SlideShare une entreprise Scribd logo
1  sur  25
Télécharger pour lire hors ligne
Process Mining in
Action
Self-service data science for
business teams
Marlon Dumas
Professor of Information Systems @ University of Tartu
Co-founder @ Apromore
Meet Tom
- Customer Excellence Manager @ XYZ
- Tom cares about customers, recurrent
sales revenue, efficient service delivery, …
- Every week, he has different questions:
- Why did our churn rate increased last month?
- Why did the number of customer complaints
keep rising?
- Why are our response times so slow even
though we have added more staff?
- Should I automate parts of my customer
service process? Should I buy this brand new
chatbot? Should I buy the brand new co-
browsing platform I saw last week?
Tom’s company has tons of data
in their information systems!
- Customers’ web site visits
- Customers’ orders
- Customers’ complaints
- The activity of salespeople
- The activity of customer service staff
- Your shipments, product returns, …
- etc.
How to use these data?
4
https://www.youtube.com/watch?v=z9b9ZeU5aac
• Nice option, very useful to address specific challenges
• …but will you keep calling on them every day you
need an insight?
Hire a data science consultancy that delivers
successfully on 85% of its projects
• Possible in larger companies, but how much time it
takes them to gain your domain & business
knowledge?
Hire a data scientist or data science team
• Is it possible?
Set up a self-service-system that allows you to
analyze the data yourself.
Digital Footprint
Every process leaves digital footprints (transactions)
Data Preparation
Data is prepared (e.g. multiple datasets are merged)
Event Collection
Transactional data is collected from enterprise systems
and other sources
Process Analysis
Process mining algorithms are used to extract process
models and other process analytics.
Step 01
Step 02
Step 03
Step 04
Process Mining:
Self-Service Data-Driven Process Analysis
Input: Business Process Event Log
Process Mining
event log
discovered
process model
Automated Process
Discovery
Enter Loan
Application
Retrieve
Applicant
Data
Compute
Installments
Approve
Simple
Application
Approve
Complex
Application
Notify
Rejection
Notify
Eligibility
CID Task Time Stamp …
13219 Enter Loan Application 2007-11-09 T 11:20:10 -
13219 Retrieve Applicant Data 2007-11-09 T 11:22:15 -
13220 Enter Loan Application 2007-11-09 T 11:22:40 -
13219 Compute Installments 2007-11-09 T 11:22:45 -
13219 Notify Eligibility 2007-11-09 T 11:23:00 -
13219 Approve Simple Application 2007-11-09 T 11:24:30 -
13220 Compute Installements 2007-11-09 T 11:24:35 -
… … … …
Process Map
(directly follows graph)
BPMN process model
Automated Process Discovery
8
Process Mining
/
event log
discovered
process model
Automated Process
Discovery
Conformance
Checking
Business rules /
normative model
END-TO-END PROCESS IMPROVEMENT
Copyright 2020, Apromore Pty Ltd
Copyright 2020, Apromore Pty Ltd
Conformance checking
PROCESS MINING 101
Modeled process
(Expected: 8 hours)
Actual process
(In reality: 18 hours)
10
Process Mining
/
event log
discovered
process model
Automated Process
Discovery
Conformance
Checking
Performance
Mining
Enhanced
process model
Business rules /
normative model
Process map with duration overlay
Process performance
dashboards
Performance Mining
Process Mining
/
event log
discovered
process model
Automated Process
Discovery
Conformance
Checking
Variants Analysis
Difference
diagnostics
Performance
Mining
Business rules /
normative model
Enhanced
process model
event log’
Simple
repairs
Complex repairs
Variant Analysis
HSPI, Process Mining: A Database of Applications, 2020
Where is it used?
Uptake by organization size
MarketsandMarkets, Process Analytics Market – Global Forecast to 2023, May 2018
Case 1:
Process mining @ Nordic financial company
• Context: Mid-sized European payment systems provider operating in multiple countries
• Goal: Analysis of customer onboarding and customer support processes (B2B sales)
• Questions: Why are we performing in terms of customer satisfaction and resolution
times better in some countries and for some customer segments and not for others?
• Data sources: SAP CRM and ServiceNow, centralized via a data warehouse solution
• Timeframe: 8 weeks of data extraction & analysis, continued use aftewards
Positive deviance
Practices prevalent in best-performing
countries. For example, we found that
performing some activities earlier in the
process lead to better customer feedback.
Negative deviance
Practices associated with poor customer
feedback. For example, certain rework
loops caused by incorrect data collection
(for a type of customer) lead to delays.
Outcomes (after ca. 6 months)
• Process changes leading to reductions in customer onboarding time
of several days in lower-performing countries
• Changes leading to reductions in rework loops, increase in NPS
• Analysts are able to perform regular review of the process in days,
instead weeks (more than 3 x speed-up)
Case 1:
Process mining @ Nordic financial company
Case 2:
Process mining @ Australian pension fund
Identifying Inefficiencies in the
Claims Process
Identifying Complexity of the Claims
Process
Augmenting the Speed to Analysis
Proactive Conformance/Compliance
Analysis
Variant Analysis
Showcase the Flexibility of the Tool
Model the new Claims Process
Validate the Cost to Serve
Case 2:
Process mining @ Australian pension fund
82% of all pension claims cases were following the
“happy path”, i.e. were compliant with the process model
(straight-through processing).
But the 82% only accounted for 2 out of the total of 474
case variants, suggesting there were various non-
compliant cases.
Case 2:
Process mining @ Australian pension fund
The remaining 18% of cases had various errors, rework
loops, or were withdrawn at different stages of the
pension claims process.
Case 2:
Process mining @ Australian pension fund
Significant expected
ROI
 Estimated annual ROI
of over AUD
 Cost savings of AUD
150K during
project phase
Increased Speed to
Process Improvement
 2.6 times
faster compared
to traditional PI
approaches
Increased Process
Efficiency
 Expected process
efficiency gains
between 5-30%
1 2 3
Case 3:
Process mining @ Cineca
Fast facts
• One of the major EU computational centers
• 600 IT staff
• 2000+ requests per month
Processes analyzed
• Change request process
• Help request process
• Fault handling process
• Variants per geographical region and university
served
• 10 months of data
Case 3:
Process mining @ Cineca
Adoption of positive
deviances
• Replicating behavior of
top performing offices
• Training of IT service operators
Changes in ticket management
system
• Identified reasons for some
types of bounce-backs between
teams
• Alerts for real-time monitoring of
certain state changes
HSPI, Process Mining: A Database of Applications, 2020
Process Mining is Everywhere!

