CA2865890A1 - Systems and methods for analyzing recognition data for talent and culture discovery - Google Patents
Systems and methods for analyzing recognition data for talent and culture discovery Download PDFInfo
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- CA2865890A1 CA2865890A1 CA2865890A CA2865890A CA2865890A1 CA 2865890 A1 CA2865890 A1 CA 2865890A1 CA 2865890 A CA2865890 A CA 2865890A CA 2865890 A CA2865890 A CA 2865890A CA 2865890 A1 CA2865890 A1 CA 2865890A1
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- CA
- Canada
- Prior art keywords
- recognition
- employee
- data
- graph
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- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
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Classifications
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0639—Performance analysis of employees; Performance analysis of enterprise or organisation operations
- G06Q10/06398—Performance of employee with respect to a job function
Abstract
Embodiments of the invention provide tools for creating recognition moments in real-time and generating recognition network graphs that represent the recognition connections throughout organizations. Recognition network graphs are utilized to transmit recognition announcements throughout the organization, which, in turn, promotes a positive organizational climate and the values of the organization and aides managers in determining employees who are critical to the prior and future success of their business initiatives even when those employees are not within their traditional organizational hierarchies or span of control. The recognition network graph highlights connections between employees that are not self-evident within traditional organization charts. The recognition network graph may depict how business objectives are achieved via both formal and informal employee connections. Embodiments further provide managers and others with dynamic user interfaces containing recognition network graphs, reports and other analytics that facilitate the assessment of employee performance, influence, impact and other employee metrics.
Claims (48)
1. A system for promoting employee recognition at an organization, the system comprising:
a recognition data collection module for:
receiving organizational data of the organization, the organizational data including at least organizational relationship data of a plurality of employees;
receiving recognition details associated with one or more recognition moments;
storing in memory the recognition details and the organizational data; and a recognition graph module for generating, using at least one processor, a recognition network graph based on at least the recognition details and the organizational data containing the organizational relationship data, wherein the generated recognition network graph contains a plurality of nodes representing the plurality of employees.
a recognition data collection module for:
receiving organizational data of the organization, the organizational data including at least organizational relationship data of a plurality of employees;
receiving recognition details associated with one or more recognition moments;
storing in memory the recognition details and the organizational data; and a recognition graph module for generating, using at least one processor, a recognition network graph based on at least the recognition details and the organizational data containing the organizational relationship data, wherein the generated recognition network graph contains a plurality of nodes representing the plurality of employees.
2. The system of claim 1, wherein the recognition graph module aggregates at least the recognition details and the organizational data to generate the recognition network graph.
3. The system of claim 1, wherein the recognition graph module associates a first node and a second node with at least one recognition moment and at least a portion of the organizational data, the second node connected to the first node by a graphical link.
4. The system of claim 3, wherein the graphical link represents at least one of recognition moments received by a first employee from a second employee and recognition moments received by the second employee from the first employee.
5. The system of claim 3, wherein the graphical link corresponds to the stored recognition details.
6. The system of claim 3, wherein the recognition data collection module determines an employee connection score based on the recognition details and organizational data.
7. The system of claim 6, wherein the shape, size or color of the first node is based on at least the determined employee connection score.
8. The system of claim 6, wherein the shape, thickness or color of the graphical link is based on at least on the determined employee connection score.
9. The system of claim 1, wherein the recognition network graph contains a focus node representing a first employee, the focus node being located at a general center location of the recognition network graph and connected to a plurality of connected nodes by a plurality of graphical links in accordance with at least the recognition details and the organizational data.
10. The system of claim 9, wherein, in response to a selection of a second employee, the recognition graph module generates a second recognition network graph containing a second focus node located at a general center location of the second recognition network graph, the second focus node representing the second employee.
11. The system of claim 1, wherein the recognition graph module generates a performance graph, the performance graph depicting employee performance of at least some of the plurality of employees.
12. The system of claim 11, wherein the performance graph is generated based on at least one of: a determined employee connection score, the number of recognition moments for each employee, and an economic value of recognition moments.
13. The system of claim 1, wherein the recognition graph module generates an influence graph, the influence graph depicting the relative organizational influence of at least some of the plurality of employees of the organization.
14. The system of claim 13, wherein the influence graph is generated based on at least one of the following recognition details:
number of recognition moments;
source of the recognition moments;
employee connection score; and employee performance rating.
number of recognition moments;
source of the recognition moments;
employee connection score; and employee performance rating.
