MEHRWERK ProcessMining (MPM)

MEHRWERK GmbH was founded in 2008 with the vision to implement agile and user-friendly Data Analytics. The company has developed MEHRWERK ProcessMining (MPM) on the BI platform Qlik Sense to offer comprehensive Process Mining capabilities to enterprise customers. MPM combines self-service Process Mining, visual and associative analytics so that even non-experts achieve quick results. The platform enables MPM to integrate functionalities that expand the sole Process Mining capability with Advanced Analytics, AI tools, Process Benchmarking, Big Data approaches and real-time scenarios. Its data governance capabilities empower users to enrich and create ad hoc analyses and dashboards without the need of programming skills. MEHRWERK has deployed its solution in various industries, including Automotive, Healthcare, Energy, Manufacturing and governmental institutions and created on that basis a comprehensive and free insider content portal named the ProcessMining BlackBox.

MEHRWERK ProcessMining (MPM)
Tool Name
MEHRWERK ProcessMining (MPM)
MEHRWERK GmbH (Karlsruhe, Germany)
Company Size
251-500 employees
Free Trial
Upon request
SaaS, Cloud
, On-Premises
Embedded In
Qlik Sense
Tested Version
April 2020 version (SaaS) - Tested in 06/2020
Data Management
Import File Types
CSV, Excel files, XML, DIF, JSON
Database Connections
Various connectors available
Various connectors available
Integrated ETL Functionality
Data Anonymization & Pseudonymization
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
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.
By custom sequence of activities
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
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, Occurrence in variants; Customizable
Time Metrics
The term “duration” is used when both active and waiting/idle times can be displayed
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
Root Cause Analysis
Pre-configured anomalies such as long lead times or "happy path fitness below 80%" can be used to detect respective root causes. Scope of anomalies can be modified upon request
Variant Breakdown by
“Duration” refers to the case throughput time
Case and Activity List
Activity List
, Case List
, Case List for Variants
View Case Details
Rework Analysis
Can be manually configured through custom analysis/listing/table via own code
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
, Auto-create from as-is
, Create new
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
Prediction of continuation of process path with weighted probabilities for running cases
Recommendations (Prescriptive Analytics)
Advanced Enhancement Capabilities
Organizational Mining
Scenario Simulation
Decision Rule Mining
Views, Monitoring and Reporting
Export Reports
Events (XLSX), Cases (XLSX), Variants (SVG, JPG, PNG, PDF, XLSX)
Export Charts and Tables
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
English, German, Spanish
Additional languages upon request
Share & Collaborate
Share selection
; Qlik Sense "Stories"
Security & Compliance
Role-Based Access
User Authentication
Basic; 2FA (authentication app) on SaaS; more for Windows deployment
Audit Logs

Distinctive Focus and Features

  • Associative Engine: MEHRWERK ProcessMining use Qlik’s native Associative Engine that allows the user to search across all data in any direction with no pre-aggregated data or pre-defined queries. Compared with traditional query-based methods, it offers the flexibility to explore data from all perspectives in a dynamic, interactive interface. Data analysis is no longer restricted to linear exploration. The competitive advantage is a direct overview of which data is related and which is not.
  • Dashboard flexibility: Dashboards can be easily configured using a highly advanced palette of charts and tables. KPIs can be tailored to any specific need. On top of that, the user can create snapshots of any sheet and enrich them with visual effects and text in order to present the results (called “Stories”) to stakeholders.
  • Comprehensive ETL functionality: With more than 100 connectors, the tool leverages Qlik’s ability to source data from any kind of database and IT system.

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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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