Contenu connexe

Tendances

Business Process Monitoring and Mining
Business Process Monitoring and MiningBusiness Process Monitoring and Mining
Business Process Monitoring and MiningMarlon Dumas
 
Automated Process Improvement: Status, Challenges, and Perspectives
Automated Process Improvement: Status, Challenges, and PerspectivesAutomated Process Improvement: Status, Challenges, and Perspectives
Automated Process Improvement: Status, Challenges, and PerspectivesMarlon Dumas
 
Apromore: Advanced Business Process Analytics on the Cloud
Apromore: Advanced Business Process Analytics on the CloudApromore: Advanced Business Process Analytics on the Cloud
Apromore: Advanced Business Process Analytics on the CloudMarlon Dumas
 
Mine Your Simulation Model: Automated Discovery of Business Process Simulatio...
Mine Your Simulation Model: Automated Discovery of Business Process Simulatio...Mine Your Simulation Model: Automated Discovery of Business Process Simulatio...
Mine Your Simulation Model: Automated Discovery of Business Process Simulatio...Marlon Dumas
 
Process Mining and Predictive Process Monitoring
Process Mining and Predictive Process MonitoringProcess Mining and Predictive Process Monitoring
Process Mining and Predictive Process MonitoringMarlon Dumas
 
Prescriptive Process Monitoring for Cost-Aware Cycle Time Reduction
Prescriptive Process Monitoring for Cost-Aware Cycle Time ReductionPrescriptive Process Monitoring for Cost-Aware Cycle Time Reduction
Prescriptive Process Monitoring for Cost-Aware Cycle Time ReductionMarlon Dumas
 
Business Process Performance Mining with Staged Process Flows
Business Process Performance Mining with Staged Process FlowsBusiness Process Performance Mining with Staged Process Flows
Business Process Performance Mining with Staged Process FlowsMarlon Dumas
 
Fundamentals of Business Process Management - Tutorial at CAiSE'2018
Fundamentals of Business Process Management - Tutorial at CAiSE'2018Fundamentals of Business Process Management - Tutorial at CAiSE'2018
Fundamentals of Business Process Management - Tutorial at CAiSE'2018Marlon Dumas
 
