Case Outcome by Category

Overview

The Case Outcome by Category calculator analyzes success rates across different categories in your process data. This powerful calculator lets you define what constitutes a successful outcome (using attribute filters), then breaks down that success rate by any categorical attribute. It answers questions like "What is the on-time delivery rate by region?" or "What is the approval rate by department?"

Common Uses

Compare success rates across regions, departments, or vendors
Analyze compliance rates by business unit
Measure on-time performance by product category
Compare quality metrics across suppliers
Identify high and low performing segments
Benchmark process outcomes across organizational units

Settings

Attribute Name: Select the categorical attribute to group by. The calculator will show outcome percentages for each unique value of this attribute. Only columns with suitable data types are available (String, Boolean, Integer).

Attribute Filter: Define what constitutes a "successful" outcome using filter criteria:

Column Name: The attribute to evaluate for success
Compare Method: How to compare (Equal, Contains, Greater Than, etc.)
Compare Value: The value that indicates success
For array comparisons: Use "Is One Of" with multiple values

Example

On-Time Delivery Rate by Region

Scenario: You want to compare on-time delivery performance across different sales regions.

Setup:

Attribute Name: "Region"
Attribute Filter: "Delivery Status" equals "On Time"

Output:

Region	Percentage	On-Time Cases	Total Cases
Western	92%	460	500
Eastern	87%	435	500
Northern	78%	312	400
Southern	85%	340	400

Interpretation:

Western region has the highest on-time rate at 92%
Northern region has the lowest at 78%
This 14-percentage-point gap represents significant performance variation

Insights: The regional variation suggests different processes, resources, or challenges in each area. Northern region may need investigation - is it a capacity issue, supplier issue, or geographic challenge?

Approval Rate by Department

Scenario: You want to analyze which departments have the highest purchase order approval rates.

Setup:

Attribute Name: "Department"
Attribute Filter: "Status" equals "Approved"

Output:

Department	Percentage	Approved	Total
Marketing	95%	285	300
IT	88%	352	400
Operations	82%	410	500
R&D	76%	228	300

Insights: R&D has the lowest approval rate, possibly due to more experimental purchases, budget constraints, or stricter review requirements. This could be expected based on business context or may indicate process issues worth investigating.

Compliance Rate by Vendor

Scenario: You want to identify which vendors have the highest rates of compliance issues.

Setup:

Attribute Name: "Vendor"
Attribute Filter: "Compliance Issue" equals "Yes"

Output:

Vendor	Percentage	With Issues	Total
Vendor A	15%	45	300
Vendor B	8%	32	400
Vendor C	3%	9	300
Vendor D	22%	110	500

Insights: Vendor D has a 22% compliance issue rate - significantly higher than others. This vendor may require additional oversight, contract renegotiation, or replacement consideration.

Advanced Filter Configurations

Multiple Success Values

Use "Is One Of" to define success with multiple acceptable values:

Setup:

Attribute Name: "Product Category"
Attribute Filter: "Quality Rating" is one of ["A", "A+", "Excellent"]

This captures cases with any of the acceptable quality ratings.

Numeric Thresholds

Use comparison operators for numeric outcomes:

Setup:

Attribute Name: "Customer Segment"
Attribute Filter: "Order Value" greater than 1000

This shows high-value order rates by customer segment.

Boolean Attributes

For boolean outcome attributes:

Setup:

Attribute Name: "Sales Rep"
Attribute Filter: "Deal Closed" equals "True"

This shows close rates by sales representative.

Interactive Features

Drill-Down to Cases

Click on any row to see the underlying cases:

Click on the "Total" column to see all cases in that category
Click on the "Category" value to see cases matching the outcome filter

Sorting

Results can be sorted by:

Percentage (highest/lowest success rates first)
Total count (largest/smallest categories first)
Category name (alphabetically)

By default, results are sorted by Percentage descending to highlight best performers first.

Use Cases by Industry

Financial Services

Loan approval rates by branch
Claim acceptance rates by policy type
Investment return rates by portfolio category

Manufacturing

Quality pass rates by production line
On-time completion rates by product type
Defect rates by supplier

Healthcare

Treatment success rates by facility
Readmission rates by department
Patient satisfaction by service line

Retail

Return rates by product category
Fulfillment success by warehouse
Customer retention by segment

Best Practices

Choosing the Right Category

Select attributes with manageable cardinality (5-50 unique values)
Very high cardinality (100+ values) makes comparison difficult
Consider grouping detailed values into broader categories first

Defining Clear Outcomes

Use binary or clearly categorical success definitions
Ensure outcome data quality is consistent across categories
Document what "success" means for your analysis

Interpreting Variations

Consider baseline rates: is 85% good or bad in context?
Account for sample sizes: categories with few cases may show extreme percentages
Look for actionable differences: can you actually influence the factors?

Output

The calculator produces a data table with:

Category: Each unique value of the grouping attribute
Percentage: Success rate (outcome cases / total cases) displayed as percentage
Count: Number of cases meeting the outcome criteria
Total: Total number of cases in the category

Results are:

Sorted by percentage descending (default)
Formatted with percentage display
Interactive with drill-down capability
Exportable for reporting

Use this calculator to compare process outcomes across organizational dimensions, identify high and low performers, and prioritize improvement efforts where they'll have the greatest impact.

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