Granted Patent B2

US 12,423,635 · App. 17/504,176 · Granted Sep 23, 2025

Inventors: Jeffrey A. Rau (Celebration, FL); Blair K. Martlaro (Belle Isle, FL); Steven Harrop (Winter Garden, FL); Christopher P. Duran (Polk City, FL); Jason J. Isley (Mountlake Terrace, WA)

Assignee: DISNEY ENTERPRISES, INC.

G06Q10/0635G06F11/008G06N5/04

Abstract

Claims (69)

1. A method, comprising:

training a machine learning model on historical technology change data relating to a plurality of technology items in a technology infrastructure, the historical technology change data comprising data relating to at least one of:

(i) prior technology changes applied to the plurality of technology items,

(ii) incident data generated by the prior technology changes, and

(iii) success or failure metrics associated with the prior technology changes;

identifying a planned change to a technology item in the technology infrastructure;

generating, by a controller and using the machine learning model, a plurality of components of a change confidence rating for a risk of failure for the planned change to the technology item, wherein the plurality of components comprises:

an implementer component that is determined based on results of the prior technology changes by an implementer or a coordinator of the planned change,

a process component that is determined based on prior process problems relating to the coordinator of the planned change or an approval group for the planned change, and

a technology component that is determined based on the results of the prior technology changes relating to the technology item or a related technology item;

generating the change confidence rating based on the plurality of components;

processing the change confidence rating, by the controller automatically and in real-time, to identify one or more characteristics of the planned change that impact the change confidence rating relative to one or more other characteristics of the planned change; and

modifying, by the controller automatically and based on the change confidence rating and the one or more characteristics, at least one of (i) a time of an implementation of the planned change within the technology infrastructure or (ii) a level of risk that is stored in a repository and associated with one or more users included in a user group to which the planned change is applied.

2. The method of claim 1 , wherein the technology item comprises a hardware item or software item in an information technology (IT) infrastructure.

3. The method of claim 1 , wherein the implementer component is determined based on at least one of a change volume, a number of historical changes causing incidents, a historical change success rate, or a fatigue factor associated with the implementer or the coordinator of the planned change.

4. The method of claim 1 , wherein the implementer component is based on the results of the prior technology changes for all of:

(i) the coordinator tasked with managing the implementation of the planned change,

(ii) a coordinator group of people that includes the coordinator,

(iii) the implementer of the planned change, and

(iv) an implementer group of people that includes the implementer.

5. The method of claim 1 , wherein the process component is based on at least one of a change volume, revert codes, a lead time, process exceptions, prior change success rates, or non-closed change records relating to the coordinator of the planned change or the approval group for the planned change.

6. The method of claim 1 , wherein:

the technology component is based on the results of the prior technology changes relating to the technology item and the related technology item, and

the related technology item is provided by a same entity as the technology item.

7. The method of claim 1 , wherein:

the technology component is based on incident history information, problem history information, and change history information associated with the related technology item or the technology item.

8. The method of claim 1 , further comprising generating an alert indicating a high level of risk based on the change confidence rating.

9. A non-transitory computer-readable medium containing computer program code that, when executed by operation of one or more computer processors, performs operations comprising:

training a machine learning model on historical technology change data relating to a plurality of technology items in a technology infrastructure, the historical technology change data comprising data relating to at least one of:

(i) prior technology changes applied to the plurality of technology items,

(ii) incident data generated by the prior technology changes, and

(iii) success or failure metrics associated with the prior technology changes;

identifying a planned change to a technology item in the technology infrastructure;

generating, by a controller and using the machine learning model, a plurality of components of a change confidence rating for a risk of failure for the planned change to the technology item, wherein the plurality of components comprises:

an implementer component that is determined based on results of the prior technology changes by an implementer or a coordinator of the planned change,

a process component that is determined based on prior process problems relating to the coordinator of the planned change or an approval group for the planned change, and

a technology component that is determined based on results of prior technology changes relating to the technology item or a related technology item;

generating the change confidence rating based on the plurality of components;

processing the change confidence rating, by the controller automatically and in real-time, to identify one or more characteristics of the planned change that impact the change confidence rating relative to one or more other characteristics of the planned change; and

modifying, by the controller automatically and based on the change confidence rating and the one or more characteristics, at least one of (i) a time of an implementation of the planned change within the technology infrastructure or (ii) a level of risk that is stored in a repository and associated with one or more users included in a user group to which the planned change is applied.

10. The non-transitory computer-readable medium of claim 9 , wherein the technology item comprises a hardware item or software item in an information technology (IT) infrastructure.

11. The non-transitory computer-readable medium of claim 9 , wherein the implementer component is determined based on at least one of a change volume, a number of historical changes causing incidents, a historical change success rate, or a fatigue factor associated with the implementer or the coordinator of the planned change.

12. The non-transitory computer-readable medium of claim 9 , wherein:

the implementer component is based on the results of the prior technology changes for all of:

(i) the coordinator tasked with managing the implementation of the planned change,

(ii) a coordinator group of people that includes the coordinator,

(iii) the implementer of the planned change, and

(iv) an implementer group of people that includes the implementer,

the process component is based on the prior process problems relating to the coordinator of the planned change and the approval group for the planned change,

the technology component is based on the results of the prior technology changes relating to the technology item and the related technology item, and

the related technology item is provided by a same entity as the technology item.

13. A system, comprising:

a computer processor; and

a memory having instructions stored thereon which, when executed on the computer processor, performs operations comprising:

training a machine learning model on historical technology change data relating to a plurality of technology items in a technology infrastructure, the historical technology change data comprising data relating to at least one of:

(i) prior technology changes applied to the plurality of technology items,

(ii) incident data generated by the prior technology changes, and

(iii) success or failure metrics associated with the prior technology changes;

identifying a planned change to a technology item in the technology infrastructure;

generating, by a controller and using the machine learning model, a plurality of components of a change confidence rating for a risk of failure for the planned change to the technology item, wherein the plurality of components comprises:

an implementer component that is determined based on results of the prior technology changes by an implementer or a coordinator of the planned change,

a process component that is determined based on prior process problems relating to the coordinator of the planned change or an approval group for the planned change, and

a technology component that is determined based on the results of the prior technology changes relating to the technology item or a related technology item;

generating the change confidence rating based on the plurality of components;

processing the change confidence rating, by the controller automatically and in real-time, to identify one or more characteristics of the planned change that impact the change confidence rating relative to one or more other characteristics of the planned change; and

modifying, by the controller automatically and based on the change confidence rating and the one or more characteristics, at least one of (i) a time of an implementation of the planned change within the technology infrastructure or (ii) a level of risk that is stored in a repository and associated with one or more users included in a user group to which the planned change is applied.

14. The system of claim 13 , wherein the technology item comprises a hardware item or software item in an information technology (IT) infrastructure.

15. The system of claim 13 , wherein the operations further comprise generating a user interface illustrating a risk level for the planned change.

16. The system of claim 15 , wherein the operations further comprise initiating a supplemental review of the planned change.

Assignments (1)

Continuity (1)

References Cited (10)