Demystifying AI: From Technology to Business Value
Demystifying AI:  From Technology to Business ValueDemystifying AI:  From Technology to Business Value
Demystifying AI: From Technology to Business ValueMarlon Dumas
 
My business processes are deviant! What should I do about it?
My business processes are deviant! What should I do about it?My business processes are deviant! What should I do about it?
My business processes are deviant! What should I do about it?Marlon Dumas
 
Introduction to Business Process Analysis and Redesign
Introduction to Business Process Analysis and RedesignIntroduction to Business Process Analysis and Redesign
Introduction to Business Process Analysis and RedesignMarlon Dumas
 
Business Process Modelling via BPMN, Session I
Business Process Modelling via BPMN, Session IBusiness Process Modelling via BPMN, Session I
Business Process Modelling via BPMN, Session IAmirHossein Aghdassi
 
BPM Techniques and Tools: A Quick Tour of the BPM Lifecycle
BPM Techniques and Tools: A Quick Tour of the BPM LifecycleBPM Techniques and Tools: A Quick Tour of the BPM Lifecycle
BPM Techniques and Tools: A Quick Tour of the BPM LifecycleMarlon Dumas
 
Evidence-Based Business Process Management
Evidence-Based Business Process ManagementEvidence-Based Business Process Management
Evidence-Based Business Process ManagementMarlon Dumas
 
Process mining with Disco (Eng)
Process mining with Disco (Eng)Process mining with Disco (Eng)
Process mining with Disco (Eng)Dafna Levy
 
Rutgers Research Center
Rutgers Research CenterRutgers Research Center
Rutgers Research Centercarlabrut
 
Process Mining - a new governance approach
Process Mining - a new governance approachProcess Mining - a new governance approach
Process Mining - a new governance approachMartin Pscheidl
 
From Models to Data and Back: The Journey of the BPM Discipline and the Tangl...
From Models to Data and Back: The Journey of the BPM Discipline and the Tangl...From Models to Data and Back: The Journey of the BPM Discipline and the Tangl...
From Models to Data and Back: The Journey of the BPM Discipline and the Tangl...Marlon Dumas
 
AnalysisServices
AnalysisServicesAnalysisServices
AnalysisServiceswebuploader
 

Tendances (20)

Business Process Monitoring and Mining
Business Process Monitoring and MiningBusiness Process Monitoring and Mining
Business Process Monitoring and Mining
 
Automated Process Improvement: Status, Challenges, and Perspectives
Automated Process Improvement: Status, Challenges, and PerspectivesAutomated Process Improvement: Status, Challenges, and Perspectives
Automated Process Improvement: Status, Challenges, and Perspectives
 
Apromore: Advanced Business Process Analytics on the Cloud
Apromore: Advanced Business Process Analytics on the CloudApromore: Advanced Business Process Analytics on the Cloud
Apromore: Advanced Business Process Analytics on the Cloud
 
Mine Your Simulation Model: Automated Discovery of Business Process Simulatio...
Mine Your Simulation Model: Automated Discovery of Business Process Simulatio...Mine Your Simulation Model: Automated Discovery of Business Process Simulatio...
Mine Your Simulation Model: Automated Discovery of Business Process Simulatio...
 
Process Mining and Predictive Process Monitoring
Process Mining and Predictive Process MonitoringProcess Mining and Predictive Process Monitoring
Process Mining and Predictive Process Monitoring
 
Prescriptive Process Monitoring for Cost-Aware Cycle Time Reduction
Prescriptive Process Monitoring for Cost-Aware Cycle Time ReductionPrescriptive Process Monitoring for Cost-Aware Cycle Time Reduction
Prescriptive Process Monitoring for Cost-Aware Cycle Time Reduction
 
Business Process Performance Mining with Staged Process Flows
Business Process Performance Mining with Staged Process FlowsBusiness Process Performance Mining with Staged Process Flows
Business Process Performance Mining with Staged Process Flows
 
Fundamentals of Business Process Management - Tutorial at CAiSE'2018
Fundamentals of Business Process Management - Tutorial at CAiSE'2018Fundamentals of Business Process Management - Tutorial at CAiSE'2018
Fundamentals of Business Process Management - Tutorial at CAiSE'2018
 
Demystifying AI: From Technology to Business Value
Demystifying AI:  From Technology to Business ValueDemystifying AI:  From Technology to Business Value
Demystifying AI: From Technology to Business Value
 
My business processes are deviant! What should I do about it?
My business processes are deviant! What should I do about it?My business processes are deviant! What should I do about it?
My business processes are deviant! What should I do about it?
 
