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Categorize Attribute Values

Enrichments

Overview

The Categorize Attribute Values enrichment transforms numerical attributes into meaningful business categories by applying customizable range-based rules. This powerful enrichment enables you to convert continuous numerical data into discrete categories that are easier to analyze, filter, and understand in your process mining dashboards. Instead of dealing with raw numbers like invoice amounts ranging from $1 to $1,000,000, you can create intuitive categories such as "Small", "Medium", "Large", and "Enterprise" that immediately convey business significance.

This enrichment is particularly valuable for creating performance indicators, risk categories, and business classifications that align with your organizational standards. It supports both simple range definitions (greater than X) and complex range combinations (between X and Y), allowing you to define categories that precisely match your business rules. The resulting categorical attributes can be used in filters, charts, and conformance checks, making them essential for creating actionable process insights and enabling data-driven decision making across your organization.

Common Uses

  • Categorize invoice amounts into approval tiers (Under $1000, $1000-$5000, $5000-$25000, Over $25000)
  • Classify processing times into SLA categories (On Time, At Risk, Overdue, Critical)
  • Group customer order values into segments (Low Value, Standard, Premium, VIP)
  • Define risk levels based on transaction amounts (Low Risk, Medium Risk, High Risk, Critical)
  • Create age bands for outstanding payments (Current, 30 Days, 60 Days, 90+ Days)
  • Segment inventory levels into stock categories (Out of Stock, Low Stock, Normal, Overstocked)
  • Classify employee tenure into experience levels (New, Junior, Senior, Expert)

Settings

New Attribute Name: The name for the new categorical attribute that will be created in your dataset. Choose a descriptive name that clearly indicates the categorization purpose, such as "Invoice_Category", "SLA_Status", or "Risk_Level". This attribute will contain the category names you define based on the value ranges.

Attribute Name: Select the numerical attribute you want to categorize. This must be a numeric field (integer or decimal) from your case attributes. Common choices include amounts, durations, counts, or any other numerical measure that would benefit from categorization.

Category List: Define your categories by creating rules that map numerical ranges to category names. Each category requires:

  • Category Range Name: The text label that will appear when values fall within this range (e.g., "High Priority", "Standard", "Low Risk")
  • First Comparison Method: Choose how to compare the attribute value (Equal, Greater Than, Greater Than or Equal, Less Than, Less Than or Equal, Not Equal)
  • First Value: The numerical threshold for the first comparison
  • Second Comparison Method (Optional): Add a second condition to create range boundaries (useful for "between" logic)
  • Second Value (Optional): The threshold for the second comparison (only available when Second Comparison Method is selected)

Categories are evaluated in the order they appear in the list. You can drag and drop categories to reorder them. The first matching category will be applied to each case.

Examples

Example 1: Invoice Amount Approval Tiers

Scenario: A procurement department needs to route invoices to different approval workflows based on their total amount. Different approval levels are required for different value ranges.

Settings:

  • New Attribute Name: Approval_Tier
  • Attribute Name: Total_Invoice_Amount
  • Category List:
    • Category: "Auto-Approval" | Less Than or Equal: 500
    • Category: "Manager Approval" | Greater Than: 500 | AND Less Than or Equal: 5000
    • Category: "Director Approval" | Greater Than: 5000 | AND Less Than or Equal: 25000
    • Category: "C-Level Approval" | Greater Than: 25000

Output: Creates an "Approval_Tier" attribute where:

  • Invoices up to $500 are marked as "Auto-Approval"
  • Invoices from $501 to $5,000 are marked as "Manager Approval"
  • Invoices from $5,001 to $25,000 are marked as "Director Approval"
  • Invoices over $25,000 are marked as "C-Level Approval"

Insights: This categorization enables automatic routing of invoices to appropriate approvers, analysis of approval workload distribution, and identification of bottlenecks at specific approval levels.

Example 2: SLA Performance Categories

Scenario: A customer service team needs to monitor case resolution times against their SLA commitments. Cases should be categorized based on how close they are to breaching the 48-hour SLA target.