15. The system of claim 13, wherein the influence graph contains a first node representing a first employee on a first team, and the position of a first node within the influence graph is based on recognition details including:
an internal employee connection score calculated using the recognition moments associated with the first employee and employees part of the first team; and an external employee connection score calculated based on recognition moments associated with the first employee and employees not part of the first team.
an internal employee connection score calculated using the recognition moments associated with the first employee and employees part of the first team; and an external employee connection score calculated based on recognition moments associated with the first employee and employees not part of the first team.
16. The system of claim 1, wherein the recognition graph module generates a performance alignment graph, the performance alignment graph depicting the alignment of the recognition moments against performance ratings associated with performance reviews for at least some of the plurality of employees.
17. The system of claim 16, wherein the performance alignment graph contains a first node representing a first employee, and the position of the first node within the performance alignment graph is based on at least a recognition connection score and a performance review rating of the first employee.
18. The system of claim 1, wherein the recognition details comprise one or more of a creator, a recipient, an award, an award reason, a role relationship, a performance indicator, a scope of accomplishment, a recognition category, a message; recognition reason data;
recognition nominator data; recognition nominee data; recognition profile and activities data; sphere of influence data; validation data; composition of recognition message data;
approval data; and recognition distribution data.
recognition nominator data; recognition nominee data; recognition profile and activities data; sphere of influence data; validation data; composition of recognition message data;
approval data; and recognition distribution data.
19. The system of claim 1, wherein the recognition graph module is further configured to automatically regenerate the recognition network graph in response to the data collection module receiving new recognition details associated with new recognition moments, the recognition graph module regenerating the recognition network graph based on the new recognition details.
20. The system of claim 1, further comprising a recognition delivery module configured to automatically transmit the recognition details to one or more computing devices upon the receiving of the recognition details by the recognition data collection module, wherein the transmitting causes at least some of the recognition details to be automatically displayed at the one or more computing devices.
21. The system of claim 1, further comprising a talent analysis module configured to:
automatically process, using the at least one processor, the recognition details and the organizational data to generate recognition analytics results;
determine employees part of a manager's team; and generate a talent analysis user interface containing the generated recognition analytics results associated with the employees part of the manager's team.
automatically process, using the at least one processor, the recognition details and the organizational data to generate recognition analytics results;
determine employees part of a manager's team; and generate a talent analysis user interface containing the generated recognition analytics results associated with the employees part of the manager's team.
22. The system of claim 21, wherein the generated recognition analytics results describing at least one of:
likelihood of an employee leaving the company;
work engagement;
employee connections;
performance potential;
scope of influence;
employee engagement;
employee connection score;
succession candidacy;
readiness for promotion;
most inspirational employees;
top performers;
top culture promoter; and top influencers.
likelihood of an employee leaving the company;
work engagement;
employee connections;
performance potential;
scope of influence;
employee engagement;
employee connection score;
succession candidacy;
readiness for promotion;
most inspirational employees;
top performers;
top culture promoter; and top influencers.
23. The system of claim 1, wherein the organizational data comprises at least one of:
team and division data;
tenure data;
diversity data;
performance rating data;
employee history data;
grade and grade history data; and functional group data.
team and division data;
tenure data;
diversity data;
performance rating data;
employee history data;
grade and grade history data; and functional group data.
24. A computer-implemented method for promoting employee recognition at an organization, the method comprising:
performing the following operations at one or more computers comprising a memory and a processor:
receiving organizational data of the organization, the organizational data including at least organizational relationship data of a plurality of employees;
receiving recognition details associated with one or more recognition moments;
storing in memory the recognition details and the organizational data; and generating a recognition network graph based on at least the recognition details and the organizational data containing the organizational relationship data, wherein the generated recognition network graph contains a plurality of nodes representing the plurality of employees.
performing the following operations at one or more computers comprising a memory and a processor:
receiving organizational data of the organization, the organizational data including at least organizational relationship data of a plurality of employees;
receiving recognition details associated with one or more recognition moments;
storing in memory the recognition details and the organizational data; and generating a recognition network graph based on at least the recognition details and the organizational data containing the organizational relationship data, wherein the generated recognition network graph contains a plurality of nodes representing the plurality of employees.
25. The method of claim 24, further comprising the step of aggregating at least the recognition details and the organizational data, wherein the recognition network graph is generated based on said aggregating.
26. The method of claim 24, further comprising the step of associating a first node and a second node with at least one recognition moment and at least a portion of the organizational data, the second node connected to the first node by a graphical link.