Introduction to Business Process Analysis and Redesign
Introduction to Business Process Analysis and RedesignIntroduction to Business Process Analysis and Redesign
Introduction to Business Process Analysis and Redesign
 
Business Process Modelling via BPMN, Session I
Business Process Modelling via BPMN, Session IBusiness Process Modelling via BPMN, Session I
Business Process Modelling via BPMN, Session I
 
BPM Techniques and Tools: A Quick Tour of the BPM Lifecycle
BPM Techniques and Tools: A Quick Tour of the BPM LifecycleBPM Techniques and Tools: A Quick Tour of the BPM Lifecycle
BPM Techniques and Tools: A Quick Tour of the BPM Lifecycle
 
Evidence-Based Business Process Management
Evidence-Based Business Process ManagementEvidence-Based Business Process Management
Evidence-Based Business Process Management
 
Process mining with Disco (Eng)
Process mining with Disco (Eng)Process mining with Disco (Eng)
Process mining with Disco (Eng)
 
Rutgers Research Center
Rutgers Research CenterRutgers Research Center
Rutgers Research Center
 
Process Mining - a new governance approach
Process Mining - a new governance approachProcess Mining - a new governance approach
Process Mining - a new governance approach
 
From Models to Data and Back: The Journey of the BPM Discipline and the Tangl...
From Models to Data and Back: The Journey of the BPM Discipline and the Tangl...From Models to Data and Back: The Journey of the BPM Discipline and the Tangl...
From Models to Data and Back: The Journey of the BPM Discipline and the Tangl...
 
AnalysisServices
AnalysisServicesAnalysisServices
AnalysisServices
 
Manufacturing Data Analytics
Manufacturing Data AnalyticsManufacturing Data Analytics
Manufacturing Data Analytics
 

Similaire à Process Mining in Action: Self-service data science for business teams

The Hidden Economics of Business Content - A Revelation by Union Bank
The Hidden Economics of Business Content - A Revelation by Union BankThe Hidden Economics of Business Content - A Revelation by Union Bank
The Hidden Economics of Business Content - A Revelation by Union BankPyramid Solutions, Inc.
 
Service Design and the joy of prototyping operating models
Service Design and the joy of prototyping operating modelsService Design and the joy of prototyping operating models
Service Design and the joy of prototyping operating modelsStephen McKernon
 
FDSeminar Reporting & controlling
FDSeminar Reporting & controllingFDSeminar Reporting & controlling
FDSeminar Reporting & controllingFDMagazine
 
North American Utility Sparks Up its Complaint Handling System
North American Utility Sparks Up its Complaint Handling SystemNorth American Utility Sparks Up its Complaint Handling System
North American Utility Sparks Up its Complaint Handling SystemCognizant
 
North American Utility Sparks Up its Complaint Handling System
North American Utility Sparks Up its Complaint Handling SystemNorth American Utility Sparks Up its Complaint Handling System
North American Utility Sparks Up its Complaint Handling SystemCognizant
 
Product reengineering solution for a global web services enterprise.
Product reengineering solution for a global web services enterprise.Product reengineering solution for a global web services enterprise.
Product reengineering solution for a global web services enterprise.Mindtree Ltd.
 
Using Web Data to Drive Revenue and Reduce Costs
Using Web Data to Drive Revenue and Reduce CostsUsing Web Data to Drive Revenue and Reduce Costs
Using Web Data to Drive Revenue and Reduce CostsConnotate
 
2012 Global Awards for Excellence in BPM and Workflow
2012 Global Awards for Excellence in BPM and Workflow2012 Global Awards for Excellence in BPM and Workflow
2012 Global Awards for Excellence in BPM and WorkflowFuture Strategies Inc.
 
