- Number
- 12423635
- Published
- 2025-09-23
- Filed
- 2021-10-18
- Assignee
- DISNEY ENTERPRISES, INC.
- Inventors
- Rau; Jeffrey A. et al.
- CPC
- G06F11/008; G06Q10/0635; G06N5/04
- Verdict
- Set aside IT change-management tooling, business
- Source
- Google Patents · FreePatentsOnline
Abstract
Techniques for identifying a risk of failure for a planned change to a technology item in a technology infrastructure are disclosed. Historical technology change data are retrieved, including data relating to at least one of: (i) prior technology changes by an implementer or coordinator of the planned change, (ii) a process relating to the planned change, or (iii) prior technology changes relating to the technology item or a related technology item. A change confidence rating for a risk of failure for the planned change is generated, based on the historical technology change data. The change confidence rating is applied, including at least one of: (i) generating a user interface illustrating a risk level for the technology change, (ii) flagging for or initiating a supplemental review of the technology change, or (iii) recommending implementer training relating to the technology change.
Background
BACKGROUND (1) Scheduled information technology (IT) changes carry varying levels of risk. For example, some changes are expected to impact large user sets or critical technology infrastructure, and so are likely to be deemed, by an observer (e.g., an IT professional) to have a relatively high risk of failure or negative organizational impact. Other changes are expected to have only a limited impact, and so are likely to be deemed relatively low risk by an observer. These risk assessments are typically based on a human analysis of a limited number of factors, and may be incorrect. SUMMARY (2) Embodiments include a method. The method includes identifying a planned change to a technology item in a technology infrastructure. The method further includes retrieving historical technology change data relating to the technology item and the planned change, the historical technology change data including data relating to at least one of: (i) prior technology changes by an implementer or coordinator of the planned change, (ii) a process relating to the planned change, or (iii) prior technology changes relating to the technology item or a related technology item. The method further includes generating a change confidence rating for a risk of failure for the planned change, based on the historical technology change data. The method further includes applying the change confidence rating, including at least one of: (i) generating a user interface illustrating a risk level for the technolog
Claims
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. ||
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. ||
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.