Overview
The Process Performance Matrix calculator creates a comprehensive view of your process health by plotting cases based on two critical dimensions: conformance to process standards and performance category. This matrix visualization helps you identify which segments of your process need attention by showing the distribution of cases across eight distinct categories (conformance status x performance level).
The calculator groups cases into a 2x4 matrix where rows represent whether cases have conformance issues (yes/no) and columns represent performance categories (Extreme, Slow, Normal, Fast). Each cell shows the percentage and count of cases, allowing you to quickly identify problematic areas such as slow cases with conformance violations or extremely fast cases that might be cutting corners.
Common Uses
- Identify process segments that require immediate attention (slow performance + conformance issues)
- Detect potential quality shortcuts where cases are fast but have conformance violations
- Balance process improvement efforts between speed optimization and compliance enhancement
- Segment cases for targeted root cause analysis based on combined performance and conformance profiles
- Monitor the overall health of process execution across both efficiency and quality dimensions
- Prioritize improvement initiatives by focusing on high-impact segments (large percentages in problem quadrants)
Settings
Conformance Issue Attribute: Select the boolean case attribute that indicates whether a case has conformance issues. This is typically created by the Conformance Rules enrichment operator. The default is the standard conformance column created when you define process rules. Cases marked "true" have violations, while "false" indicates compliance.
Performance Attribute Name: Select the string case attribute that categorizes cases by performance. This attribute must contain only valid performance category values: "Fast," "Normal," "Slow," or "Extreme." This is typically created by the Duration Categorization enrichment operator, which assigns categories based on case duration thresholds you define.
Examples
Example 1: Analyzing Order Fulfillment Process Health
Scenario: Your order fulfillment process has defined duration thresholds (Fast: under 2 days, Normal: 2-5 days, Slow: 5-10 days, Extreme: over 10 days) and conformance rules (required activities, correct sequence). You want to understand the overall health of the process and identify which segments need improvement.
Settings:
- Conformance Issue Attribute: ConformanceIssue
- Performance Attribute Name: CasePerformance
Output:
The matrix displays eight cells showing the distribution of your 10,000 cases:
No Conformance Issues:
- Extreme (over 10 days): 2% (200 cases)
- Slow (5-10 days): 8% (800 cases)
- Normal (2-5 days): 45% (4,500 cases)
- Fast (under 2 days): 25% (2,500 cases)
Has Conformance Issues:
- Extreme (over 10 days): 5% (500 cases)
- Slow (5-10 days): 10% (1,000 cases)
- Normal (2-5 days): 4% (400 cases)
- Fast (under 2 days): 1% (100 cases)
Insights: This output reveals several important findings. First, 80% of your cases (8,000) have no conformance issues, which is positive. However, the 5% of cases in the "Extreme + Conformance Issues" category (500 cases) should be your top priority - these are both slow and non-compliant. The 10% in "Slow + Conformance Issues" (1,000 cases) is also concerning. Interestingly, 1% of cases are Fast but have conformance issues - these may represent shortcuts where steps are being skipped to achieve speed. The matrix helps you prioritize: focus first on the 15% of cases that are both slow and non-compliant (1,500 cases total), then investigate why fast cases have conformance violations.
Example 2: Invoice Processing Performance Segmentation
Scenario: You've categorized invoice processing cases by duration and applied conformance rules checking for required approvals, correct document matching, and proper sequencing. You want to segment cases for targeted improvement initiatives.
Settings:
- Conformance Issue Attribute: ConformanceIssue
- Performance Attribute Name: InvoiceDurationCategory
Output:
The matrix shows your 5,000 invoice cases distributed across performance and conformance:
No Conformance Issues:
- Extreme: 3% (150 cases) - Very slow but compliant
- Slow: 12% (600 cases) - Slower than target but compliant
- Normal: 50% (2,500 cases) - Target performance, compliant
- Fast: 20% (1,000 cases) - Better than target, compliant
Has Conformance Issues:
- Extreme: 8% (400 cases) - Very slow and non-compliant
- Slow: 5% (250 cases) - Slower than target, non-compliant
- Normal: 1.5% (75 cases) - Normal speed but non-compliant
- Fast: 0.5% (25 cases) - Fast but non-compliant
Insights: This matrix reveals that 85% of your invoices (4,250 cases) are processed without conformance issues, which is good. However, the 8% in the "Extreme + Conformance Issues" category (400 cases) represents your biggest problem area - these invoices are taking too long AND have process violations. You can click on this cell to drill down and investigate common patterns. The 5% in "Slow + Conformance Issues" (250 cases) also needs attention. The small percentage (0.5%) of fast invoices with conformance issues suggests some processors may be skipping approval steps. The 3% of extremely slow but compliant cases (150) might indicate complex invoices that require special handling - these are following the rules but taking a long time, suggesting a process design issue rather than compliance problem.
Example 3: Prioritizing Process Improvement Resources
Scenario: Your process improvement team has limited resources and needs to prioritize which process segments to address first. You use the Process Performance Matrix to make data-driven decisions about where to focus improvement efforts.
Settings:
- Conformance Issue Attribute: ConformanceIssue
- Performance Attribute Name: CasePerformanceCategory
Output:
Matrix showing 8,000 cases:
No Conformance Issues:
- Extreme: 1% (80 cases)
- Slow: 15% (1,200 cases)
- Normal: 55% (4,400 cases)
- Fast: 18% (1,440 cases)
Has Conformance Issues:
- Extreme: 3% (240 cases)
- Slow: 6% (480 cases)
- Normal: 1.5% (120 cases)
- Fast: 0.5% (40 cases)
Insights: This matrix helps you prioritize improvement efforts strategically. The "Extreme + Conformance Issues" segment (3%, 240 cases) is your highest priority - these cases have both quality and speed problems. Next, address the "Slow + Conformance Issues" segment (6%, 480 cases). Together, these two segments represent 9% of cases (720 total) that need both performance and compliance improvements. After addressing these critical segments, you can focus on the 15% of slow but compliant cases (1,200) - these might benefit from process optimization while maintaining quality. The 1% of extremely slow compliant cases (80) might be edge cases requiring different handling. The small percentage of fast cases with conformance issues (0.5%, 40 cases) suggests isolated incidents of shortcuts that can be addressed through training. By using this matrix, you can allocate resources efficiently: assign your senior analysts to the 9% with both issues, process improvement specialists to the 15% that are slow but compliant, and quality auditors to investigate the fast cases with violations.
Output
The calculator displays a matrix with two rows and four columns. Each cell shows the percentage of total cases and the count of cases that fall into that combination of conformance status and performance category. The percentages across all eight cells sum to 100%.
You can click on any cell to drill down and view the specific cases in that segment, enabling detailed investigation of particular problem areas. This drill-down capability allows you to perform further analysis, such as running root cause analysis on slow cases with conformance issues or examining the process maps of different segments.
The matrix visualization typically uses color coding to highlight cells with higher percentages, making it easy to spot where most of your cases are concentrated and which segments represent the biggest opportunities for improvement.
This documentation is part of the mindzie Studio process mining platform.