Southwest Airlines: How to make the great leap from paper to digital
Southwest Airlines: How to make the great leap from paper to digitalSouthwest Airlines: How to make the great leap from paper to digital
Southwest Airlines: How to make the great leap from paper to digitalBlueFish
 
Using Web Data to Drive Revenue and Reduce Costs
Using Web Data to Drive Revenue and Reduce CostsUsing Web Data to Drive Revenue and Reduce Costs
Using Web Data to Drive Revenue and Reduce CostsConnotate
 
ITlecture1.ppt
ITlecture1.pptITlecture1.ppt
ITlecture1.pptname954606
 
Client Onboarding: Effectively Managing the Client Lifecycle
Client Onboarding: Effectively Managing the Client LifecycleClient Onboarding: Effectively Managing the Client Lifecycle
Client Onboarding: Effectively Managing the Client LifecycleDoxim Inc.
 
ERP implementation at steel mill
ERP implementation at steel millERP implementation at steel mill
ERP implementation at steel millAsher Jawad
 
Wedding Hall Management 9975053592
Wedding Hall Management 9975053592Wedding Hall Management 9975053592
Wedding Hall Management 9975053592sachinc020
 
Business Processes - Improvement - Reengineering - Analytics
Business Processes - Improvement - Reengineering - AnalyticsBusiness Processes - Improvement - Reengineering - Analytics
Business Processes - Improvement - Reengineering - AnalyticsLaurence Gartner
 
Business Processes - Improvement - Reengineering - Analytics
Business Processes - Improvement - Reengineering - AnalyticsBusiness Processes - Improvement - Reengineering - Analytics
Business Processes - Improvement - Reengineering - AnalyticsLaurence R. L. Gartner
 

Similaire à Process Mining in Action: Self-service data science for business teams (20)

The Hidden Economics of Business Content - A Revelation by Union Bank
The Hidden Economics of Business Content - A Revelation by Union BankThe Hidden Economics of Business Content - A Revelation by Union Bank
The Hidden Economics of Business Content - A Revelation by Union Bank
 
Nimbus IP10 CJ Workshop
Nimbus IP10 CJ WorkshopNimbus IP10 CJ Workshop
Nimbus IP10 CJ Workshop
 
Process transformation in theContact Centre (DMAIC). AXA Страхование. Irina C...
Process transformation in theContact Centre (DMAIC). AXA Страхование. Irina C...Process transformation in theContact Centre (DMAIC). AXA Страхование. Irina C...
Process transformation in theContact Centre (DMAIC). AXA Страхование. Irina C...
 
Service Design and the joy of prototyping operating models
Service Design and the joy of prototyping operating modelsService Design and the joy of prototyping operating models
Service Design and the joy of prototyping operating models
 
Value Stream Mapping in the Office
Value Stream Mapping in the Office Value Stream Mapping in the Office
Value Stream Mapping in the Office
 
FDSeminar Reporting & controlling
FDSeminar Reporting & controllingFDSeminar Reporting & controlling
FDSeminar Reporting & controlling
 
North American Utility Sparks Up its Complaint Handling System
North American Utility Sparks Up its Complaint Handling SystemNorth American Utility Sparks Up its Complaint Handling System
North American Utility Sparks Up its Complaint Handling System
 
North American Utility Sparks Up its Complaint Handling System
North American Utility Sparks Up its Complaint Handling SystemNorth American Utility Sparks Up its Complaint Handling System
North American Utility Sparks Up its Complaint Handling System
 
Final Draft Sitter Solutions
Final Draft Sitter SolutionsFinal Draft Sitter Solutions
Final Draft Sitter Solutions
 
Product reengineering solution for a global web services enterprise.
Product reengineering solution for a global web services enterprise.Product reengineering solution for a global web services enterprise.
Product reengineering solution for a global web services enterprise.
 
Using Web Data to Drive Revenue and Reduce Costs
Using Web Data to Drive Revenue and Reduce CostsUsing Web Data to Drive Revenue and Reduce Costs
Using Web Data to Drive Revenue and Reduce Costs
 
2012 Global Awards for Excellence in BPM and Workflow
2012 Global Awards for Excellence in BPM and Workflow2012 Global Awards for Excellence in BPM and Workflow
2012 Global Awards for Excellence in BPM and Workflow
 
Southwest Airlines: How to make the great leap from paper to digital
Southwest Airlines: How to make the great leap from paper to digitalSouthwest Airlines: How to make the great leap from paper to digital
Southwest Airlines: How to make the great leap from paper to digital
 
Using Web Data to Drive Revenue and Reduce Costs
Using Web Data to Drive Revenue and Reduce CostsUsing Web Data to Drive Revenue and Reduce Costs
Using Web Data to Drive Revenue and Reduce Costs
 
