Case Stage Performance

Overview

The Case Stage Performance calculator monitors the performance of specific process stages and identifies cases that remain in a stage longer than expected. A process stage is defined as the time between two selected events, allowing you to track how long cases spend in critical phases of your workflow. This calculator helps you detect bottlenecks, identify at-risk cases, and monitor stage-specific SLAs.

Common Uses

  • Monitor the time cases spend in approval stages and identify those exceeding approval SLAs
  • Track cases stuck in "pending documentation" or "waiting for customer response" stages
  • Analyze the duration of critical production or manufacturing stages
  • Identify cases that have been in a review stage beyond acceptable timeframes
  • Alert on cases requiring escalation due to extended stage duration
  • Measure stage-specific performance across different case categories

Settings

Stage Start Event Attribute: Select the attribute that defines the beginning of the stage (typically 'Activity Name').

Stage Start Value: Select the specific event value that marks when cases enter the stage (e.g., "Submit for Approval").

Stage End Event Attribute: Select the attribute that defines the end of the stage (typically 'Activity Name').

Stage End Value: Select the specific event value that marks when cases exit the stage (e.g., "Approval Completed").

Threshold Duration: Specify the maximum acceptable duration for cases to remain in this stage. Cases exceeding this threshold will be highlighted for attention.

Threshold Unit: Select the time unit for the threshold:

  • Hours
  • Days
  • Weeks

Group By (optional): Select a categorical attribute to analyze stage performance across different categories (e.g., by Department, Product Type, or Priority Level).

Examples

Example 1: Monitoring Approval Stage Performance

Scenario: You want to monitor how long purchase orders spend in the approval stage and identify those that have been waiting for approval for more than 3 days.

Settings:

  • Stage Start Event Attribute: Activity Name
  • Stage Start Value: Submit for Approval
  • Stage End Event Attribute: Activity Name
  • Stage End Value: Approval Completed
  • Threshold Duration: 3
  • Threshold Unit: Days

Output:

The calculator displays performance metrics for the approval stage:

Summary Statistics:

  • Total cases in stage: 1,245
  • Average stage duration: 1.8 days
  • Median stage duration: 1.2 days
  • Cases exceeding threshold: 87 cases (7%)

Cases Exceeding Threshold: A detailed list of the 87 purchase orders that have been in approval for more than 3 days, including:

  • Case ID
  • Current duration in stage
  • Days over threshold
  • Additional case attributes for context

Insights:

This reveals that while most purchase orders are approved within 1-2 days, 7% are experiencing delays beyond the 3-day threshold. The list of specific cases enables immediate action:

  • Route delayed cases to management for escalation
  • Identify patterns in delayed approvals (large amounts, specific approvers, certain vendors)
  • Measure the impact of approval delays on overall case duration
  • Set up automated alerts for cases approaching or exceeding the threshold

Example 2: Production Stage Analysis by Product Category

Scenario: You want to analyze how long different product types spend in the manufacturing stage and identify which categories consistently exceed the standard 5-day production window.

Settings:

  • Stage Start Event Attribute: Activity Name
  • Stage Start Value: Production Started
  • Stage End Event Attribute: Activity Name
  • Stage End Value: Production Completed
  • Threshold Duration: 5
  • Threshold Unit: Days
  • Group By: Product Category

Output:

The calculator breaks down production stage performance by product category:

Product Category Cases Avg Duration Cases Over Threshold % Over Threshold
Electronics 450 6.2 days 210 47%
Furniture 320 4.1 days 45 14%
Textiles 280 3.8 days 32 11%
Hardware 195 7.4 days 145 74%

Insights:

The category breakdown reveals significant variation in production stage performance:

  • Hardware products have the highest failure rate (74% exceed threshold), with an average duration of 7.4 days - indicating possible capacity constraints or process complexity issues
  • Electronics also struggle, with 47% exceeding the 5-day window
  • Furniture and Textiles perform better, staying within the threshold for most cases

This analysis enables targeted improvements:

  • Investigate why Hardware takes longest and has highest threshold violation rate
  • Consider adjusting thresholds by category to reflect realistic production timelines
  • Allocate additional resources to problematic categories
  • Implement category-specific process improvements

Example 3: Customer Response Wait Time Monitoring

Scenario: You're managing a customer service process and want to identify support tickets that have been waiting for customer response for more than 48 hours, which triggers an automatic close policy.

Settings:

  • Stage Start Event Attribute: Activity Name
  • Stage Start Value: Awaiting Customer Response
  • Stage End Event Attribute: Activity Name
  • Stage End Value: Customer Response Received
  • Threshold Duration: 48
  • Threshold Unit: Hours

Output:

The calculator identifies tickets at risk of automatic closure:

Current Status:

  • Total tickets awaiting response: 234
  • Average wait time: 18.5 hours
  • Tickets over 48 hours: 23 tickets (9.8%)

Critical Tickets List: The 23 tickets that have exceeded 48 hours and are candidates for automatic closure, showing:

  • Ticket ID and customer name
  • Hours waiting (e.g., 52 hours, 67 hours, 118 hours)
  • Original issue category
  • Last contact timestamp

Insights:

This analysis supports proactive customer relationship management:

  • Identify which customers may lose access to their support tickets
  • Send final reminder emails before auto-closure
  • Recognize patterns in non-responsive customers (specific issue types, customer segments)
  • Measure the effectiveness of customer communication
  • Adjust auto-close policies based on actual response patterns

The calculator helps balance operational efficiency (closing inactive tickets) with customer satisfaction (ensuring adequate response time before closure).

Output

The calculator provides comprehensive stage performance analytics:

Summary Metrics:

  • Total number of cases currently in or having passed through the stage
  • Average, median, minimum, and maximum stage durations
  • Count and percentage of cases exceeding the threshold
  • Stage completion rate

Threshold Violation Details:

  • Complete list of cases exceeding the threshold
  • Sortable by duration, days over threshold, or any case attribute
  • Drill-down capability to examine individual case details
  • Export functionality for further analysis or alerting workflows

Visual Representations:

  • Distribution histogram showing stage duration frequency
  • Trend charts showing stage performance over time
  • Category comparisons (when Group By is used)

Interactive Filtering:

  • Click on any case to view its complete process path
  • Filter the case list by various attributes
  • Export violation list for escalation or reporting

This calculator is particularly valuable for operational monitoring, SLA compliance, and proactive case management in time-sensitive processes.


This documentation is part of the mindzie Studio process mining platform.

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