Adaptive analytics system and method of using same

• US 10,108,926 B2
• Filed: 04/04/2007
• Issued: 10/23/2018
• Est. Priority Date: 05/11/2006
• Status: Active Grant

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Helal, Robert
• Primary Examiner(s): Delich, Stephanie Z
• Application Number:
  US11/732,568
• Publication Number:
  US 20080249815A1
• Time in Patent Office: 4,220 Days
• Field of Search: None
• CPC Class Codes: G06Q 10/06 Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
• CPC Class Codes: G06Q 10/06311 Scheduling, planning or task assignment for a person or group
• CPC Class Codes: G06Q 10/06375 Prediction of business process outcome or impact based on a proposed change
• CPC Class Codes: G06Q 10/0639 Performance analysis of employees; Performance analysis of enterprise or organisation operations
• CPC Class Codes: G06Q 10/06398 Performance of employee with respect to a job function
• CPC Class Codes: G06Q 10/10 Office automation; Time management
• CPC Class Codes: G06Q 30/0206 Price or cost determination based on market factors

Abstract

An adaptive analytics system comprises a set of analytic type templates representing analytic types, each analytic type template including predetermined report items for generating a report for a respective analysis type; and an analytic framework for defining relations among the analytic types. The relations provides analytic paths for navigating reports.

Claims

1. A computer-implemented method for an adaptive analytics application to create an analytic framework for use in analysing business intelligence (BI) information stored in a database system, the adaptive analytics application including an item handler module, an analytic path module, and a report module, the computer-implemented method comprising:

receiving, by the adaptive analytics application, a definition of a new role for analysing the BI information stored in the database system, wherein the definition of the new role specifies BI information requirements that are specific to the new role;

receiving, by the adaptive analytics application, selection of one or more analytic type templates for analysing the BI information, wherein each analytic type template specifies a layout of the BI information on a BI report to support a corresponding type of BI analysis, by specifying how dimensions of the BI information are assembled in the BI report and how measures of the BI information are included in the BI report;

configuring, by the item handler module, the selected one or more analytic type templates for the new role on the basis of the BI information requirements that are specific to the new role;

generating, by the analytic path module when executed by one or more computer processors, a new analytic framework based on the configured analytic type templates, wherein the new analytic framework defines at least one navigable analytic path between the configured analytic type templates, wherein the at least one navigable analytic path relates a summary-level view of the BI information to a detail-level view of the BI information;

navigating from the summary-level view to the detail-level view based on the at least one navigable analytic path defined by the new analytic framework; and

generating, by the report module, the BI report by analysing the BI information based on the new analytic framework, whereafter the BI report is output.

2. The computer-implemented method as claimed in claim 1, wherein the configuring step comprises the step of:

specifying measures and dimensions relating to the new role on the basis of the BI information requirements that are specific to the new role.

3. The computer-implemented method as claimed in claim 1, further comprising:

generating BI reports containing BI information obtained from a source database system based on new BI reports created for the role; and

guiding navigation of the BI information using the at least one navigable analytic path among the new BI reports in the new analytic framework.

4. The computer-implemented method as claimed in claim 3, wherein the guiding step comprises the step of:

drilling BI information from the summary-level view to the detail-level view.

5. The computer-implemented method as claimed in claim 1, further comprising:

accepting modification of existing analysis types or addition of new analytic analysis types; and

incorporating the modified analysis types or new analytic analysis types in the analytic framework.

6. The computer-implemented method of claim 5, wherein the analytic framework is adaptable for modification of existing analysis types and addition of new analytic analysis types.

7. A non-transitory computer readable medium containing an adaptive analytics application executable to perform an operation to create an analytic framework for use in analysing business intelligence (BI) information stored in a database system, the adaptive analytics application including an item handler module, an analytic path module, and a report module, the operation comprising:

receiving, by the adaptive analytics application, a definition of a new role for analysing the BI information stored in the database system, wherein the definition of the new role specifies BI information requirements that are specific to the new role;

receiving, by the adaptive analytics application, selection of one or more analytic type templates for analysing the BI information, wherein each analytic type template specifies a layout of the BI information on a BI report to support a corresponding type of BI analysis, by specifying how dimensions of the BI information are assembled in the BI report and how measures of the BI information are included in the BI report;

configuring, by the item handler module, the selected one or more analytic type templates for the new role on the basis of the BI information requirements that are specific to the new role;

generating, by the analytic path module when executed by one or more computer processors, a new analytic framework based on the configured analytic type templates, wherein the new analytic framework defines at least one navigable analytic path between the configured analytic type templates, wherein the at least one navigable analytic path relates a summary-level view of the BI information to a detail-level view of the BI information;

navigating from the summary-level view to the detail-level view based on the at least one navigable analytic path defined by the new analytic framework; and

generating, by the report module, the BI report by analysing the BI information, based on the new analytic framework, whereafter the BI report is output.

