AUTOMATED EMPLOYEE SATISFACTION PREDICTOR

• US 20140351155A1
• Filed: 05/21/2013
• Published: 11/27/2014
• Est. Priority Date: 05/21/2013
• Status: Abandoned Application

• Current Assignee: Rawllin International Inc.
• Original Assignee: Rawllin International Incorporated
• Inventors: Nikankin, Andrey N.
• Application Number:
  US13/899,380
• Publication Number:
  US 20140351155A1
• Time in Patent Office: Days
• US Class Current: 705/320
• CPC Class Codes: G06Q 10/105 Human resources

Abstract

Employee satisfaction and the possibility of an employee job change are predicted. Data can be collected related to employee internet usage, employee mobile device telecom usage, employee human resource data, or employee demographic data. By analyzing this collection data, employees that are satisfied or dissatisfied can be identified. In addition, it can also be determined how likely an employee is to make a job change.

Claims

1. A system, comprising:

a memory that stores computer executable components; and

a processor, communicatively coupled to the memory, that facilitates execution of computer executable components, the computer executable components comprising;

an internet monitoring component that monitors internet usage data associated with internet usage of an employee and generates employee internet profile data representative of an internet profile of the employee based on a result of the internet usage data being monitored;

a mobile device monitoring component that monitors mobile communication data representative of communications associated with a mobile device of the employee and generates employee mobile device profile data representative of an employee mobile device profile based on a result of the mobile communication data being monitored;

a human resources data component that generates employee human resource profile data representative of a human resource profile of the employee based on job description data representative of a job description of the employee, attendance record data representative of an attendance record of the employee, and compensation profile data representative of a compensation profile of the employee; and

an employee satisfaction component that determines employee job satisfaction data representative of a job satisfaction of the employee based on the employee internet profile data, the employee mobile device profile data, and the employee human resource profile data.

2. The system of claim 1, wherein the computer executable components further comprise:

a demographic component that generates employee demographic profile data representative of a demographic profile of the employee wherein the employee satisfaction component determines the employee job satisfaction data based on the employee demographic profile data.

3. The system of claim 2, wherein the employee demographic profile data includes at least one of a home purchase date associated with the employee, a residence change date associated with the employee, a set of child birth dates associated with the employee, a marriage date associated with the employee, a credit report value associated with the employee, or an employee birth date associated with the employee.

4. The system of claim 1, wherein the internet monitoring component monitors at least one of social network site visits by the employee, social network site posts by the employee, updated resumes in social network sites uploaded by the employee, business e-mail frequency associated with e-mails by the employee, personal e-mail frequency associated with the e-mails by the employee, or university site visits by the employee.

5. The system of claim 1, wherein the mobile device monitoring component monitors at least one of a first frequency of calls using the mobile device during work hours defined for the employee, a second frequency of text messages using the mobile device during the work hours, or location log data representative of past locations of the mobile device.

6. The system of claim 2, wherein the employee satisfaction component further generates a possible job change predictor value associated with the employee based on the employee internet profile data, the employee mobile device profile data, the employee human resource profile data, and the employee demographic profile data.

7. A method, comprising:

receiving, by a system including a processor, internet history data indicative of an internet history associated with an employee wherein the internet history data comprises social networking post data, web site history data, application access data, employer e-mail volume data, and personal e-mail volume data;

receiving mobile device data representative of communications associated with a mobile device of the employee wherein the mobile device data comprises a first set of phone calls using the mobile device, a second set of text messages using the mobile device, or location log data representative of past locations of the mobile device;

receiving employee human resource profile data representative of a human resource profile of the employee based on job description data representative of a job description of the employee, attendance record data representative of an attendance record of the employee, and compensation profile data representative of a compensation profile of the employee;

generating an employment satisfaction rating representative of an employment satisfaction of the employee based on the set of internet history data, the mobile device data, and the employee human resource profile data.

8. The method of claim 7, further comprising:

generating an intensity of resume updates index based on the internet history data wherein the intensity of resume updates is a function based on a time of monitoring, a volume of resumes in a set of resumes, and a volume of information included in skills, project, or development sections of resumes in the set of resumes.

9. The method of claim 8, wherein the generating the employment satisfaction rating is based on the intensity of resume updates index.

