Flexible baselines in an operating plan data aggregation system

• US 10,713,301 B2
• Filed: 04/26/2005
• Issued: 07/14/2020
• Est. Priority Date: 04/26/2004
• Status: Active Grant

• Current Assignee: Ignite Enterprise Software Solutions, Inc. (Infonow Corporation)
• Original Assignee: Right90, Inc. (ESW Capital, LLC)
• Inventors: Orumchian, Kim, Stabenow, Art, Skelton, Dean, Petiot, David
• Primary Examiner(s): Nigh, James D
• Application Number:
  US11/116,129
• Publication Number:
  US 20060080294A1
• Time in Patent Office: 5,558 Days
• Field of Search: 705 26, 705 50
• CPC Class Codes: G06F 16/2228 Indexing structures
• CPC Class Codes: G06F 16/254 Extract, transform and load [ETL] procedures, e.g. ETL data flows in data warehouses
• CPC Class Codes: G06F 16/283 Multi-dimensional databases or data warehouses, e.g. MOLAP or ROLAP
• CPC Class Codes: G06F 16/90335 Query processing
• CPC Class Codes: G06F 2216/03 Data mining
• CPC Class Codes: G06Q 10/04 Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem" market predictions or forecasting for commercial activities G06Q30/0202
• CPC Class Codes: G06Q 10/063 Operations research, analysis or management
• CPC Class Codes: G06Q 10/0631 Resource planning, allocation, distributing or scheduling for enterprises or organisations
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G06Q 30/0202 Market predictions or forecasting for commercial activities
• CPC Class Codes: G06Q 30/06 Buying, selling or leasing transactions
• CPC Class Codes: G06Q 40/04 Trading; Exchange, e.g. stocks, commodities, derivatives or currency exchange
• CPC Class Codes: G06Q 40/06 Asset management; Financial planning or analysis
• CPC Class Codes: Y10S 707/99933 Query processing, i.e. searching
• CPC Class Codes: Y10S 707/99956 File allocation

Abstract

In an embodiment, the a method is provided. The method includes receiving forecast data in a database with an associated window value. The method also includes accessing data based on associated window values. The method further includes comparing the data accessed based on associated window values to other data.

Claims

1. A computer implemented method of maintaining information in multiple OLAP cubes data structures of a database of a computer and propagating information in real-time through the OLAP cubes to reduce delays in generating an updated baseline forecast, comprising:

for each of multiple organizations, dedicating an instance of one of the OLAP cubes to each of the organizations;

for each of the multiple organizations, performing by the computer programmed with code stored in a memory and when the code is executed by a processor of the computer to configure the computer into a machine for;

partitioning each of the OLAP cubes of the database into at least a first partition and a second partition;

receiving a set of initial forecast data representing a prediction or judgment for a future event by the computer;

for each organization, storing the forecast data in the first partition of the OLAP cube of the database dedicated to the organization;

incorporating the set of initial forecast data into the database through the instance of the OLAP cube for analytical processing dedicated to the organization;

processing the initial forecast data by the computer to determine the prediction or judgment for the future event and generating an initial baseline forecast from information stored in the database, including the initial forecast data;

receiving updates to the information stored in the database on an asynchronous or random basis, the updates including changes to the initial forecast data and comments about the initial forecast data;

for each organization, updating the first partition of the OLAP cube of the computer database every time T1, wherein T1 is an amount of time;

identifying some updated information as private and remaining updated information is non-private;

identifying some updated information as allowed and the remaining updated information as denied;

processing the updates by the computer to incorporate the non-private and allowed updates into the database, the database including updates to the initial forecast data for any changes to the initial forecast data;

associating any comments about the initial forecast data including any comments about the updated forecast data, with the forecast data;

propagating the processed updates, the received comments, and the received changes to the initial forecast data in essentially real-time throughout the database through the instance of the OLAP cube dedicated to the organization to (i) associate the received comments and changes with the forecast information and (ii) asynchronously update the baseline forecast with the received updated non-private information changes of the forecast information in essentially real-time;

associating the received comments and changes with the forecast information;

asynchronously updating the baseline forecast with the received changes of the forecast information in essentially real-time;

for each organization, storing the updates in the second partition of the OLAP cube dedicated to the organization;

for each organization, updating the second partition of the OLAP cube dedicated to the organization every time T2, wherein T2 is an amount of time and T2 is less than T1 for each organization; and

generating an updated baseline forecast from the updated OLAP cube and the initial baseline forecast.

