Founded in 2009 by Dr. Anne Rozinat and Dr. Christian W. Günther after their Ph.D. in the process mining group of Prof. Wil van der Aalst at the Technical University in Eindhoven, Fluxicon has been at the forefront of the process mining movement ever since. After their work on the academic process mining tool ProM, their Process Mining software Disco was developed from scratch with the goal to make Process Mining accessible for business users. Disco’s framework is based on proven scientific research and it has been in use in various industries with use cases like customer journey analysis, audit, process improvement and optimization. The tool allows an easy and flexible discovery of processes with its visualization and filtering capabilities. Fluxicon also organizes the annual Process Mining Camp, has written the “Process Mining in Practice” book that defines the process mining methodology for practitioners, and supports close to 700 universities through the Fluxicon Academic Initiative.

Tool Name
Fluxicon BV (Eindhoven, Netherlands)
Company Size
1-10 employees
Free Trial
Immediate access
Academic, Commercial
Embedded In
Tested Version
2.4.0 (March 2020 Release) - Tested in 04/2020
Data Management
Import File Types
Some of the supported file types can be uploaded in compressed format
Database Connections
via Airlift API
via Airlift API
Integrated ETL Functionality
Data Anonymization & Pseudonymization
Approach: Selected columns can be hashed upon export, and reimported as pseudonymized log data
Data Loading
  • Data Refresh: Incremental data loading, appending new data to an existing set of data
  • Scheduled Jobs = Automatic data loading in defined time intervals
Data Refresh
, Scheduled Jobs
Disco is focused on the process mining analysis use case and is not meant to be automated (the user can trigger an import of fresh data and re-use previous analyses anytime)
Character Encodings
UTF-8 compatibility tested with special characters and various languages: Korean, Japanese, Trad. & Simplif. Chinese, Hebrew, Arabic, Russian
UTF-8 (verified
) + various more encodings
Attribute Types
, Event-level
Specify Business Hours
Working week
, Multiple shifts/day
, Exclude days
, Holiday calendar
Define Event Order
Manual definition of event ordering in case of identical timestamps. This criterion does not consider automatic ordering by the tool.
Start/End Timestamp
2 timestamps
Process Discovery
» Process Graph
As-Is Process Visualization
Directly-Follows Graph (vertical)
The Disco miner has been further developed based on the Fuzzy miner and does include parallelism.
Export As-Is Process Graph
For data exports (e.g. CSV) see “Export Reports” criterion
Performance Highlighting
Visual highlighting of process bottlenecks
Active time
, Idle time
Process Animation (Replay)
Adjust speed
, Adjust timeframe
, Switch time mode
, Zoom in case
Search and Filter in Graph
  • Search and find activity names (relevant for spaghetti-like graphs)
  • Filter activities/transitions directly from graph
, Filter
Graph Abstraction
Frequency Metrics
Activity frequency, Case frequency, Max. repetitions, Start/end activity frequency
Time Metrics
The term “duration” is used when both active and waiting/idle times can be displayed
Tot/min/max/avg/med duration
Additional Graph Metrics
Cost metrics
, Custom metrics
» Process Analysis & Analytics
Process Benchmarking
Visual comparison
, Metric comparison
Processes can be compared visually by including the compared dimension in the activity name
Process Benchmarking (Different Logs)
Visual comparison
, Metric comparison
Root Cause Analysis
Variant Breakdown by
“Duration” refers to the case throughput time
Case count, event count, avg/med duration
Case and Activity List
Activity List
, Case List
, Case List for Variants
View Case Details
Rework Analysis
Different rework analyses are possible, including the filtering of direct and indirect loops, the filtering of cases that contain any type of rework, and the visualization of repetition hotspots
Edge/Transition Details
From-to activities: List of ingoing and outgoing activities for any selected activity
List of all transitions
, From-to activities
via export of transitions as a matrix
Conformance Checking
Compare As-Is and Target Process
Disco supports comformance checking by checking process rules in various dimensions (e.g. control flow, variant-based, first time right, SLA-based, via attributes)
Target Model Creation
In-Graph Conformance Visualization
List of Compliance Violations
Four-Eyes Principle
Sequence Filtering
“(Not) Directly followed by” filtering
Conformance Root Cause Analysis
Operational Support
Alert Generation
Predictive Analytics
Recommendations (Prescriptive Analytics)
Advanced Enhancement Capabilities
Organizational Mining
Scenario Simulation
Process maps and metrics can be exported to external simulation tools via XML
Decision Rule Mining
Views, Monitoring and Reporting
Export Reports
Events (CSV, XES, MXML), Cases (CSV), Variants (PDF, PNG, JPG, XML)
Export Charts and Tables
Charts are exported without axes
Custom Dashboards
Custom charts
, Custom tables
Custom Metrics/KPIs
KPI Thresholds
Deviation from defined thresholds can be detected through color differentiation
Advanced Charts
Dashboard offers >5 different chart types
World Map
Latitude & longitude coordinates
, Location by attribute (e.g. country codes, city names)
Save Filter Settings
UI Languages
Share & Collaborate
Share selection
; Project export; Filter settings sharing
Security & Compliance
Role-Based Access
N/A (Standalone)
User Authentication
N/A (Standalone)
Audit Logs
N/A (Standalone)

Distinctive Focus and Features

  • Easy-to-use desktop software: Disco is a simple and easy-to-use Process Mining desktop software (no “implementation project”) that can be run locally or in virtualized environments. The tool is suitable for interactive use in workshop sessions with process stakeholders due to its intuitive visualizations and high speed.
  • Analytical flexibility: Disco is able to simplify complex and heterogeneous process maps in an interactive way. The tool is based on the scientifically proven framework of the Fuzzy Miner and has been further extended to a fast performing algorithm, taking into account years of experience in practice and user testing. Furthermore, Disco provides various filter types such as four-eyes check, SLA-based filtering and variant filtering, which can be applied in any use case.
  • Data privacy: Privacy is guaranteed due to the local analysis of IT log data, which ensures that confidential data remains in the organization.

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Disclaimer: The timeliness of provided information is based on the tested version and date as stated under “Tested Version”. No guarantee can be given about the correctness and accuracy of the information contained.

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