; and

generating a resolved hierarchy using the optimized first hierarchy and the optimized second hierarchy, wherein the resolved hierarchy includes more accurate data for forecasting the needs of the organization as compared to the first hierarchy and the second hierarchy.

2. The computer-program product of claim 1, wherein the updated common node values have a same value as a value of one of the nodes in the common level before the linking constraint is applied to the common level node of each of the hierarchies.

3. The computer-program product of claim 1, further comprising instructions configured to cause the data processing apparatus to perform operations including:

computing a change in a target node value associated with each of the first and second hierarchies;

determining that the change in the target node value associated with one or more of the first and second hierarchies are above a predetermined threshold; and

re-applying the linking constraint to the common level node of each of the first and second hierarchies, wherein applying the linking constraint includes generating alternative common node values associated with the nodes in the common level, wherein the alternative common node values are a same set of node values, and wherein the alternative common node values are different than the updated target node values.

4. The computer-program product of claim 1, wherein a node in the target level of a hierarchy includes a most accurate data of all nodes within the hierarchy.

5. The computer-program product of claim 1, wherein applying a linking constraint to common level nodes forces common level node values associated with the common level nodes to be the same value.

6. The computer-program product of claim 1, further comprising instructions configured to cause the data processing apparatus to perform operations including:

computing disaggregation factors for each of the nodes of two or more hierarchies; and

determining, using the disaggregation factors for a parent node in a hierarchy, whether a set of child nodes of the parent node comply with flow conservation properties, wherein determining whether a set of child nodes of the parent node comply with flow conservation properties includes determining if a sum of the node values of the child nodes equals the node value of the parent node.

7. The computer-program product of claim 6, wherein determining that the sum of the node values of the child nodes does not equal the node value of the parent node includes comparing the difference between the sum of the node values of the child nodes and the node value of the parent node to a predetermined threshold.

8. The computer-program product of claim 6, further comprising instructions configured to cause the data processing apparatus to perform operations including:

determining that the set of child nodes of the parent node comply with flow conservation properties if the difference between the sum of the node values of the child nodes and the node value of the parent node are less than the predetermined threshold.

9. A computing device, comprising:

one or more processors; and

a memory having instructions stored thereon, which when executed by the one or more processors, cause the computing device to perform operations including;

receiving data associated with nodes of a first hierarchy and a second hierarchy separate from the first hierarchy, wherein the first and second hierarchies each include data associated with forecasting needs of an organization, and wherein the first hierarchy and second hierarchy each include a plurality of levels and one or more nodes on each level of the plurality of levels;

identifying a common level and a target level for the first hierarchy and identify a common level and a target level for the second hierarchy;

identifying a linking constraint, wherein the linking constraint includes a rule to adjust values at a node from a level in the first hierarchy to make it consistent with values at a node from a corresponding level in the second hierarchy, wherein the rule limits how values at nodes in the first and second hierarchies may be changed;

generating an optimized first hierarchy and an optimized second hierarchy using the first hierarchy, the second hierarchy, and the linking constraint, wherein generating the optimized first hierarchy and the optimized second hierarchy includes;

generating first updated common node values associated with nodes in the common level of the first hierarchy and generating second updated common node values associated with nodes in the common level of the second hierarchy, wherein the first updated common node values and the second updated common node values are a same and wherein the first updated common node values and second updated common node values are generated to minimize changes in first updated target node values associated with nodes in the target level of the first hierarchy and second updated target node values associated with nodes in the target level of the second hierarchy;

updating, using the first updated common node values, values associated with nodes in the target level of the first hierarchy to generate the first updated target node values and updating, using the second updated common node values, values associated with nodes in the target level of the second hierarchy to generate the second updated target node values; and

generating a resolved hierarchy using the optimized first hierarchy and the optimized second hierarchy, wherein the resolved hierarchy includes more accurate data for forecasting the needs of the organization as compared to the first hierarchy and the second hierarchy.

10. The computing device of claim 9, wherein the updated common node values have a same value as a value of one of the nodes in the common level before the linking constraint is applied to the common level node of each of the hierarchies.

11. The computing device of claim 9, further comprising instructions, which when executed by the one or more processors, cause the computing device to perform operations including:

computing a change in a target node value associated with each of the first and second hierarchies;

determining that the change in the target node value associated with one or more of the first and second hierarchies are above a predetermined threshold; and

re-applying the linking constraint to the common level node of each of the first and second hierarchies, wherein applying the linking constraint includes generating alternative common node values associated with the nodes in the common level, wherein the alternative common node values are a same set of node values, and wherein the alternative common node values are different than the updated target node values.

