NATURAL LANGUAGE METRIC CONDITION ALERTS GENERATION

• US 20140100846A1
• Filed: 10/05/2012
• Published: 04/10/2014
• Est. Priority Date: 10/05/2012
• Status: Active Grant

• Current Assignee: Successfactors Incorporated (SAP SE)
• Original Assignee: Successfactors Incorporated (SAP SE)
• Inventors: Haine, Dominic Philip, Strezo, Michael, Capraro, Michel Angelo, Hagar, Lyndal, Ashton, Anthony, Bolwell, Laesa, Krakovsky, Dmitri, Ahlberg, Thor Axel
• Granted Patent: US 9,323,736 B2
• Time in Patent Office: Days
• US Class Current: 704/9
• CPC Class Codes: G06F 40/186 Templates
• CPC Class Codes: G06Q 10/067 Enterprise or organisation modelling

Abstract

Enterprise data sources can be monitored to detect metric conditions via rules, and alerts can be generated. The alerts can be presented as natural language descriptions of business metric conditions. From an alert, the reader can navigate to a story page that presents additional detail and allows further navigation within the data. Additional detail presented can include a drill down synopsis, strategies for overcoming a negative condition, links to discussions within the organization about the condition, options for sharing or collaborating about the condition, or the like.

Claims

1. A method implemented at least in part by a computer, the method comprising:

receiving an observed business metric value for a business metric and one or more supporting values further quantifying the business metric;

determining a metric case based on comparing a comparable value and the observed business metric value for the business metric;

based at least on the metric case, looking up a text template in a natural language dictionary, wherein the text template comprises natural language and one or more fields for completion;

completing the text template via the one or more supporting values; and

outputting a natural language description of a condition of the business metric, wherein the natural language description comprises the completed text template.

2. One or more computer-readable media comprising computer-executable instructions for performing the method of claim 1.

3. The method of claim 1 wherein the text template comprises a natural language complete sentence in headline format describing the condition of the business metric.

4. The method of claim 3 wherein the text template further comprises a natural language subheading providing further information about the condition of the business metric.

5. The method of claim 1 wherein the text template is stored in a template table comprising a plurality of text templates organized for look up by business metric and metric case.

6. The method of claim 5 wherein:

a subset of the text templates are associated with a metric case indicative of exceeding a target and threshold; and

the subset of text templates contain color information designating language to be depicted in a color denoting urgency.

7. The method of claim 1 further comprising:

associating color data with the natural language description according to severity of the condition of the business metric.

8. The method of claim 1 wherein determining the metric case comprises applying a tolerance value indicating a tolerance for the comparable value.

9. The method of claim 8 wherein:

determining the metric case comprises determining that the observed business metric value exceeds the comparable value plus the tolerance; and

the text template comprises natural language indicating that a target is greatly exceeded.

10. The method of claim 1 wherein determining the metric case comprises choosing from a group comprising:

above target,

above target plus threshold,

below target, and

below target minus threshold.

11. The method of claim 1 wherein:

determining the metric case comprises comparing against a prior period; and

the text template describes comparing against a prior period.

12. The method of claim 1 wherein:

determining the metric case comprises comparing against an enterprise average; and

the text template describes comparing against an enterprise average.

13. The method of claim 1 further comprising:

receiving a value indicative of a desired perspective; and

based on the value indicative of the desired perspective, choosing between text template entries phrased in a second person perspective and text template entries phrased in a third person perspective.

14. The method of claim 1 further comprising:

switching between formal and casual language based on a tone parameter.

15. The method of claim 1 further comprising:

receiving a metric identifier for the business metric;

wherein looking up the text template is additionally based on the metric identifier.

16. The method of claim 1 wherein:

the business metric relates to termination rate; and

at least one of the one or more supporting values indicates a headcount of employees who terminated.

17. The method of claim 1 further comprising:

associating a summary graph with the natural language description, wherein the summary graph depicts a trend of the condition of the business metric.

18. The method of claim 1 wherein the text template comprises a field for a description of a business enterprise group for which a business metric has been observed, a natural language description of the business metric, and a natural language description of a business metric condition status for the business metric as observed for the business enterprise group

19. One or more computer-readable storage media comprising computer-executable instructions causing a computing system to perform a method comprising:

constructing a user-centric natural language description of a business enterprise group for which a business metric has been observed;

constructing a natural language description of the business metric; and

constructing a natural language description of a business metric condition status for the business metric as observed for the business enterprise group, based on a metric case for the observed business metric.

20. A system monitoring business metric conditions within one or more business enterprise data sources, the system comprising:

one or more processors;

memory;

a natural language dictionary comprising natural language words associated with respective comparison scenarios; and

a natural language engine configured to receive a business metric value as observed within a population, a business metric identifier, a business metric condition comprising a target and a tolerance, supporting values, and an indication of user perspective, wherein the natural language engine is further configured to consult the natural language dictionary and output a natural language description of the business metric condition from words in the natural language dictionary based on the business metric value, the business metric identifier, the target, the tolerance, and supporting values;

wherein the natural language engine further comprises logic configured to choose between natural language description using second person grammar and natural language description using third person grammar for the natural language description of the business metric condition based on the indication of user perspective.