10. The method of claim 7, further comprising:

generating a call volume index based on the mobile device data, wherein the call volume index is a function of at least one of a time of monitoring, the first set of phone calls, a volume of the first set of phone calls, a type of phone calls for phone calls in the first set of phone calls, a time of phone calls for phone calls in the first set of phone calls, or a weather index associated with a date of phone calls in the first set of phone calls.

11. The method of claim 10, further comprising, in response to determining the time of phone calls associated with a phone call among the first set of phone calls is outside of a work schedule associated with the employee, removing the phone call from the first set of phone calls.

12. The method of claim 10, wherein the generating the employment satisfaction rating is based on the call volume index.

13. The method of claim 7, further comprising:

generating an internet job search index based on the internet history data, wherein the internet job search index is a function of at least one of a time of monitoring, a number of site visits to a set of employment sites, a number of application visits to a set of employment applications, a number of site visits to a set of educational sites, or a number of application visits to a set of educational applications.

14. The method of claim 13, wherein the generating the employment satisfaction rating is based on the internet job search index.

15. The method of claim 7, further comprising:

generating a geographical index based on the location log data, wherein the geographical index is a function of at least one of a set of clustered locations, a time spent at clustered locations among the set of clustered locations, or a time of day associated with clustered locations among the set clustered locations.

16. The method of claim 15, wherein the generating the employment satisfaction rating is based on the geographical index.

17. The method of claim 15, wherein the geographical index further indicates an emergence of a new geographical location.

18. The method of claim 7, further comprising:

generating a possible job change index based on the employment satisfaction rating.

19. The method of claim 18, wherein the generating the possible job change index is based on the internet history data, the mobile device data, and the employee human resource profile data.

20. A system, comprising:

means for receiving internet history data indicative of an internet history associated with an employee wherein the internet history data comprises social networking post data, web site history data, application access data, employer e-mail volume data, and personal e-mail volume data;

means for mobile device data representative of communications associated with a mobile device of the employee wherein the mobile device data comprises a first set of phone calls using the mobile device, a second set of text messages using the mobile device, or location log data representative of past locations of the mobile device;

means for employee human resource profile data representative of a human resource profile of the employee based on job description data representative of a job description of the employee, attendance record data representative of an attendance record of the employee; and

means for generating an employment satisfaction rating representative of an employment satisfaction of the employee based on the set of internet history data, the mobile device data, and the employee human resource profile data.

21. The system of claim 20, further comprising:

means for generating a possible job change index based on the employment satisfaction rating, the internet history data, the mobile device data, and the employee human resource profile data.

22. The system of claim 20, further comprising:

means for generating an intensity of resume updates index based on the internet history data, wherein the intensity of resume updates is a function based on a time of monitoring, a volume of resumes in a set of resumes, and a volume of information included in skills, project, or development sections of resumes in the set of resumes, and wherein the means for generating the employment satisfaction rating generates the employment satisfaction rating based on the intensity of resume updates index.

23. A computer-readable storage medium comprising computer-executable instructions that, in response to execution, cause a computing system comprising a processor to perform operations, comprising:

receiving internet history data indicative of an internet history associated with an employee, wherein the internet history data comprises social networking post data, web site history data, application access data, employer e-mail volume data, and personal e-mail volume data;

receiving mobile device data representative of communications associated with a mobile device of the employee wherein the mobile device data comprises a first set of phone calls using the mobile device, a second set of text messages using the mobile device, or location log data representative of past locations of the mobile device;

receiving employee human resource profile data representative of a human resource profile of the employee based on job description data representative of a job description of the employee, attendance record data representative of an attendance record of the employee, and compensation profile data representative of a compensation profile of the employee;

receiving demographic profile data representative of a demographic profile of the employee based on at least one of a home purchase date associated with the employee, a residence change date associated with the employee, a set of child birth dates associated with the employee, a marriage date associated with the employee, a credit report value associated with the employee, or an employee birth date associated with the employee; and

generating an employment satisfaction rating representative of an employment satisfaction of the employee based on the set of internet history data, the mobile device data, the employee human resource profile data; and

the demographic profile data.

24. The computer-readable storage medium of claim 23, further comprising:

generating a possible job change index based on the employment satisfaction rating, the internet history data, the mobile device data, the employee human resource profile data, and the demographic profile data.

25. The computer-readable storage medium of claim 23, wherein internet history data includes data from the mobile device of the employee.