8. The non-transitory computer readable medium of claim 7, wherein the analytic framework is adaptable for modification of existing analysis types and addition of new analytic analysis types.

9. A computer-implemented method for an adaptive analytics application to create an analytic framework for use in analysing business intelligence (BI) information stored in a database system, the adaptive analytics application including an item handler module, an analytic path module, and a report module, the computer-implemented method comprising:

receiving, by the adaptive analytics application, a definition of a new role for analysing the BI information stored in the database system, wherein the definition of the new role specifies BI information requirements that are specific to the new role;

receiving, by the adaptive analytics application, selection of one or more analytic type templates for analysing the BI information, wherein each analytic type template specifies a layout of the BI information on a BI report to support a corresponding type of BI analysis, by specifying how dimensions of the BI information are assembled in the BI report and how measures of the BI information are included in the BI report;

configuring, by the item handler module, the selected one or more analytic type templates for the new role on the basis of the BI information requirements that are specific to the new role;

generating a new analytic framework based on the configured analytic type templates, wherein the new analytic framework defines at least one navigable analytic path between the configured analytic type templates, wherein the at least one navigable analytic path relates a summary-level view of the BI information to a detail-level view of the BI information, wherein generating the new analytic framework comprises;

generating, by the report module, a series of BI reports based on the configured analytic type templates for the new role;

generating, by the analytic path module when executed by one or more computer processors, the at least one navigable analytic path by linking the series of BI reports based on a predefined analytic framework describing relations between analytic types; and

forming the new analytic framework based on the series of BI reports and the at least one navigable analytic paths; and

navigating from the summary-level view to the detail-level view based on the at least one navigable analytic path linking the series of BI reports in the new analytic framework, wherein at least one of the series of BI reports is output.

10. The computer-implemented method of claim 9, wherein the analytic framework is adaptable for modification of existing analysis types and addition of new analytic analysis types, wherein each analytic type template provides a distinct layout that prescribes how primary, secondary, and tertiary dimensions are defined as assembled, how measures are included and considered, and how information is laid out to support a type of analysis of interest, wherein context is passed via the at least one navigable analytic path.

11. The computer-implemented method of claim 10, wherein the adaptive analytics application is configured to add and modify, based on user input, predefined content stored in a performance analysing system to which the adaptive analytics application is operatively connected, wherein the predefined content includes predefined metrics and predefined BI reports, wherein the predefined metrics include measurements based on which information in one or more database systems is analysed, wherein the predefined BI reports are used to generate BI reports to facilitate analysing business performance.

12. The computer-implemented method of claim 11, wherein the adaptive analytics application further includes a storage module configured to store the analytic type templates and the analytic framework, wherein the analytic path module is configured to generate analytic paths among the new BI reports, based on the analytic framework, wherein the generated new BI reports and analytic paths form a customized analytic framework and constitute a component of one or more analytic information systems for report generation and information navigation;

wherein the adaptive analytics application is configured such that the customized analytic framework is generated and evolves to adapt to changing information needs of one or more end-users over time without requiring any technical expertise of any BI report author other than the one or more end-users and in order to assist management decision-making processes by reducing time to obtain desired information by the one or more end-users.

13. The computer-implemented method of claim 12, wherein configuring the selected one or more analytic type templates for the new role comprises specifying measures and dimensions relating to the new role on the basis of the BI information requirements that are specific to the new role;

wherein the item handler module, the analytic path module, and the report module increase a measure by which the adaptive analytics application is adaptable to changing information needs over time, relative to predefined reports and custom reports in absence of the item handler module, the analytic path module, and the report module.

14. The computer-implemented method of claim 13, wherein the analytic framework accelerates reporting and analysis relative to reporting and analysis in an absence of the analytic framework, reduces a time cost of defining information needs for content development relative to absence of the analytic framework, improves a measure of consistency with which business information is represented relative to absence of the analytic framework, and increases adoption of BI information to support decision-making processes relative to absence of the analytic framework.

15. The computer-implemented method of claim 14, wherein the performance analysing system is configured to generate the one or more analytic information systems based on user input, wherein the one or more analytic information systems are operatively connected to the adaptive analytics application and the one or more database systems, wherein the one or more analytic information systems are configured to provide BI reports and drill paths therebetween in order to facilitate BI analysis of the information stored in the one or more database systems, wherein each analytic information system is specifically tailored for a particular business organization.

