OBJECTIVELY CHARACTERIZING INTERVENTION IMPACTS

• US 20170256173A1
• Filed: 03/01/2016
• Published: 09/07/2017
• Est. Priority Date: 03/01/2016
• Status: Active Grant

• Current Assignee: Accenture Global Solutions Limited (Accenture PLC)
• Original Assignee: Accenture Global Solutions Limited (Accenture PLC)
• Inventors: BURFORD, Kelly
• Granted Patent: US 10,026,330 B2
• Time in Patent Office: Days
• CPC Class Codes: G06F 16/248 Presentation of query results
• CPC Class Codes: G06F 16/9535 Search customisation based on user profiles and personalisation
• CPC Class Codes: G06N 20/00 Machine learning
• CPC Class Codes: G09B 19/00 Teaching not covered by other main groups of this subclass teaching or practice apparatus for gun-aiming or gun-laying F41G3/26
• CPC Class Codes: G09B 5/06 with both visual and audible presentation of the material to be studied
• CPC Class Codes: G09B 5/125 the stations being mobile

Abstract

The disclosed embodiments include computerized methods and systems, including computer programs encoded on a computer storage medium, for objectively characterizing an impact of an intervention on individuals or groups. For example, a computing system may obtain, and store in a data lake, intervention data identifying interventions, and objective data characterizing an impact of these interventions on at least one individual. The computer system may also populate a queryable interface with query parameters (e.g., at least one of the interventions and at least a portion of the objective data), which may be presented to a user via a device. The computer system may obtain stored intervention and objective data consistent with a received query, which may be provided to the device for presentation to the user. The disclosed embodiments also provide a visual representation of trends in the stored data and candidate interventions the address the identified trends without user input.

Claims

1. An apparatus, comprising:

at least one processor; and

a memory storing executable instructions that, when executed by the at least one processor, causes the at least one processor to perform the steps of;

storing first and second data within a data repository, the first data identifying a plurality of interventions, and the second data characterizing an impact of the interventions on at least one individual;

based on at least a portion of the first and second data, establishing candidate query parameters for a queryable interface, the candidate query parameters identifying the interventions, the at least one individual, and portions of the second data;

providing the candidate query parameters to a client device for presentation within the queryable interface;

receiving, from the client device, query data comprising at least a portion of the candidate query parameters, the portion of the candidate query parameters identifying at least one of the interventions and at least a portion of the second data;

querying the data repository to obtain data consistent with the received portion of the candidate query parameters; and

providing the obtained data to the client device, the client device being configured to present a visual representation of obtained data within the queryable interface, and the visual representation objectively characterizing an impact of the at least one intervention on the at least one individual.

2. The apparatus of claim 1, wherein the data repository comprises at least one data lake, the at least one data lake having a corresponding processing engine.

3. The apparatus of claim 1, wherein the at least one processor further performs the steps of:

obtaining at least a portion of the first data from one or more databases; and

obtaining at least a portion of the second data from one or more devices.

4. The apparatus of claim 3, wherein:

the one or more databases are maintained by at least one of a learning management system platform, an enterprise resource management system, or a social-media system; and

the one or more devices comprise at least one of an loT connected device, a workstation, a mobile communications device, or a radio-frequency (RF) device.

5. The apparatus of claim 4, wherein the loT connected device comprises a wearable device, the wearable device comprising at least one of a biometric sensor or an environmental sensor.

6. The apparatus of claim 3, wherein the at least one processor further performs the step of establishing a secure communications session with at least one of the one or more databases or the one or more devices through an application programming interface (API).

7. The apparatus of claim 1, wherein the plurality of interventions comprise at least one of a purposeful or non-purposeful action impacting the at least one individual.

8. The apparatus of claim 1, wherein the plurality of interventions comprise at least one of (i) a training program in which the at least one individual participates, (ii) a change in a configuration of a workplace of the at least one individual, (iii) scheduled or unscheduled leave of the at least one individual, (iv) a change in a work schedule of the at least one individual, or (v) a change in a management structure of the workplace of the at least one individual.

9. The apparatus of claim 1, wherein the second data comprises at least one of (i) data indicative of a performance of the at least one individual within a workplace, (ii) data indicative of one or more environmental conditions experienced by the at least one individual, and (iii) biometric data indicative of a physical condition of the at least one individual.

