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Status Future consideration
Created by Guest
Created on Feb 12, 2024

Insights into the failed messages on inflight Dashborad

Priority

High

Ask

Insights into the failed messages on inflight

Details of Ask

Provide insights into failed transactions, by providing further categorization on failed transaction .

Grouping of failures based on sender/receiver ID combination based on error types to pinpoint unique errors, and indicating the how long these errors in the system.

Example: Total Translation failures 100:

i) Sender “ABC” /Receiver “XYZ” : Mandatory data missing: 50 (Map name:xxx , Oldest failure date/time )

ii) Sender “ABC” /Receiver “XYZ” Doc Type : Envelope Failure 25 (Missing Envelope, Oldest failure date/time)

iii) Sender “123” /Receiver “879” Doc Type : Protocol failures :25 (PPID, Oldest Failure date/time)

Impact to Clients

Manually examining each repetitive failure, is extremely time-consuming

Leads to Customer dissatisfaction

Impact to Support

Capable of promptly identifying distinct error types from numerous failures

Reduce Support efforts

Current Challenge

Reviewing every error is a duplicate effort and time consuming

Use Case

When encountering serval failures, identifying unique issues helps to expedites faster issue resolution.

Knowing the age of the failures helps customers/Support to focus on resolving them.

  • Guest
    Reply
    |
    Sep 18, 2024

    Priority

    High

    Ask

    Insights into the failed messages on inflight

    Details of Ask

    Provide insights into failed transactions, by providing further categorization on failed transaction .

    Grouping of failures based on sender/receiver ID combination based on error types to pinpoint unique errors, and indicating the how long these errors in the system.

    Example: Total Translation failures 100:

                   i) Sender “ABC” /Receiver “XYZ” : Mandatory data missing: 50 (Map name:xxx , Oldest failure date/time )

                   ii) Sender “ABC” /Receiver “XYZ”  Doc Type :  Envelope Failure 25  (Missing Envelope, Oldest failure date/time)

                   iii) Sender “123” /Receiver “879”  Doc Type : Protocol failures :25    (PPID, Oldest Failure date/time)

    Impact to Clients

    Manually examining each repetitive failure, is extremely time-consuming

    Leads to Customer dissatisfaction

    Impact to Support

     

    Capable of promptly identifying distinct error types from numerous failures

    Reduce Support efforts

    Current Challenge

    Reviewing every error is a duplicate effort and time consuming

    Use Case

     

    When encountering serval failures, identifying unique issues helps to expedites faster issue resolution.

    Knowing the age of the failures helps customers/Support to focus on resolving them.

  • Guest
    Reply
    |
    Mar 4, 2024

    From Dashboard Support/Customer should be able to drill down to transaction level to work on the issues. 

    Translation failure :Grouping based on  Sender/Receiver/Doc Type /Map name /Direction/Source of the message will help to narrow down the Unique Error Types.

    Protocol Failures: Grouping Protocol Failures transaction based on the PPID messages are delivered and Error message 

    Envelope Failures: Grouping failures based on the Missing envelope failures.

     

  • Guest
    Reply
    |
    Feb 23, 2024

    Along with grouping based on error types and if we can also have insights into from how long this issue exist in the system ,will help to Identify the repetitive issues which can help support to concentrate on reducing the repetitive errors in the system.

    This will save efforts to support teams