ServiceNow
Sprint scores and PI objectives are exported on demand as JSON.
Automation of sprint score and PI objective transfers between platforms, replacing manual entry with an on-demand, validated and controlled workflow.
The flow receives data exported from ServiceNow, interprets the JSON, maps each piece of information to the correct destination and updates Jira only after the required validations.
Sprint scores and PI objectives are exported on demand as JSON.
The exported content is read as structured data, not as text to be manually copied.
Interprets, maps and validates the data before writing to the destination.
Information reaches the correct projects and fields after authentication and validation.
Manual data-by-data transfer is replaced by a controlled execution with validation before each update.
Scores and objectives were checked and transferred manually between platforms, consuming hours of work and increasing the risk of errors.
The file is processed by the application, mappings are checked and updates happen directly in Jira.
Human intervention is concentrated on export and execution; processing, mapping and validation are handled by the application.
Sprint scores and PI objectives were available in ServiceNow, but had to be transferred to Jira item by item.
The process required checking source data, locating the correct destination in Jira and repeating the same operation many times. Beyond the time spent, any project, field or value error could compromise the update.
The most important work was not simply “sending a JSON”. It was understanding the structure, correctly mapping projects and fields, and validating everything until mappings reached 100% alignment.
The JSON was analyzed to identify scores, objectives, projects and other relevant information.
Each data point was associated with the correct Jira project and field before automation took over the process.
The application checks mappings and only proceeds when the expected mapping is consistent.
Credentials are requested when the application starts and are not embedded in the code.
JSON is interpreted as a data source without relying on manual copying.
Information is routed to the correct Jira destinations according to previously validated rules.
The flow checks mappings before writing data to the destination system.
The integration can be triggered whenever needed, since there is no fixed update schedule.
The solution turns a manual cross-platform transfer into a structured, validated and repeatable workflow — reducing operational effort and increasing confidence in updates.
The robustness of the flow comes from correct mapping, validation and the way the application handles authentication and writing to the destination.
Classifications were built manually until source and destination were 100% aligned. After that, the application took over validation.
Before running, the application asks the user to authenticate. Login and password are not embedded in the implementation.
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