ITlecture1.ppt
ITlecture1.pptITlecture1.ppt
ITlecture1.ppt
 
Client Onboarding: Effectively Managing the Client Lifecycle
Client Onboarding: Effectively Managing the Client LifecycleClient Onboarding: Effectively Managing the Client Lifecycle
Client Onboarding: Effectively Managing the Client Lifecycle
 
ERP implementation at steel mill
ERP implementation at steel millERP implementation at steel mill
ERP implementation at steel mill
 
Wedding Hall Management 9975053592
Wedding Hall Management 9975053592Wedding Hall Management 9975053592
Wedding Hall Management 9975053592
 
Business Processes - Improvement - Reengineering - Analytics
Business Processes - Improvement - Reengineering - AnalyticsBusiness Processes - Improvement - Reengineering - Analytics
Business Processes - Improvement - Reengineering - Analytics
 
Business Processes - Improvement - Reengineering - Analytics
Business Processes - Improvement - Reengineering - AnalyticsBusiness Processes - Improvement - Reengineering - Analytics
Business Processes - Improvement - Reengineering - Analytics
 

Plus de Marlon Dumas

How GenAI will (not) change your business?
How GenAI will (not)  change your business?How GenAI will (not)  change your business?
How GenAI will (not) change your business?Marlon Dumas
 
Walking the Way from Process Mining to AI-Driven Process Optimization
Walking the Way from Process Mining to AI-Driven Process OptimizationWalking the Way from Process Mining to AI-Driven Process Optimization
Walking the Way from Process Mining to AI-Driven Process OptimizationMarlon Dumas
 
Discovery and Simulation of Business Processes with Probabilistic Resource Av...
Discovery and Simulation of Business Processes with Probabilistic Resource Av...Discovery and Simulation of Business Processes with Probabilistic Resource Av...
Discovery and Simulation of Business Processes with Probabilistic Resource Av...Marlon Dumas
 
Can I Trust My Simulation Model? Measuring the Quality of Business Process Si...
Can I Trust My Simulation Model? Measuring the Quality of Business Process Si...Can I Trust My Simulation Model? Measuring the Quality of Business Process Si...
Can I Trust My Simulation Model? Measuring the Quality of Business Process Si...Marlon Dumas
 
Business Process Optimization: Status and Perspectives
Business Process Optimization: Status and PerspectivesBusiness Process Optimization: Status and Perspectives
Business Process Optimization: Status and PerspectivesMarlon Dumas
 
Learning When to Treat Business Processes: Prescriptive Process Monitoring wi...
Learning When to Treat Business Processes: Prescriptive Process Monitoring wi...Learning When to Treat Business Processes: Prescriptive Process Monitoring wi...
Learning When to Treat Business Processes: Prescriptive Process Monitoring wi...Marlon Dumas
 
Why am I Waiting Data-Driven Analysis of Waiting Times in Business Processes
Why am I Waiting Data-Driven Analysis of Waiting Times in Business ProcessesWhy am I Waiting Data-Driven Analysis of Waiting Times in Business Processes
Why am I Waiting Data-Driven Analysis of Waiting Times in Business ProcessesMarlon Dumas
 
Augmented Business Process Management
Augmented Business Process ManagementAugmented Business Process Management
Augmented Business Process ManagementMarlon Dumas
 
Process Mining and Data-Driven Process Simulation
Process Mining and Data-Driven Process SimulationProcess Mining and Data-Driven Process Simulation
Process Mining and Data-Driven Process SimulationMarlon Dumas
 
Modeling Extraneous Activity Delays in Business Process Simulation
Modeling Extraneous Activity Delays in Business Process SimulationModeling Extraneous Activity Delays in Business Process Simulation
Modeling Extraneous Activity Delays in Business Process SimulationMarlon Dumas
 
Business Process Simulation with Differentiated Resources: Does it Make a Dif...
Business Process Simulation with Differentiated Resources: Does it Make a Dif...Business Process Simulation with Differentiated Resources: Does it Make a Dif...
Business Process Simulation with Differentiated Resources: Does it Make a Dif...Marlon Dumas
 
Prescriptive Process Monitoring Under Uncertainty and Resource Constraints
Prescriptive Process Monitoring Under Uncertainty and Resource ConstraintsPrescriptive Process Monitoring Under Uncertainty and Resource Constraints
Prescriptive Process Monitoring Under Uncertainty and Resource ConstraintsMarlon Dumas
 
