Expected Order

Overview

The Expected Order enrichment establishes the correct sequence of activities when events have identical or ambiguous timestamps, ensuring accurate process flow representation even when precise timing information is unavailable. This enrichment is essential for datasets where activities are recorded with date-only precision, batch processing systems that timestamp events at the same moment, or legacy systems that lack millisecond-level timing granularity.

When multiple events occur on the same day or share identical timestamps, process mining tools cannot automatically determine their correct sequence. The Expected Order enrichment solves this by allowing you to define the logical business order of activities, which the system then uses to properly sequence events during process discovery and analysis. This ensures your process maps, conformance checks, and performance metrics accurately reflect the true business process flow rather than arbitrary ordering based on data load sequences.

Common Uses

• Establish correct activity sequences for events with date-only timestamps (common in SAP and ERP systems)
• Define proper ordering for batch-processed activities that receive identical system timestamps
• Resolve ambiguity in processes where multiple activities occur simultaneously but have a known business sequence
• Correct ordering issues in legacy system data where timestamp precision is insufficient
• Ensure accurate process discovery when events are recorded at daily intervals rather than real-time
• Maintain consistent activity sequences across different data extractions and imports
• Support conformance checking by establishing the expected flow before analyzing deviations

Settings

Expected Activity Order: This interactive list displays all activities found in your event log, allowing you to arrange them in their correct business sequence. Use the drag handles (represented by the six-dot icon) to reorder activities by dragging them up or down in the list. The order you define here determines how activities will be sequenced when they have identical timestamps. Activities at the top of the list are considered to occur before activities lower in the list. Any activities not explicitly ordered will be placed after the defined sequence, maintaining their relative order from the original data.

Examples

Example 1: Purchase Order Process with Daily Timestamps

Scenario: An organization's ERP system records purchase order events with date-only precision, making it impossible to determine the correct sequence of activities that occur on the same day. The business knows the standard flow but needs to enforce it in the process mining analysis.

Settings:

• Expected Activity Order:
  1. Create Purchase Requisition
  2. Approve Purchase Requisition
  3. Create Purchase Order
  4. Send Purchase Order
  5. Receive Goods
  6. Verify Invoice
  7. Process Payment
  8. Close Purchase Order

Output: The enrichment creates a new event attribute called "Expected Order" with integer values (1-8) corresponding to each activity's position in the defined sequence. When multiple events share the same date, the system uses these values to determine their correct order in process maps and analytics.

Insights: By establishing the correct activity sequence, the organization can now accurately analyze their purchase-to-pay process, identify bottlenecks between specific steps, and ensure conformance checking reflects the true business process rather than arbitrary data ordering.

Example 2: Patient Treatment Protocol in Healthcare

Scenario: A hospital's patient management system records treatment activities at the shift level (morning, afternoon, evening) rather than exact times. Multiple activities within the same shift need to be ordered according to medical protocols to ensure accurate process analysis.

Settings:

• Expected Activity Order:
  1. Patient Registration
  2. Triage Assessment
  3. Vital Signs Check
  4. Doctor Consultation
  5. Order Diagnostic Tests
  6. Perform Lab Tests
  7. Perform Imaging
  8. Review Test Results
  9. Diagnosis
  10. Prescribe Treatment
  11. Administer Medication
  12. Patient Discharge

Output: Each event receives an "Expected Order" value from 1-12 based on the medical protocol sequence. Events with the same timestamp are now properly ordered, ensuring that "Triage Assessment" always appears before "Doctor Consultation" in the process flow, even when both occurred during the same shift.

Insights: The correct sequencing reveals that 15% of cases skip vital signs checks before doctor consultations, indicating a compliance issue. Additionally, process mining can now accurately calculate waiting times between specific treatment steps.

Example 3: Manufacturing Quality Control Process

Scenario: A manufacturing company's quality control system batches multiple inspection activities together, recording them with identical timestamps when the batch completes. The actual inspection sequence follows a strict protocol that must be reflected in process analysis.

Settings:

• Expected Activity Order:
  1. Receive Raw Materials
  2. Initial Quality Check
  3. Material Preparation
  4. Production Start
  5. In-Process Inspection 1
  6. In-Process Inspection 2
  7. Final Assembly
  8. Final Quality Inspection
  9. Packaging
  10. Shipping Preparation
  11. Ship Product

Output: The enrichment assigns sequential order values to ensure inspection activities appear in their correct sequence. Even when multiple inspections are recorded simultaneously, the process map now shows them in the proper order based on the manufacturing protocol.

Insights: With proper sequencing, the company discovers that 8% of products skip "In-Process Inspection 2", which explains quality issues reported by customers. The corrected process flow also reveals that the bottleneck is actually at "Material Preparation" rather than "Final Assembly" as previously thought.

Example 4: Insurance Claim Processing

Scenario: An insurance company's claim system records multiple assessment and approval activities on the same date, especially for complex claims requiring multiple reviews. The business needs to enforce the correct review hierarchy in their process analysis.

Settings:

• Expected Activity Order:
  1. Claim Submission
  2. Initial Document Check
  3. Claim Registration
  4. Assign to Adjuster
  5. Damage Assessment
  6. First Level Review
  7. Medical Review (if applicable)
  8. Second Level Review
  9. Final Approval Decision
  10. Payment Processing
  11. Claim Closure

Output: Each activity receives an order value ensuring that review levels appear in the correct sequence. Claims with multiple reviews on the same day now show the proper escalation path from first to second level review.

Insights: Proper sequencing reveals that 22% of claims bypass "First Level Review" and go directly to "Second Level Review", indicating either a training issue or system configuration problem. The analysis also shows that "Medical Review" activities, when present, cause significant delays in the overall process.

Example 5: Financial Month-End Close Process

Scenario: A finance department performs multiple month-end closing activities that are all recorded with the last day of the month as their timestamp. The activities must follow accounting principles and dependencies, but the flat timestamps make process analysis impossible without proper sequencing.

Settings:

• Expected Activity Order:
  1. Freeze Transaction Entry
  2. Run Trial Balance
  3. Review Suspense Accounts
  4. Clear Suspense Items
  5. Process Accruals
  6. Process Prepayments
  7. Run Depreciation
  8. Reconcile Intercompany
  9. Review Financial Statements
  10. Management Approval
  11. Post Closing Entries
  12. Lock Period

Output: The enrichment creates an "Expected Order" attribute that ensures closing activities appear in their correct sequence despite all having the same date. The process map now accurately reflects the dependencies between activities, such as "Clear Suspense Items" always following "Review Suspense Accounts".

Insights: With correct sequencing, the finance team identifies that 30% of month-end processes have "Reconcile Intercompany" happening after "Review Financial Statements", which means financial statements are being reviewed with potentially incorrect intercompany balances, requiring rework and delaying the close.

Output

The Expected Order enrichment creates a single event attribute that determines the sequencing of activities with identical timestamps:

Expected Order: An integer attribute added to the event table that specifies the relative position of each activity in the defined sequence. Activities are numbered starting from 1, with lower numbers occurring before higher numbers when timestamps are identical. Activities not included in the defined order receive values higher than the last defined activity, preserving their relative order from the source data.

This attribute is automatically used by the process mining engine when:

• Building process maps and determining edge directions
• Calculating durations between activities
• Performing conformance checking against expected paths
• Analyzing process variants and their frequencies
• Identifying rework and loop patterns in the process

The Expected Order attribute works in conjunction with the existing timestamp attributes, only affecting the sequencing when timestamps are identical or ambiguous. Events with clearly different timestamps maintain their temporal ordering regardless of the expected order values.

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