2. The method of claim 1, further comprising for each organization:

comparing data of the baseline forecast with data of the updated baseline forecast;

analyzing differences between the data of the baseline forecast and the data of the updated baseline forecast; and

presenting the differences to a user.

3. The method of claim 1, further comprising for each organization:

receiving a request for a private baseline from a user; and

generating the OLAP cube dedicated to the organization a private baseline forecast from the database and the baseline forecast in response to the received request, extracting the private baseline forecast from the database, the private baseline forecast derived from the baseline forecast.

4. The method of claim 1, further comprising for each organization:

receiving a request for a private baseline from a user; and

extracting the private baseline forecast from the database, the private baseline forecast derived from the updated baseline forecast.

5. The method of claim 1, further comprising for each organization:

segregating at least one of forecast data and baseline data based on a customer or user identity; and

receiving forecast information from users associated with a first customer identity and with different users associated with a second customer identity.

6. The method of claim 1, further including for each organization notifying a user of changes in a set of watched data points responsive to the propagating and receiving updates.

7. The method of claim 3, wherein, for each organization, each user has a set of forecast targets that are associated with the user'"'"'s particular responsibilities in a company for use in generating personal private forecasts, shared private, forecasts, and optionally public forecasts.

8. The method of claim 7, wherein, for each organization, a first user is a CEO user and the CEO user has analyst forecast, a CEO personal target forecast, and internal forecast targets associated with the CEO user.

9. The method of claim 3, wherein data are stored in the database and processed by the OLAP cube to efficiently generate updated private baselines.

10. The method of claim 8, wherein, for each organization, a second user is a vice-president of sales user and the vice-president of sales user has an official target forecast, a vice-president of sales personal forecast target, a sales manager forecast target, and a sales representative forecast target, association with the Vice-President of sales user.

11. The method of claim 10, wherein, for each organization, a third user is a regional sales manager user and the regional sales manager user has an official target forecast, and a regional sales manager personal forecast target, associated with the regional sales manager user.

12. The method of claim 3, wherein, for each organization, the private baseline from a user includes a CEO private baseline for a company, and the CEO private baseline is generated using a CEO personal forecast target.

13. The method of claim 3, wherein, for each organization, the private baseline from a user includes a Vice-President of sales private baseline for a company, and the Vice-President of sales private baseline is generated using a Vice-President of sales personal forecast target.

14. The method of claim 3, wherein, for each organization, the private baseline from a user includes a regional sales manager private baseline for a company, and the regional sales manager private baseline is generated using a regional sales manager personal forecast target.

15. The method of claim 3, wherein, for each organization, the private baseline from a user includes a company private baseline for the company, and the company private baseline is generated using a combination of:

(i) an analyst forecast target, (ii) an internal target forecast, and (iii) an official target regional sales manager forecast target.

16. The method of claim 3, wherein, for each organization, the private baseline from a user includes a sales private baseline for the company, and the sales baseline is generated using a combination of:

(i) a sales manager forecast target, (ii) a sales representative target forecast, and (iii) an official target regional sales manager forecast target.

17. The method of claim 1, further comprising, for each organization, issuing an alert to at least one user based on a change of an identified amount from a baseline forecast.

18. The method of claim 3, further comprising, for each organization, issuing an alert to at least one user based on a change of an identified amount from a private baseline forecast.

