Method and device for estimating efficiency of an employee of an organization

• US 10,043,146 B2
• Filed: 03/27/2015
• Issued: 08/07/2018
• Est. Priority Date: 02/12/2015
• Status: Active Grant

• Current Assignee: Workday Incorporated
• Original Assignee: Wipro Limited
• Inventors: Khatravath, Sreevidya, Raman, Manikhantan Sanakara, Suman, Abhishek
• Primary Examiner(s): Miller, Alan S
• Application Number:
  US14/671,043
• Publication Number:
  US 20160239782A1
• Time in Patent Office: 1,229 Days
• Field of Search: 705 711- 742
• CPC Class Codes: G06Q 10/06398 Performance of employee with respect to a job function
• CPC Class Codes: G06Q 10/1091 Recording time for administrative or management purposes

Abstract

The present disclosure relates to a method and device for estimating efficiency of an employee of an organization. In one embodiment, the input data is received from one or more data sources. The input data is classified into one of location data, video data, voice data and text data of the employee. Using the location data and the video data, the trajectory information of the employee is generated. The trajectory information, the voice data and the text data are correlated. Based on the correlation, the efficiency of the employee is estimated.

Claims

1. A method for estimating efficiency of an employee of an organization, the method comprising:

receiving, by an estimation computing device, input data from a plurality of data sources;

converting, by the estimation computing device, the received input data into a pre-defined format;

classifying, by the estimation computing device, the converted input data into one or more of location data, video data, voice data, and text data relating to the employee, forming, at least in part, formatted voice data and formatted video data;

identifying, by the estimation computing device, the employee based on at least one of the formatted voice data and the formatted video data;

generating, by the estimation computing device, a trajectory information of the employee using at least the location data and the video data;

correlating, by the estimation computing device, the trajectory information, the voice data and the text data relating to the employee;

estimating, by the estimation computing device, an efficiency of the employee based on the correlation and generating recommendations based on the estimated efficiency;

responsive to determining that the estimated efficiency is less than a predefined efficiency limit, providing, by an output device, the estimated efficiency of the employee and recommendations based on the estimated efficiency to a supervisor of the employee;

receiving, by an input device, user feedback on the estimated efficiency and the recommendations; and

applying, by the estimation computing device, learning models to update the efficiency estimate and recommendations based on the user feedback.

2. The method as claimed in claim 1, wherein the plurality of data sources comprises a video camera, an e-mail database, recorded meeting database, employee swipe database, and security systems.

3. The method as claimed in claim 1, wherein the text data includes at least one of e-mail information, calendar information, login information, swipe information and resource information.

4. The method as claimed in claim 1, wherein the voice data includes information about meetings of the employee.

5. The method as claimed in claim 1, wherein the estimated efficiency of the employee provides one or more information comprising amount of time spent on a work assigned to the employee, one or more resources used by the employee for completing the work, preparing presentations for the work and time spent in a meeting.

6. The method as claimed in claim 1, wherein using the formatted video data further comprises identifying a face of the employee and movement coordinates of the employee in the formatted video data.

7. An estimation computing device for estimating efficiency of an employee of an organization, comprising:

a processor; and

a memory communicatively coupled to the processor, wherein the memory stores processor-executable instructions, which, on execution, causes the processor to;

receive input data from a plurality of data sources;

convert the received input data into a pre-defined format;

classify the converted input data into one or more of location data, video data, voice data, and text data relating to the employee, forming, at least in part, formatted voice data and formatted video data;

identify the employee based on at least one of the formatted voice data and the formatted video data;

generate a trajectory information of the employee using at least the location data and the video data;

correlate the trajectory information, the voice data and the text data relating to the employee;

estimate an efficiency of the employee based on the correlation and generate recommendations based on the estimated efficiency;

responsive to determining that the estimated efficiency is less than a predefined efficiency limit, provide recommendations based on the estimated efficiency of the employee;

receive user feedback on the estimated efficiency and the recommendations; and

apply learning models to update the efficiency estimate and recommendations based on the user feedback.

8. The estimation computing device as claimed in claim 7, wherein the estimated efficiency of the employee provides one or more information comprising amount of time spent on a work assigned to the employee, one or more resources used by the employee for completing the work, preparing presentations for the work and time spent in a meeting.

9. The estimation computing device as claimed in claim 7, wherein the plurality of data sources comprises a video camera, an e-mail database, recorded meeting database, employee swipe database and security systems.

10. The estimation computing device as claimed in claim 7, wherein the text data includes at least one of e-mail information, calendar information, login information, swipe information and resource information.

11. The estimation computing device as claimed in claim 7, wherein the voice data includes information about meetings of the employee.

12. The estimation computing device as claimed in claim 7, wherein using the formatted video data further comprises identifying a face of the employee and movement coordinates of the employee in the formatted video data.

13. A non-transitory computer readable medium including instructions stored thereon that when processed by at least one processor cause an estimation computing device to perform operations comprising:

receiving input data from a plurality of data sources;

converting the received input data into a pre-defined format;

classifying the converted input data into one or more of location data, video data, voice data, and text data relating to the employee , forming, at least in part, formatted voice data and formatted video data;

identifying the employee based on at least one of the formatted voice data and the formatted video data;

generating a trajectory information of the employee using at least the location data and the video data;

correlating the trajectory information, the voice data and the text data relating to the employee;

estimating an efficiency of the employee based on the correlation and generate recommendations based on the estimated efficiency;

responsive to determining that the estimated efficiency is less than a predefined efficiency limit, providing the estimated efficiency of the employee and recommendations based on the estimated efficiency;

receiving user feedback on the estimated efficiency and the recommendations; and

applying learning models to update the efficiency estimate and recommendations based on the user feedback.

14. The medium as claimed in claim 13, wherein the instructions further cause the at least one processor to provide a notification based on the estimated efficiency of the employee, wherein the notification includes information of at least one of successful completion of the work by the employee, incomplete work by the employee and misuse of one or more resources by the employee.

15. The medium as claimed in claim 13, wherein the text data includes at least one of e-mail information, calendar information, login information, swipe information and resource information.

16. The medium as claimed in claim 13, wherein the voice data includes information about meetings of the employee.

17. The medium as claimed in claim 13, wherein using the formatted video data further comprises identifying a face of the employee and movement coordinates of the employee in the formatted video data.