12. The computing device of claim 9, wherein a node in the target level of a hierarchy includes a most accurate data of all nodes within the hierarchy.

13. The computing device of claim 9, wherein applying a linking constraint to common level nodes forces common level node values associated with the common level nodes to be the same value.

14. The computing device of claim 9, further comprising instructions, which when executed by the one or more processors, cause the computing device to perform operations including:

computing disaggregation factors for each of the nodes of two or more hierarchies; and

determining, using the disaggregation factors for a parent node in a hierarchy, whether a set of child nodes of the parent node comply with flow conservation properties, wherein determining whether a set of child nodes of the parent node comply with flow conservation properties includes determining if a sum of the node values of the child nodes equals the node value of the parent node.

15. The computing device of claim 14, wherein determining that the sum of the node values of the child nodes does not equal the node value of the parent node includes comparing the difference between the sum of the node values of the child nodes and the node value of the parent node to a predetermined threshold.

16. The computing device of claim 15, further comprising instructions, which when executed by the one or more processors, cause the computing device to perform operations including:

determining that the set of child nodes of the parent node comply with flow conservation properties if the difference between the sum of the node values of the child nodes and the node value of the parent node are less than the predetermined threshold.

17. A computer implemented method, comprising:

receiving data associated with nodes of a first hierarchy and a second hierarchy separate from the first hierarchy, wherein the first and second hierarchies each include data associated with forecasting needs of an organization, and wherein the first hierarchy and second hierarchy each include a plurality of levels and one or more nodes on each level of the plurality of levels;

identifying a common level and a target level for the first hierarchy and identify a common level and a target level for the second hierarchy;

identifying a linking constraint, wherein the linking constraint includes a rule to adjust values at a node from a level in the first hierarchy to make it consistent with values at a node from a corresponding level in the second hierarchy, wherein the rule limits how values at nodes in the first and second hierarchies may be changed;

generating an optimized first hierarchy and an optimized second hierarchy using the first hierarchy, the second hierarchy, and the linking constraint, wherein generating the optimized first hierarchy and the optimized second hierarchy includes;

generating first updated common node values associated with nodes in the common level of the first hierarchy and generating second updated common node values associated with nodes in the common level of the second hierarchy, wherein the first updated common node values and the second updated common node values are a same values, and wherein the first updated common node values and second updated common node values are generated to minimize changes in first updated target node values associated with nodes in the target level of the first hierarchy and second updated target node values associated with nodes in the target level of the second hierarchy;

updating, using the first updated common node values, values associated with nodes in the target level of the first hierarchy to generate the first updated target node values and updating, using the second updated common node values, values associated with nodes in the target level of the second hierarchy to generate the second updated target node values; and

generating a resolved hierarchy using the optimized first hierarchy and the optimized second hierarchy, wherein the resolved hierarchy includes more accurate data for forecasting the needs of the organization as compared to the first hierarchy and the second hierarchy.

18. The method of claim 17, wherein the updated common node values have a same value as a value of one of the nodes in the common level before the linking constraint is applied to the common level node of each of the hierarchies.

19. The method of claim 17, further comprising:

computing a change in target node value associated with each of the first and second hierarchies;

determining that the change in the target node value associated with one or more of the first and second hierarchies are above a predetermined threshold; and

re-applying the linking constraint to the common level node of each of the first and second hierarchies, wherein applying the linking constraint includes generating alternative common node values associated with the nodes in the common level, wherein the alternative common node values are a same set of node values, and wherein the alternative common node values are different than the updated target node values.

20. The method of claim 17, wherein a node in the target level of a hierarchy includes a most accurate data of all nodes within the hierarchy.

21. The method claim 17, wherein applying a linking constraint to common level nodes forces common level node values associated with the common level nodes to be the same value.

22. The method of claim 17, further comprising:

computing disaggregation factors for each of the nodes of two or more hierarchies; and

determining, using the disaggregation factors for a parent node in a hierarchy, whether a set of child nodes of the parent node comply with flow conservation properties, wherein determining whether a set of child nodes of the parent node comply with flow conservation properties includes determining if a sum of the node values of the child nodes equals the node value of the parent node.

23. The computer-program product of claim 22, wherein determining that the sum of the node values of the child nodes does not equal the node value of the parent node includes comparing the difference between the sum of the node values of the child nodes and the node value of the parent node to a predetermined threshold.

24. The computer-program product of claim 22, further comprising:

determining that the set of child nodes of the parent node comply with flow conservation properties if the difference between the sum of the node values of the child nodes and the node value of the parent node are less than the predetermined threshold.