19. A system for maintaining information in multiple OLAP cubes data structures of a database of a computer and propagating information in real-time through the OLAP cubes to reduce delays in generating an updated baseline forecast, comprising:

a processor, and

a memory, coupled to the processor, having code stored therein and when the code is executed by the processor cause the processor to configure the computer into a machine that performs the steps of;

for each of multiple organizations, dedicating an instance of one of the multiple OLAP cubes to store data in accordance with the instance of the OLAP cube; and

for each of the multiple organizations;

partitioning each of the OLAP cubes of the database into at least a first partition and a second partition;

receiving a set of initial forecast data representing a prediction or judgment for future event by the computer;

for each organization, storing the forecast data in the first partition of the OLAP cube of the database dedicated to the organization;

incorporating the set of initial forecast data into the database through the instance of the OLAP cube for analytical processing dedicated to the organization;

determining the prediction or judgment for the future event from the initial forecast data;

extracting an initial baseline forecast from the determined prediction or judgment for the future event initial forecast data and database;

receiving updates to the information stored in the database on an asynchronous or random basis, the updates including changes to the initial forecast data and comments about the initial forecast data;

for each organization, updating the first partition of the OLAP cube of the computer database every time T1, wherein T1 is an amount of time;

identifying some updated information as private and remaining updated information is non-private;

identifying some updated information as allowed and the remaining updated information as denied;

processing the updates by the computer to incorporate only the non-private and allowed updates into the database, the database including updates to the initial forecast data for any changes to the initial forecast data;

associating any comments about the initial forecast data including any comments about the updated forecast data, with the forecast data;

propagating the processed updates, the received comments, and the received changes to the initial forecast data in essentially real-time throughout the database through the instance of the OLAP cube dedicated to the organization to (i) associate the received comments and changes with the forecast information and (ii) asynchronously update the baseline forecast with the received updated non-private information changes of the forecast information in essentially real-time;

associating the received comments and changes with the forecast information;

asynchronously updating the baseline forecast with the received changes of the forecast information in essentially real-time;

for each organization, storing the updates in the second partition of the OLAP cube dedicated to the organization;

for each organization, updating the second partition of the OLAP cube dedicated to the organization every time T2, wherein T2 is an amount of time and T2 is less than T1 for each organization; and

extracting an updated baseline forecast from the database that is updated and the initial baseline forecast.

20. The system of claim 19, wherein the memory further comprises code executable for each of the organizations by the processor for:

comparing data of the baseline forecast with data of the updated baseline forecast;

analyzing differences between the data of the baseline forecast and the data of the updated baseline forecast; and

presenting the differences to a user.

21. The system of claim 19, wherein the memory further comprises code executable for each of the organizations by the processor for:

receiving a request for a private baseline from a user; and

extracting the private baseline forecast from the database, the private baseline forecast derived from the baseline forecast.

22. The system of claim 19, wherein the memory further comprises code executable for each of the organizations by the processor for:

receiving a request for a private baseline from a user; and

extracting the private baseline forecast from the database, the private baseline forecast derived from the updated baseline forecast.

23. The system of claim 19, wherein the database includes an information database, the system further comprising:

an identification server coupled to the information database; and

a first client device coupled to a first organization database, and a second client device coupled to a second organization database, the first and second organization databases being either logically or physically different portions of the information database.

24. The system of claim 23, wherein the memory further comprises code executable by the processor for:

submitting information to the user interface from a remote location.

25. The system of claim 19, wherein the memory further comprises code executable for each of the organizations by the processor for:

receiving a request for a private baseline from a user;

generating using the instance of the OLAP cube for the organization a private baseline forecast from, the database and the baseline forecast in response to the received request; and

extracting the private baseline forecast from the database, wherein the private baseline forecast is derived from the baseline forecast.

26. The system of claim 25, wherein, for each organization, each user has a set of forecast targets that are associated with the user'"'"'s particular responsibilities in a company for use in generating personal private forecasts, shared private, forecasts, and optionally public forecasts.

27. The system of claim 26, wherein, for each organization, a first user is a CEO user and the CEO user has analyst forecast, a CEO personal target forecast, and internal forecast targets associated with the CEO user.

