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Performance Page

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Revision as of 10:58, 15 August 2025 by Hendry.mwamburi (talk | contribs)

Summary

This Power BI report provides a centralized view of service ticket performance across entities. It combines API-sourced data, calculated metrics, and user-interactive filters to enable monitoring of resolution efficiency, root cause trends, and corrective action effectiveness. The report supports operational decision-making, performance tracking, and process improvement initiatives

Filters

Filter Description
Date picker Allows users to filter the dataset by a specific date or date range.
Entity slicer Enables users to filter the report by entity ( Business unit)
Resolution Status Filters data by the status of a case, issue, or task (e.g. Resolved, Not Resolved).

Data Transformation Applied

Query Transformations
Entity table API link =https://customer-service.datacair.com/api/ticket/customfield/6
  • Default Behavior: The API returns a maximum of 50 records per request unless otherwise specified.
Root cause table API link =https://customer-service.datacair.com/api/ticket/customfield/5
  • Default Behavior: The API returns a maximum of 50 records per request unless otherwise specified.
Corrective Action table API link =https://customer-service.datacair.com/api/ticket/customfield/4
  • Default Behavior: The API returns a maximum of 50 records per request unless otherwise specified.

Calculations

Columns Calculation Description
1. Total tickets by resolution time Total Tickets =

DISTINCTCOUNT ( 'Performance and Root Cause'[Ticket Number] )

This metric tracks the number of support or service tickets resolved within specified time intervals. It provides insight into the efficiency of the resolution process, helping identify trends, bottlenecks, and opportunities for process improvement.
2. Total tickets by Root cause Total Tickets =

DISTINCTCOUNT ( 'Performance and Root Cause'[Ticket Number] )

This metric measures the number of tickets categorized by their underlying root cause. It is used to identify recurring issues, prioritize fixes, and prevent similar incidents in the future.
3. Total tickets by Corrective Action Total Tickets =

DISTINCTCOUNT ( 'Performance and Root Cause'[Ticket Number] )

This metric measures the number of tickets categorized by the corrective action taken to resolve them. It helps evaluate the effectiveness of remediation strategies and supports continuous improvement in service delivery.
4. Breaks down tickets performance life cycle by:
  • Ticket Number
  • Channel
  • Priority
  • User
  • Reason
  • Root Cause
  • Corrective Action
  • Creation Date
  • Resolved Date
  • Status
  • Days
  • Hours
  • Minutes
  • Ticket Number is system-generated by the ticketing platform.
  • Channel is Captured automatically at ticket creation.
  • Priority is Set manually by agent or automatically based on predefined rules.
  • User is Captured from ticket submission form or authentication data.
  • Reason is Entered by user or agent when ticket is logged.
  • Root cause is Selected by agent during or after resolution based on analysis.
  • Corrective Action is Recorded by the resolving agent at ticket closure.
  • Creation Date is Captured automatically when ticket is created.
  • Status is Updated automatically by the system or manually by agent.
  • Days=⌊Resolved Date−Creation Date⌋
  • Hours=⌊((Resolved Date−Creation Date)×24)mod24⌋
  • Minutes = [((Resolved Date - Creation Date) * 1440) mod 60]
 This table contains detailed records of service tickets, including metadata, categorization, and time-based metrics. It serves as the foundation for operational reporting, performance tracking, and root cause analysis.
  • Provide a comprehensive view of each ticket’s lifecycle.
  • Support performance measurement and service quality analysis.
  • Enable trend identification and process improvement initiatives.
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