Founded in 2011 by three university students, Celonis’ market leading platform (Gartner, 2019) has helped companies achieve process excellence by removing operational friction points with its Intelligent Business Cloud platform. Besides user-friendly process discovery, analytics and conformance checking capabilities, the platform offers a dedicated Transformation Center for KPI monitoring. One of the key strengths is Celonis’ comprehensive approach for process enhancement which includes a Python-based Machine Learning Workbench for predictive insights, an AI-powered Action Engine for intelligent process recommendations and Process Automation to automate workflows. Celonis provides a highly scalable and secure platform, offers various deployment options and supports many databases and systems for data extraction. Celonis recently launched Operational Applications, which are role-based applications that automate tasks, prioritize workflows, and prescribe guidance against target business goals leveraging business context, AI, and the core process mining engine. The vendor is closely cooperating with universities through its Academic Alliance program.
Tool Name
Celonis Process Mining
Vendor
Celonis SE (Munich, Germany & New York, NY, USA)
Company Size
1001-5000 employees
Free Trial
Immediate access
Licenses
Free, Academic, Commercial
Separate Enterprise and Consulting licenses available
Deployment
Cloud , Hybrid, On-Premises
Embedded In
–
Tested Version
Celonis Intelligent Business Cloud - Tested in 04/2020
Data Management
Import File Types
CSV, XLSX, XES
Database Connections
JDBC drivers, e.g. Postgres, MSSQL, HANA, Oracle and many more
Postgres, MSSQL, HANA, Oracle, IBM DB2, MySQL, Amazon Redshift, SAP MaxDB, Sybase, Azure SQL, Snowflake, Teradata, Amazon Athena, OpenEdge. Some drivers are not provided for On-Premises deployment due to legal reasons.
Adapters/Connectors
Oracle EBS/ERP Cloud/BI Publisher, Salesforce, SAP Ariba/Hybris/ECC/Concur, ServiceNow, UiPath, Coupa, Google Sheets
Integrated ETL Functionality
Data Anonymization & Pseudonymization
Data can be pseudonymized during data extraction or data transformation using a hash algorithm of the SHA1/2 family
Event collection: SQL workbench
Column pseudonymization during data extraction
Data permissions on data model level
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
Real-time loading possible with and without delta
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
Case-level , Event-level
Specify Business Hours
Working week , Multiple shifts/day , Exclude days , Holiday calendar
No country-specific holiday calendar, however holidays can be imported from a given TFACS table
Define Event Order
Manual definition of event ordering in case of identical timestamps. This criterion does not consider automatic ordering by the tool.
By selected column
Start/End Timestamp
2 timestamps
Process Discovery
» Process Graph
As-Is Process Visualization
Directly-Follows Graph (vertical)
Export As-Is Process Graph
For data exports (e.g. CSV) see “Export Reports” criterion
BPMN
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
Search , Filter
Graph Abstraction
Frequency Metrics
Activity frequency, Case frequency, From-to frequency; Customizable
Time Metrics
The term “duration” is used when both active and waiting/idle times can be displayed
Avg/med/trim med duration; Customizable
Additional Graph Metrics
Cost metrics , Custom metrics
» Process Analysis & Analytics
Process Benchmarking
Visual comparison , Metric comparison
Process Benchmarking (Different Logs)
Visual comparison , Metric comparison
Possible with multi-level event logs
Root Cause Analysis
Variant Breakdown by
“Duration” refers to the case throughput time
Case count, Avg throughput time; Customizable
Case and Activity List
Activity List , Case List , Case List for Variants
View Case Details
Rework Analysis
Rework analysis can be tailored with custom dashboards
Edge/Transition Details
From-to activities: List of ingoing and outgoing activities for any selected activity
List of all transitions , From-to activities
Conformance Checking
Compare As-Is and Target Process
Target Model Creation
Import model (BPMN), Auto-create from as-is , Create new
In-Graph Conformance Visualization
Celonis' conformance checker allows the analysis of violations that can be visualized in the process explorer; the process graph can be filtered by any selected violation
List of Compliance Violations
Four-Eyes Principle
Sequence Filtering
“(Not) Directly followed by” filtering
Conformance Root Cause Analysis
Operational Support
Alert Generation
Predictive Analytics
Available out-of-the-box and can be configured in the Machine Learning Workbench
Recommendations (Prescriptive Analytics)
Advanced Enhancement Capabilities
Organizational Mining
Scenario Simulation
Possible through manual configuration in the Machine Learning Workbench
Decision Rule Mining
Possible through manual configuration in the Machine Learning Workbench
Share selection ; Sharing of workspaces and projects; Task management
Security & Compliance
Role-Based Access
User Authentication
Basic; 2FA (email); IP-based access restrictions; SSO via SAML 2.0, LDAP or OIDC
Audit Logs
Distinctive Focus and Features
Data Connectivity: Through its JDBC drivers, Celonis Process Mining supports data extraction from various databases such as Postgres, MSSQL, HANA and Amazon Redshift. Pre-built connectors for ERP, CRM and other systems are available as well. Celonis currently offers real-time data extraction from SAP, Salesforce and ServiceNow.
Machine Learning Workbench: The Intelligent Business Cloud (IBC) includes a self-hosted Jupyter Notebook for Python-based creation and deployment of predictive models. Pre-built Python packages for certain use cases are available.
Action Engine: A comprehensive action management assists employees with intelligent recommendations for the “next steps” to achieve a desired process outcome and the ability to directly trigger actions in any system with the click of a button.
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.
Click to enlarge
Tap to enlarge
Process Graph
Process Variants
Dashboards
Conformance Checking
Social Analysis
Action Engine
Machine Learning Workbench
Appetite for an additional visual impression of Celonis Process Mining?
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