27. The method of claim 26, wherein the graphical link represents at least one of recognition moments received by a first employee from a second employee and recognition moments received by the second employee from the first employee.
28. The method of claim 26, wherein the graphical link corresponds to the stored recognition details.
29. The method of claim 26, further comprising the step of determining an employee connection score based on the recognition details and organizational data.
30. The method of claim 29, wherein the shape, size or color of the first node is based on at least the determined employee connection score.
31. The method of claim 29, wherein the shape, thickness or color of the graphical link is based on at least the determined employee connection score.
32. The method of claim 24, wherein the recognition network graph contains a focus node representing a first employee, the focus node being located at a general center location of the recognition network graph and connected to a plurality of connected nodes by a plurality of graphical links in accordance with at least the recognition details and the organizational data.
33. The method of claim 32, wherein in response to the selection of a second employee, the recognition graph module generates a second recognition network graph containing a second focus node located at a general center location of the second recognition network graph, the second focus node representing the second employee.
34. The method of claim 24, further comprising the step of generating at least one of the following:
a performance graph depicting employee performance of at least some of the plurality of employees;
an influence graph depicting the relative organizational influence of at least some of the plurality of employees; and a performance alignment graph depicting the alignment of the recognition moments against performance ratings associated with performance reviews for at least some of the plurality of employees.
a performance graph depicting employee performance of at least some of the plurality of employees;
an influence graph depicting the relative organizational influence of at least some of the plurality of employees; and a performance alignment graph depicting the alignment of the recognition moments against performance ratings associated with performance reviews for at least some of the plurality of employees.
35. The method of claim 34, wherein the performance graph is generated based at least one of: a determined employee connection score, the number of recognition moments for each employee, and an economic value of recognition moments.
36. The method of claim 34, wherein the influence graph is generated based on at least one of the following recognition details:
number of recognition moments;
source of the recognition moments;
employee connection score; and employee performance rating.
number of recognition moments;
source of the recognition moments;
employee connection score; and employee performance rating.
37. The method of claim 34, wherein the influence graph contains a first node representing a first employee on a first team, and the position of a first node within the influence graph is based on recognition details including:
an internal employee connection score calculated using the recognition moments associated with the first employee and employees part of the first team; and an external employee connection score calculated based on recognition moments associated with the first employee and employees not part of the first team.
an internal employee connection score calculated using the recognition moments associated with the first employee and employees part of the first team; and an external employee connection score calculated based on recognition moments associated with the first employee and employees not part of the first team.
38. The method of claim 34, wherein the performance alignment graph contains a first node representing a first employee, and the position of a first node within the performance alignment graph is based on at least a recognition connection score and a performance review rating of the first employee.
39. The method of claim 24, wherein the recognition details comprise one or more of a creator, a recipient, an award, an award reason, a role relationship, a performance indicator, a scope of accomplishment, a recognition category, a message; recognition reason data;
recognition nominator data; recognition nominee data; recognition profile and activities data;
sphere of influence data; validation data; composition of recognition message data; approval data; and recognition distribution data.
recognition nominator data; recognition nominee data; recognition profile and activities data;
sphere of influence data; validation data; composition of recognition message data; approval data; and recognition distribution data.
40. The method of claim 24, wherein the recognition graph module is further configured to automatically regenerate the recognition network graph in response to receiving new recognition details associated with new recognition moments, the recognition graph module regenerating the recognition network graph based on the new recognition details.
41. The method of claim 24, further comprising the step of automatically transmitting the recognition details to one or more computing devices upon the receiving of the recognition details, wherein the transmitting causes at least some of the recognition details to be automatically displayed at the one or more computing devices.
42. The method of claim 24, further comprising the steps of:
automatically processing the recognition details and the organizational data to generate recognition analytics results;
determining employees part of a manager's team; and generating a talent analysis user interface containing the generated recognition analytics results associated with the employees part of the manager's team.
automatically processing the recognition details and the organizational data to generate recognition analytics results;
determining employees part of a manager's team; and generating a talent analysis user interface containing the generated recognition analytics results associated with the employees part of the manager's team.
43. The method of claim 24, wherein the organizational data comprises at least one of:
team and division data;
tenure data;
diversity data;
performance rating data;
employee history data;
grade and grade history data; and functional group data.
team and division data;
tenure data;
diversity data;
performance rating data;
employee history data;
grade and grade history data; and functional group data.
