Natural language metric condition alerts generation

• US 9,323,736 B2
• Filed: 10/05/2012
• Issued: 04/26/2016
• 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
• Primary Examiner(s): SPOONER, LAMONT M
• Application Number:
  US13/646,609
• Publication Number:
  US 20140100846A1
• Time in Patent Office: 1,299 Days
• Field of Search: 704/1, 704/9, 704/10
• US Class Current: 1/1
• 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:

by a computing system comprising the computer;

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

determining a metric case associated with a metric case identifier based on comparing a comparable value and the observed business metric value for the business metric, wherein determining the metric case comprises identifying the metric case with a metric case identifier supporting metric cases comprising above target, above target plus tolerance, below target, and below target minus tolerance;

transforming the metric case identifier, one or more supporting values, and observed business metric value into an alert, wherein the transforming comprises (a)-(d);

(a) determining an identity for a receiving user and a location of the receiving user in an organizational structure comprising the group;

(b) determining a desired perspective based on whether the organizational structure indicates that the receiving user manages the group for which the metric was observed, wherein the desired perspective is determined to be second person when the receiving user manages the group, and the desired perspective is determined to be third person when the receiving user does not manage the group;

(c) based at least on the metric case identified by the metric case identifier, looking up a text template in a natural language dictionary organized for look up by metric case identifier and desired perspective, wherein the text template comprises natural language describing the metric case and one or more fields for completion, wherein the looking up switches between text template entries phrased in a second person perspective that describe the metric case and text template entries phrased in a third person perspective that describe the same metric case based on the desired perspective; and

(d) completing the text template via the one or more supporting values, wherein completing the text template transforms the text template and comprises substituting the one or more supporting values into the text template; and

outputting the alert, wherein the alert comprises a natural language description of a condition of the business metric, wherein the natural language description comprises the completed text template, which comprises the natural language describing the metric case and the one more supporting values.

2. 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.

3. The method of claim 2 wherein the text template further comprises a natural language subheading providing further information about the condition of the business metric.

4. 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.

5. The method of claim 4 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.

6. 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.

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

8. The method of claim 7 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.

9. 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.

10. 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.

11. The method of claim 1 wherein:

determining the metric case comprises comparing the observed business metric value for the business metric against an enterprise average used as the comparable value; and

the text template describes comparing against an enterprise average.

12. The method of claim 1 further comprising:

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

13. 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.

14. 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.

15. 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;

wherein the alert further comprises the summary graph.

16. 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.

17. The method of claim 1 further comprising:

associating a graphic with the completed text template, wherein the graphic depicts a visual representation of the condition of the business metric;

wherein the outputted alert further comprises the associated graphic.

18. One or more non-transitory computer-readable media comprising computer-executable instructions for performing a method comprising:

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

determining a metric case associated with a metric case identifier based on comparing a comparable value and the observed business metric value for the business metric, wherein determining the metric case comprises identifying the metric case with a metric case identifier supporting metric cases comprising above target, above target plus tolerance, below target, and below target minus tolerance;

transforming the metric case identifier, one or more supporting values, and observed business metric value into an alert, wherein the transforming comprises (a)-(d);

(a) determining an identity for a receiving user and a location of the receiving user in an organizational structure comprising the group;

(b) determining a desired perspective based on whether the organizational structure indicates that the receiving user manages the group for which the metric was observed, wherein the desired perspective is determined to be second person when the receiving user manages the group, and the desired perspective is determined to be third person when the receiving user does not manage the group;

(c) based at least on the metric case identified by the metric case identifier, looking up a text template in a natural language dictionary organized for look up by metric case identifier and desired perspective, wherein the text template comprises natural language describing the metric case and one or more fields for completion, wherein the looking up switches between text template entries phrased in a second person perspective that describe the metric case and text template entries phrased in a third person perspective that describe the same metric case based on the desired perspective; and

(d) completing the text template via the one or more supporting values, wherein completing the text template transforms the text template and comprises substituting the one or more supporting values into the text template; and

outputting the alert, wherein the alert comprises a natural language description of a condition of the business metric, wherein the natural language description comprises the completed text template, which comprises the natural language describing the metric case and the one more supporting values.

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

for a receiving user in an organizational structure, constructing a user-centric natural language description of a business enterprise group for which a business metric has been observed, wherein the constructing comprises switching between text templates phrased in a second person perspective that describe a business metric condition status and text templates phrased in a third person perspective that describe the same business metric condition status based on a value indicating a desired perspective of the business enterprise group, wherein the desired perspective is determined to be second person responsive to determining that a location of the receiving user in the organizational structure indicates that the receiving user manages the group;

constructing a natural language description of the business metric;

constructing a natural language description of the 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;

constructing an alert comprising the user-centric natural language description of the business enterprise group and the natural language description of the business metric condition status for the business metric as observed for the business enterprise group; and

distributing the alert.

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;

configuration information comprising an organizational structure comprising organizational chart data; and

a natural language engine configured to receive a business metric value as observed within a population of a group, a business metric identifier, a business metric condition comprising a target and a tolerance, supporting values, and an indication of user perspective of a user receiving an alert of the business metric condition, 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, wherein the indication of user perspective is automatically determined to be second person when a location of the user in the organizational structure indicates that the user manages the group.