Servicenow, Inc.

Hans Jochen Gerhard Pohle

Manjeet Singh

Ciprian Mocanu

Vadim Denisov

Fabio Casati

Sai Harini Chettla

Siddhant Sinha

A system for root cause analysis based on process optimization data is provided. The system receives log data associated with a first trace between a first activity and a second activity of a process. The system further determines a state of inefficiency between the first activity and the second activity based on the received log data. The system further applies a first machine learning (ML) model on the received log data. The system further determines a first label and a first value to be associated with the first trace of the process based on the application of the first ML model. The system further generates presentation data associated with the determined state of inefficiency of the first trace based on the determination of the first label and the first value and further transmits the generated presentation data on a user device.

Root cause analysis based on process optimization data

An embodiment may involve a server-side log collected by a server device, where the server-side log includes a set of entries indicating a unique identifier, and wherein the unique identifier is assigned to a work item of a server-based application executed by the server device. The embodiment may further involve one or more processors configured to: receive, from a client device disposed upon a network, a client-side log, wherein the client-side log includes operational data related to usage of a client-based application executed by the client device; identify, from the operational data, the client-based application and one or more activities performed by the client-based application; determine that the one or more activities are related to the unique identifier; based on the one or more activities, determine an action that can be taken to improve efficacy of the server-based application; and write, to the persistent storage, a representation of the action.

Server-side workflow improvement based on client-side data mining

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Amsterdam, Netherlands

Hans Jochen Gerhard Pohle