INTELLIGENT THRESHOLD EDITOR

• US 20160224920A1
• Filed: 01/30/2015
• Published: 08/04/2016
• Est. Priority Date: 01/30/2015
• Status: Active Grant

• Current Assignee: SAP SE
• Original Assignee: Andreas Doms
• Inventors: DOMS, Andreas
• Granted Patent: US 10,089,589 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06Q 10/06393 Score-carding, benchmarking or key performance indicator [KPI] analysis

Abstract

A method for selecting thresholds for a data variable or key performance indicator (KPI) includes processing, by a computer, an actual data set for the data variable or KPI and displaying a perspective view representing the actual data for the data variable or KPI in an interactive threshold editor or selection dialog on a computer-user interface. Processing the actual data set for the data variable or KPI includes statistically curve fitting the actual data set to a probability distribution function and determining a set of pre-selected thresholds based on the parameters obtained by fitting the actual data set to the probability distribution function. The method further involves presenting one or more user-activable UI elements that are configured to receive user acceptance, rejection or adjustment of the pre-selected thresholds as thresholds for the data variable or KPI.

Claims

1. A system for selecting thresholds for a data variable or key performance indicator (KPI), the system comprising:

a processor coupled to a memory;

a computer-user interface; and

a threshold editor configured to process an actual data set for the data variable or KPI, and display a perspective view representing the actual data for the data variable or KPI in an interactive threshold editor or selection dialog on the computer-user interface.

2. The system of claim 1, wherein the threshold editor is further configured to statistically curve fit the actual data set to a probability distribution function and determine a set of pre-selected thresholds based on the parameters obtained by fitting the actual data set to the probability distribution function.

3. The system of claim 2, wherein the probability distribution function is the normal distribution function and the parameters obtained by fitting the actual data set include a mean μ

and a standard deviation σ

of the fitted normal distribution function, and the maximum and minimum data values in the actual data set.

4. The system claim 3, wherein the threshold editor is further configured to determine the set of pre-selected thresholds by selecting at least one threshold proportional to one of the mean μ

, the standard deviation σ

, the maximum data value and the minimum data value.

5. The system claim 2, wherein the threshold editor is further configured to evaluate more than one different statistical distribution function to determine which type of distribution function best fits the actual data set and determine the set of pre-selected thresholds based on the characteristics and parameters of the best-fitting distribution.

6. The system claim 2, wherein the threshold editor is further configured to display the perspective view representing the actual data for the data variable or KPI in the interactive threshold editor or selection by displaying a graphical representation of the actual data and displaying one or more pre-selected thresholds in the interactive threshold editor or selection dialog.

7. The system claim 6, wherein the threshold editor is further configured to present one or more user-activable UI elements that are configured to receive user acceptance, rejection or adjustment of the pre-selected thresholds as thresholds for the data variable or KPI.

8. The system claim 6, wherein the threshold editor is further configured to present one or more user-activable UI elements that are configured to define a data range delimited by a threshold as having an open interval boundary or a closed interval boundary, and/or are configured to define an action for a data range delimited by a threshold.

9. A method for selecting thresholds for a data variable or key performance indicator (KPI), the method comprising:

processing, by a computer, an actual data set for the data variable or KPI; and

displaying a perspective view representing the actual data for the data variable or KPI in an interactive threshold editor or selection dialog on a computer-user interface.

10. The method of claim 9, wherein processing the actual data set for the data variable or KPI includes statistically curve fitting the actual data set to a probability distribution function and determining a set of pre-selected thresholds based on the parameters obtained by fitting the actual data set to the probability distribution function.

11. The method of claim 10, wherein the probability distribution function is the normal distribution function and the parameters obtained by fitting the actual data set include a mean μ

and a standard deviation σ

of the fitted normal distribution function, and the maximum and minimum data values in the actual data set.

12. The method of claim 11, wherein determining a set of pre-selected thresholds includes selecting a threshold proportional to one of the mean μ

, the standard deviation a, the maximum data value and the minimum data value.

13. The method of claim 10, wherein statistically curve fitting the actual data set to a probability distribution function includes evaluating more than one different statistical distribution function to determine which type of distribution function best fits the actual data set and determining the set of pre-selected thresholds based on the characteristics and parameters of the best-fitting distribution.

14. The method of claim 10, wherein displaying the perspective view representing the actual data for the data variable or KPI in the interactive threshold editor or selection includes displaying a graphical representation of the actual data in the interactive threshold editor or selection dialog and displaying one or more pre-selected thresholds in the interactive threshold editor or selection dialog.

15. The method of claim 14, further comprising, presenting one or more user-activable UI elements that are configured to receive user acceptance, rejection or adjustment of the pre-selected thresholds as thresholds for the data variable or KPI.

16. The method of claim 15, wherein presenting one or more user-activable UI elements includes presenting one or more user-activable UI elements that are configured to define a data range delimited by a threshold as having an open interval boundary or a closed interval boundary, and/or are configured to define an action for a data range delimited by a threshold.

17. A non-transitory computer readable medium, comprising:

instructions capable of being executed on a microprocessor,

which instructions when executed allow a computer device to process an actual data set for the data variable or KPI; and

display a perspective view representing the actual data for the data variable or KPI in an interactive threshold editor or selection dialog on a computer-user interface.

18. The non-transitory computer readable medium of claim 17, wherein the instructions when executed on the microprocessor cause the computer device to process the actual data set for the data variable or KPI by statistically curve fitting the actual data set to a probability distribution function and determine a set of pre-selected thresholds based on the parameters obtained by fitting the actual data set to the probability distribution function.

19. The non-transitory computer readable medium of claim 17, wherein the instructions when executed on the microprocessor cause the computer device to process the actual data set for the data variable or KPI by evaluating more than one different statistical distribution function to determine which type of distribution function best fits the actual data set and determine the set of pre-selected thresholds based on the characteristics and parameters of the best-fitting distribution function.

20. The non-transitory computer readable medium of claim 17, wherein the instructions when executed on the microprocessor cause the computer device to display a graphical representation of the actual data in the interactive threshold editor or selection dialog, display one or more pre-selected thresholds in the interactive threshold editor or selection dialog, and presenting one or more user-activable UI elements that are configured to receive user acceptance, rejection or adjustment of the one or more pre-selected thresholds as thresholds for the data variable or KPI.