Settings:

  • New Attribute Name: SLA_Status
  • Attribute Name: Hours_Since_Creation
  • Category List:
    • Category: "On Track" | Less Than or Equal: 24
    • Category: "Warning" | Greater Than: 24 | AND Less Than or Equal: 40
    • Category: "At Risk" | Greater Than: 40 | AND Less Than or Equal: 48
    • Category: "Breached" | Greater Than: 48

Output: Creates an "SLA_Status" attribute where:

  • Cases under 24 hours are "On Track"
  • Cases between 24-40 hours are "Warning"
  • Cases between 40-48 hours are "At Risk"
  • Cases over 48 hours are "Breached"

Insights: Enables proactive management of cases approaching SLA breach, prioritization of at-risk cases, and performance reporting on SLA compliance rates.

Example 3: Customer Value Segmentation

Scenario: An e-commerce company wants to segment customers based on their total order value to provide differentiated service levels and marketing campaigns.

Settings:

  • New Attribute Name: Customer_Segment
  • Attribute Name: Total_Order_Value
  • Category List:
    • Category: "Bronze" | Less Than: 100
    • Category: "Silver" | Greater Than or Equal: 100 | AND Less Than: 500
    • Category: "Gold" | Greater Than or Equal: 500 | AND Less Than: 2000
    • Category: "Platinum" | Greater Than or Equal: 2000

Output: Creates a "Customer_Segment" attribute where customers are classified into Bronze, Silver, Gold, or Platinum tiers based on their total order value.

Insights: Facilitates targeted marketing campaigns, enables tiered customer service strategies, and helps identify opportunities for customer upgrades.

Example 4: Inventory Stock Level Alerts

Scenario: A warehouse management system needs to categorize inventory levels to trigger appropriate restocking actions and prevent stockouts.

Settings:

  • New Attribute Name: Stock_Alert_Level
  • Attribute Name: Current_Stock_Quantity
  • Category List:
    • Category: "Out of Stock" | Equal: 0
    • Category: "Critical" | Greater Than: 0 | AND Less Than or Equal: 10
    • Category: "Low Stock" | Greater Than: 10 | AND Less Than or Equal: 50
    • Category: "Normal" | Greater Than: 50 | AND Less Than or Equal: 200
    • Category: "Overstocked" | Greater Than: 200

Output: Creates a "Stock_Alert_Level" attribute that classifies inventory into five actionable categories from "Out of Stock" to "Overstocked".

Insights: Enables automated reorder point triggers, helps optimize inventory carrying costs, and provides clear visibility into stock situations requiring immediate attention.

Example 5: Payment Aging Categories

Scenario: An accounts receivable department needs to categorize outstanding invoices by age to prioritize collection efforts and assess credit risk.

Settings:

  • New Attribute Name: Payment_Age_Category
  • Attribute Name: Days_Outstanding
  • Category List:
    • Category: "Current" | Less Than or Equal: 0
    • Category: "1-30 Days" | Greater Than: 0 | AND Less Than or Equal: 30
    • Category: "31-60 Days" | Greater Than: 30 | AND Less Than or Equal: 60
    • Category: "61-90 Days" | Greater Than: 60 | AND Less Than or Equal: 90
    • Category: "Over 90 Days" | Greater Than: 90

Output: Creates a "Payment_Age_Category" attribute that groups outstanding payments into standard aging buckets used for accounts receivable reporting.

Insights: Supports collection prioritization, enables aging report generation, helps identify customers with payment issues, and facilitates bad debt provisioning calculations.

Output

The enrichment creates a new case-level attribute with the name specified in "New Attribute Name". This attribute contains string values representing the category names defined in your category list. For each case:

  • The numerical value from the source attribute is evaluated against each category rule in order
  • The first matching category name is assigned to the new attribute
  • If no categories match, the attribute remains empty (null) for that case
  • The new categorical attribute can be used immediately in filters, charts, conformance checks, and other enrichments

The categorical attribute integrates seamlessly with mindzieStudio's visualization and analysis features, enabling you to create category-based process maps, filter cases by category, generate distribution charts, and build conformance rules based on your business categories.

See Also

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

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