Robotic Process Mining
Robotic Process MiningRobotic Process Mining
Robotic Process MiningMarlon Dumas
 
Accurate and Reliable What-If Analysis of Business Processes: Is it Achievable?
Accurate and Reliable What-If Analysis of Business Processes: Is it Achievable?Accurate and Reliable What-If Analysis of Business Processes: Is it Achievable?
Accurate and Reliable What-If Analysis of Business Processes: Is it Achievable?Marlon Dumas
 
Learning Accurate Business Process Simulation Models from Event Logs via Auto...
Learning Accurate Business Process Simulation Models from Event Logs via Auto...Learning Accurate Business Process Simulation Models from Event Logs via Auto...
Learning Accurate Business Process Simulation Models from Event Logs via Auto...Marlon Dumas
 
Process Mining: A Guide for Practitioners
Process Mining: A Guide for PractitionersProcess Mining: A Guide for Practitioners
Process Mining: A Guide for PractitionersMarlon Dumas
 
Process Mining for Process Improvement.pptx
Process Mining for Process Improvement.pptxProcess Mining for Process Improvement.pptx
Process Mining for Process Improvement.pptxMarlon Dumas
 
Data-Driven Analysis of Batch Processing Inefficiencies in Business Processes
Data-Driven Analysis of  Batch Processing Inefficiencies  in Business ProcessesData-Driven Analysis of  Batch Processing Inefficiencies  in Business Processes
Data-Driven Analysis of Batch Processing Inefficiencies in Business ProcessesMarlon Dumas
 
Optimización de procesos basada en datos
Optimización de procesos basada en datosOptimización de procesos basada en datos
Optimización de procesos basada en datosMarlon Dumas
 
On the Road to AI-Infused Process Execution
On the Road to AI-Infused Process ExecutionOn the Road to AI-Infused Process Execution
On the Road to AI-Infused Process ExecutionMarlon Dumas
 

Plus de Marlon Dumas (20)

How GenAI will (not) change your business?
How GenAI will (not)  change your business?How GenAI will (not)  change your business?
How GenAI will (not) change your business?
 
Walking the Way from Process Mining to AI-Driven Process Optimization
Walking the Way from Process Mining to AI-Driven Process OptimizationWalking the Way from Process Mining to AI-Driven Process Optimization
Walking the Way from Process Mining to AI-Driven Process Optimization
 
Discovery and Simulation of Business Processes with Probabilistic Resource Av...
Discovery and Simulation of Business Processes with Probabilistic Resource Av...Discovery and Simulation of Business Processes with Probabilistic Resource Av...
Discovery and Simulation of Business Processes with Probabilistic Resource Av...
 
Can I Trust My Simulation Model? Measuring the Quality of Business Process Si...
Can I Trust My Simulation Model? Measuring the Quality of Business Process Si...Can I Trust My Simulation Model? Measuring the Quality of Business Process Si...
Can I Trust My Simulation Model? Measuring the Quality of Business Process Si...
 
Business Process Optimization: Status and Perspectives
Business Process Optimization: Status and PerspectivesBusiness Process Optimization: Status and Perspectives
Business Process Optimization: Status and Perspectives
 
Learning When to Treat Business Processes: Prescriptive Process Monitoring wi...
Learning When to Treat Business Processes: Prescriptive Process Monitoring wi...Learning When to Treat Business Processes: Prescriptive Process Monitoring wi...
Learning When to Treat Business Processes: Prescriptive Process Monitoring wi...
 
Why am I Waiting Data-Driven Analysis of Waiting Times in Business Processes
Why am I Waiting Data-Driven Analysis of Waiting Times in Business ProcessesWhy am I Waiting Data-Driven Analysis of Waiting Times in Business Processes
Why am I Waiting Data-Driven Analysis of Waiting Times in Business Processes
 
Augmented Business Process Management
Augmented Business Process ManagementAugmented Business Process Management
Augmented Business Process Management
 
Process Mining and Data-Driven Process Simulation
Process Mining and Data-Driven Process SimulationProcess Mining and Data-Driven Process Simulation
Process Mining and Data-Driven Process Simulation
 
Modeling Extraneous Activity Delays in Business Process Simulation
Modeling Extraneous Activity Delays in Business Process SimulationModeling Extraneous Activity Delays in Business Process Simulation
Modeling Extraneous Activity Delays in Business Process Simulation
 
Business Process Simulation with Differentiated Resources: Does it Make a Dif...
Business Process Simulation with Differentiated Resources: Does it Make a Dif...Business Process Simulation with Differentiated Resources: Does it Make a Dif...
Business Process Simulation with Differentiated Resources: Does it Make a Dif...
 