16. The computer-implemented method of claim 15, wherein the analytic type templates include templates representing operational analysis types and analytic analysis types, wherein the analytic type templates representing the operational analysis types include templates representing a transaction detail analytic type and transaction list analytic type, wherein the analytic type templates representing the analytic analysis types include templates representing a detailed summary analytic type, profile analytic type, cycle time aging analytic type, contribution analytic type, cross-tab analytic type, variance analytic type, trend analytic type, and walkcross analytic type.

17. The computer-implemented method of claim 16, wherein the variance analytic type is independently usable to provide each individual kind of analysis selected from budget variance at a business organization level, budget variance at a cost centre manager level, and actual to planned headcount variance, wherein most significant impacts in both relative terms and absolute terms within each kind of analysis is highlighted, wherein the variance analytic type is independently usable to support each individual variance type selected from:

(i) value type variance only;

(ii) relative time variance only; and

(iii) value type variance with relative time variance;

wherein the trend analytic type is usable to provide trending of a desired measure against a primary dimension, wherein the trend analytic type is independently usable to provide each individual kind of analysis selected from sales revenue trend, customer turnover trend, customer turnover trend by job type, and bad debt trend.

18. The computer-implemented method of claim 17, wherein the contribution analytic type is independently usable to provide, for each individual entity selected from products, vendors, customers, employees, salespeople, and business units, each individual kind of analysis selected from revenue contribution, expense contribution, and unit sales contribution, wherein the contribution analytic type is independent supplemented by each analysis selected from drivers of a level of contribution and related impacts of the contribution and via a scatter plot mapping an entity of interest against two desired measures, in order to identify clustering behavior and anomalies.

19. The computer-implemented method of claim 18, wherein the profile analytic type is independently usable to provide each individual kind of analysis selected from:

(i) employee analysis including pay and benefits to date, current position, recent performance ratings, and skills;

(ii) customer analysis including contact information, sales representative, total sales to date, current receivables, past due balances, and product purchase activity summary; and

(iii) activity analysis pertaining to a desired customer identified from the customer revenue contribution analysis.

20. The computer-implemented method of claim 19, wherein the cycle time aging analytic type is independently usable to provide each individual kind of analysis selected from accounts receivable aging schedule, employee turnover times, and production work order late delivery times, wherein the cross-tab analytic type is usable to analyse a measure of interest at the intersection of two desired dimensions;

wherein the walkcross analytic type is independently usable to provide each individual kind of analysis selected from analysis of changes in headcount by type of resource for a specific organization, analysis of contributing factors to increases in headcount, and analysis of contributing factors to decreases in headcount.

21. The computer-implemented method of claim 20, wherein the analytic type templates representing the analytic analysis types further include templates representing financial analytic types and operational analytic types, respectively, wherein the financial analytic types include:

(i) a balance sheet analytic type independently usable to support each individual kind of analysis selected from vertical financial analysis, horizontal financial analysis, time trending analysis, point-in-time analysis, cost accounting analysis, organization-level analysis for a specific organization, and organization-level analysis across multiple organizations;

(ii) an income statement analytic type independently usable to support each individual kind of analysis selected from vertical financial analysis, horizontal financial analysis, time trending analysis, point-in-time analysis, cost accounting analysis, adjusted and unadjusted ledger analysis, organization-level analysis for a specific organization, and organization-level analysis across multiple organizations; and

(iii) a cashflow analytic type independently usable to support each individual kind of analysis selected from vertical financial analysis, horizontal financial analysis, cost accounting analysis, adjusted and unadjusted ledger analysis, organization-level analysis for a specific organization, organization-level analysis across multiple organizations, and analysis of adjusted and unadjusted ledgers.

22. The computer-implemented method of claim 21, wherein the operational analytic types include:

(i) a control analytic type independently usable to support each individual data type data selected from continuous data and discrete data, at each individual grouping level selected from grouped data and ungrouped data, in order to map observed actual values against upper, lower, and average control limits;

(ii) a difference analytic type usable to independently support each individual kind of analysis selected from actual differences between data series and deviation differences between data series; and

(iii) a high-low analytic type usable to independently support each individual kind of analysis selected from distribution between maximum and minimum values and a desired measure of central tendency, financial analysis of account balances by period, actual to planned benchmark data, actual difference analysis, deviation difference analysis, product selling price by market, product selling price by sales channel.