28. The system of claim 25, wherein, for each organization, data are stored in the database and processed by the instance of the OLAP cube so that updated private baselines are efficiently generated.

29. The system of claim 27, wherein, for each organization, a second user is a vice-president of sales user and the vice-president of sales user has an official target forecast, a vice-president of sales personal forecast target, a sales manager forecast target, and a sales representative forecast target, association with the Vice-President of sales user.

30. The system of claim 29, wherein, for each organization, a third user is a regional sales manager user and the regional sales manager user has an official target forecast, and a regional sales manager personal forecast target, associated with the regional sales manager user.

31. The system of claim 25, wherein, for each organization, the private baseline from a user includes a CEO private baseline for a company, and the CEO private baseline is generated using a CEO personal forecast target.

32. The system of claim 25, wherein, for each organization, the private baseline from a user includes a Vice-President of sales private baseline for a company, and the Vice-President of sales private baseline is generated using a Vice-President of sales personal forecast target.

33. The system of claim 25, wherein, for each organization, the private baseline from a user includes a regional sales manager private baseline for the organization, and the regional sales manager private baseline is generated using a regional sales manager personal forecast target.

34. The system of claim 25, wherein, for each organization, the private baseline from a user includes a company private baseline for the organization, and the company private baseline is generated using a combination of:

(i) an analyst forecast target, (ii) an internal target forecast, and (iii) an official target regional sales manager forecast target.

35. The system of claim 25, wherein, for each organization, the private baseline from a user includes a sales private baseline for the organization, and the sales baseline is generated using a combination of:

(i) a sales manager forecast target, (ii) a sales representative target forecast, and (iii) an official target regional sales manager forecast target.

36. The system of claim 19, further comprising issuing an alert to at least one user based on a change of an identified amount from a baseline forecast.

37. The system of claim 25, further comprising issuing an alert to at least one user based on a change of an identified amount from a private baseline forecast.

38. A non-transitory, computer readable medium comprising instructions stored therein to maintain information in multiple OLAP cubes of a database of a computer and propagating information in real-time through the OLAP cubes to reduce delays in generating an updated baseline forecast, when the instructions are executed by a processor configure a computer that includes the processor into a machine to perform the steps of:

partitioning each of the OLAP cubes of the database into at least a first partition and a second partition;

receiving a set of initial forecast data representing a prediction or judgment for a future event by the computer;

for each organization, storing the forecast data in the first partition of the OLAP cube of the database dedicated to the organization;

incorporating the set of initial forecast data into the database through the instance of the OLAP cube for analytical processing dedicated to the organization;

processing the initial forecast data by the computer to determine the prediction or judgment for the future event and generating an initial baseline forecast from information stored in the database, including the initial forecast data;

receiving updates to the information stored in the database on an asynchronous or random basis, the updates including changes to the initial forecast data and comments about the initial forecast data;

for each organization, updating the first partition of the OLAP cube of the computer database every time T1, wherein T1 is an amount of time;

identifying some updated information as private and remaining updated information is non-private;

identifying some updated information as allowed and the remaining updated information as denied;

processing the updates by the computer to incorporate only the non-private and allowed updates into the database, the database including updates to the initial forecast data for any changes to the initial forecast data;

associating any comments about the initial forecast data including any comments about the updated forecast data, with the forecast data;

propagating the processed updates, the received comments, and the received changes to the initial forecast data in essentially real-time throughout the database through the instance of the OLAP cube dedicated to the organization to (i) associate the received comments and changes with the forecast information and (ii) asynchronously update the baseline forecast with the received updated non-private information changes of the forecast information in essentially real-time;

associating the received comments and changes with the forecast information;

asynchronously updating the baseline forecast with the received changes of the forecast information in essentially real-time;

for each organization, storing the updates in the second partition of the OLAP cube dedicated to the organization;

for each organization, updating the second partition of the OLAP cube dedicated to the organization every time T2, wherein T2 is an amount of time and T2 is less than T1 for each organization; and

generating an updated baseline forecast from the updated OLAP cube and the initial baseline forecast.