10. The apparatus of claim 1, wherein the at least one processor further performs the steps of:

modifying at least a portion of the first and second data to incorporate corresponding first and second tags, the modification maintaining a native format of the first and second data; and

storing the modified first and second data within the data repository.

11. The apparatus of claim 10, wherein the at least one processor further performs the steps of:

based on at least one of the first or second tags, identifying a portion a least one of the first or second data for presentation within the queryable interface; and

providing the at least one identified portion of the first or second data to the client device, the client device being configured to present a visual representation of at least one of identified portion of the first or second data within the queryable interface without input from the user.

12. The apparatus of claim 1, wherein the at least one processor further performs the step of generating profile data for the at least one individual, the generated profile data comprising one or more identifiers representative of the at least one individual within the first and second data, and holistic data identifying a subset of the interventions that impact the at least one user.

13. The apparatus of claim 12, wherein the at least one processor further performs the steps of:

based on the generated profile data, identifying one or more individuals impacted by the at least one identified intervention; and

querying the data repository to obtain data consistent with the received portion of the candidate query parameters and associated with the one or more identified individuals.

14. The apparatus of claim 1, wherein the at least one processor further performs the steps of:

identifying a trend within the stored first and second data, the identified trend comprising a time variation of at least one of a performance of the at least one individual within a workplace, an environmental condition experienced by the at least one individual, or a physical condition of the at least one individual;

providing data indicative of the identified trend to the client device, the client device being configured to present a visual representation of the identified trend within a portion of the queryable interface without input from the user.

15. The apparatus of claim 14, wherein the at least one processor further performs the steps of:

establishing at least one candidate intervention that mediates or exploits the identified trend; and

providing data indicative of the identified trend and established candidate intervention to the client device, the client device being configured to present a visual representation of the identified trend and established candidate intervention within a portion of the queryable interface without input from the user.

16. The apparatus of claim 15, wherein the at least one processor further performs the steps of:

applying a machine-learning algorithm to at least a portion of the stored first and second data; and

based on an outcome of the applied machine-learning algorithm, establishing the at least one candidate intervention.

17. A computer-implemented method, comprising:

performing, by at least one processor, operations that store first and second data within a data repository, the first data identifying a plurality of interventions, and the second data characterizing an impact of the interventions on at least one individual;

based on at least a portion of the first and second data, establishing, by the at least one processor, candidate query parameters for a queryable interface, the candidate query parameters identifying the interventions, the at least one individual, and portions of the second data;

providing, by the at least one processor, the candidate query parameters to a client device for presentation within the queryable interface;

receiving, by the at least one processor, and from the client device, query data comprising at least a portion of the candidate query parameters, the portion of the candidate query parameters identifying at least one of the interventions and at least a portion of the second data;

querying, by the at least one processor, the data repository to obtain data consistent with the received portion of the candidate query parameters; and

providing, by the at least one processor, the obtained data to the client device, the client device being configured to present a visual representation of obtained data within the queryable interface, and the visual representation objectively characterizing an impact of the at least one intervention on the at least one individual.

18. An apparatus, comprising:

at least one processor; and

a memory storing executable instructions that, when executed by the at least one processor, causes the at least one processor to perform the steps of;

storing first and second data within a data repository, the first data identifying a plurality of interventions, and the second data characterizing an impact of the interventions on at least one individual;

identifying a trend within the stored first and second data, the trend comprising a time variation of at least one of a performance of the at least one individual within a workplace, an environmental condition experienced by the at least one individual, or a physical condition of the at least one individual;

establishing at least one candidate intervention that mediates or exploits the identified trend; and

providing data indicative of the identified trend and established candidate intervention to a client device, the client device being configured to present a visual representation of the identified trend and established candidate intervention within a portion of a queryable interface without input from the user.

19. The apparatus of claim 18, wherein the at least one processor further performs the steps of:

applying a machine-learning algorithm to at least a portion of the stored first and second data; and

based on an outcome of the applied machine-learning algorithm, establishing the at least one candidate intervention.

20. The apparatus of claim 18, wherein the data repository comprises at least one data lake, the at least one data lake having a corresponding processing engine.