44. A computer-implemented method for promoting employee recognition at an organization, the method comprising:
performing the following operations at one or more computers comprising a memory and a processor:
receiving organizational data of the organization, the organizational data including at least organizational relationship data of a plurality of employees;
receiving recognition details associated with one or more recognition moments;
automatically transmitting the recognition moments to a client device upon the receiving of the recognition details for display in a recognition feed to a user;
discarding a portion of the plurality of recognition feeds; and presenting an un-discarded portion of the plurality of recognition feeds.
performing the following operations at one or more computers comprising a memory and a processor:
receiving organizational data of the organization, the organizational data including at least organizational relationship data of a plurality of employees;
receiving recognition details associated with one or more recognition moments;
automatically transmitting the recognition moments to a client device upon the receiving of the recognition details for display in a recognition feed to a user;
discarding a portion of the plurality of recognition feeds; and presenting an un-discarded portion of the plurality of recognition feeds.
45. The method of claim 44, wherein discarding the portion of the plurality of recognition feeds comprises comparing the recognition feeds to a watch list.
46. The method of claim 45, further comprising, adding an entry to the watch list based on a recognition network graph.
47. The method of claim 46, wherein said entry is added to the watch list based on the recognitions received from or provided to another user in accordance with at least one recognition feed.
48. The method of claim 45, further comprising, adding an entry to the watch list based on a selection by the user.
Applications Claiming Priority (3)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| US201161568999P | 2011-12-09 | 2011-12-09 | |
| US61/568,999 | 2011-12-09 | ||
| PCT/US2012/068549 WO2013086399A1 (en) | 2011-12-09 | 2012-12-07 | Systems and method for analyzing recognition data for talent and culture discovery |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CA2865890A1 true CA2865890A1 (en) | 2013-06-13 |
Family
ID=48574935
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CA2865890A Abandoned CA2865890A1 (en) | 2011-12-09 | 2012-12-07 | Systems and methods for analyzing recognition data for talent and culture discovery |
Country Status (4)
| Country | Link |
|---|---|
| CA (1) | CA2865890A1 (en) |
| GB (1) | GB2511013A (en) |
| HK (1) | HK1199969A1 (en) |
| WO (1) | WO2013086399A1 (en) |
Families Citing this family (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US9463383B2 (en) | 2013-08-22 | 2016-10-11 | Pf Loop Inc. | Computer system and method for generating, exchanging, and valuing social currency |
| WO2015179549A1 (en) * | 2014-05-20 | 2015-11-26 | O.C. Tanner Company | Systems and methods for providing recognition to an individual |
| US10361979B2 (en) | 2014-08-08 | 2019-07-23 | Pf Loop Inc. | Computer system and method for adding attributes to an electronic message on behalf of the message's sender |
| US20160371625A1 (en) * | 2015-06-16 | 2016-12-22 | Globoforce Limited | Systems and methods for analyzing recognition data for talent and culture discovery |
Family Cites Families (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20080102422A1 (en) * | 2006-10-20 | 2008-05-01 | Hayes Marcus P | Method of and systems for business and narrative development |
| US20090276296A1 (en) * | 2008-05-01 | 2009-11-05 | Anova Innovations, Llc | Business profit resource optimization system and method |
| BRPI0917246A2 (en) * | 2008-08-04 | 2015-11-10 | Quid Inc | method and system for measuring an entity's performance, computer readable medium, and methods for determining a competitive landscape for entities in an industry, for connecting competitive entities in an industry, and for predicting an entity's future performance |
| WO2010045456A1 (en) * | 2008-10-15 | 2010-04-22 | Workscape. Inc. | Performance driven compensation for enterprise-level human capital management |
-
2012
- 2012-12-07 GB GB1410082.0A patent/GB2511013A/en not_active Withdrawn
- 2012-12-07 CA CA2865890A patent/CA2865890A1/en not_active Abandoned
- 2012-12-07 WO PCT/US2012/068549 patent/WO2013086399A1/en active Application Filing
-
2015
- 2015-01-12 HK HK15100285.7A patent/HK1199969A1/en unknown
Also Published As
| Publication number | Publication date |
|---|---|
| HK1199969A1 (en) | 2015-07-24 |
| WO2013086399A1 (en) | 2013-06-13 |
| GB2511013A (en) | 2014-08-20 |
| GB201410082D0 (en) | 2014-07-23 |
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Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| EEER | Examination request |
Effective date: 20171115 |
|
| FZDE | Discontinued |
Effective date: 20210831 |
|
| FZDE | Discontinued |
Effective date: 20210831 |