Prescriptive Process Monitoring Under Uncertainty and Resource Constraints
Prescriptive Process Monitoring Under Uncertainty and Resource ConstraintsPrescriptive Process Monitoring Under Uncertainty and Resource Constraints
Prescriptive Process Monitoring Under Uncertainty and Resource Constraints
 
Robotic Process Mining
Robotic Process MiningRobotic Process Mining
Robotic Process Mining
 
Accurate and Reliable What-If Analysis of Business Processes: Is it Achievable?
Accurate and Reliable What-If Analysis of Business Processes: Is it Achievable?Accurate and Reliable What-If Analysis of Business Processes: Is it Achievable?
Accurate and Reliable What-If Analysis of Business Processes: Is it Achievable?
 
Learning Accurate Business Process Simulation Models from Event Logs via Auto...
Learning Accurate Business Process Simulation Models from Event Logs via Auto...Learning Accurate Business Process Simulation Models from Event Logs via Auto...
Learning Accurate Business Process Simulation Models from Event Logs via Auto...
 
Process Mining: A Guide for Practitioners
Process Mining: A Guide for PractitionersProcess Mining: A Guide for Practitioners
Process Mining: A Guide for Practitioners
 
Process Mining for Process Improvement.pptx
Process Mining for Process Improvement.pptxProcess Mining for Process Improvement.pptx
Process Mining for Process Improvement.pptx
 
Data-Driven Analysis of Batch Processing Inefficiencies in Business Processes
Data-Driven Analysis of  Batch Processing Inefficiencies  in Business ProcessesData-Driven Analysis of  Batch Processing Inefficiencies  in Business Processes
Data-Driven Analysis of Batch Processing Inefficiencies in Business Processes
 
Optimización de procesos basada en datos
Optimización de procesos basada en datosOptimización de procesos basada en datos
Optimización de procesos basada en datos
 
On the Road to AI-Infused Process Execution
On the Road to AI-Infused Process ExecutionOn the Road to AI-Infused Process Execution
On the Road to AI-Infused Process Execution
 

Dernier

SFBA Splunk Usergroup meeting March 13, 2024
SFBA Splunk Usergroup meeting March 13, 2024SFBA Splunk Usergroup meeting March 13, 2024
SFBA Splunk Usergroup meeting March 13, 2024Becky Burwell
 
Persuasive E-commerce, Our Biased Brain @ Bikkeldag 2024
Persuasive E-commerce, Our Biased Brain @ Bikkeldag 2024Persuasive E-commerce, Our Biased Brain @ Bikkeldag 2024
Persuasive E-commerce, Our Biased Brain @ Bikkeldag 2024Guido X Jansen
 
5 Ds to Define Data Archiving Best Practices
5 Ds to Define Data Archiving Best Practices5 Ds to Define Data Archiving Best Practices
5 Ds to Define Data Archiving Best PracticesDataArchiva
 
Cash Is Still King: ATM market research '2023
Cash Is Still King: ATM market research '2023Cash Is Still King: ATM market research '2023
Cash Is Still King: ATM market research '2023Vladislav Solodkiy
 
The Universal GTM - how we design GTM and dataLayer
The Universal GTM - how we design GTM and dataLayerThe Universal GTM - how we design GTM and dataLayer
The Universal GTM - how we design GTM and dataLayerPavel Šabatka
 
YourView Panel Book.pptx YourView Panel Book.
YourView Panel Book.pptx YourView Panel Book.YourView Panel Book.pptx YourView Panel Book.
YourView Panel Book.pptx YourView Panel Book.JasonViviers2
 
Virtuosoft SmartSync Product Introduction
Virtuosoft SmartSync Product IntroductionVirtuosoft SmartSync Product Introduction
Virtuosoft SmartSync Product Introductionsanjaymuralee1
 
AI for Sustainable Development Goals (SDGs)
AI for Sustainable Development Goals (SDGs)AI for Sustainable Development Goals (SDGs)
AI for Sustainable Development Goals (SDGs)Data & Analytics Magazin
 
Mapping the pubmed data under different suptopics using NLP.pptx
Mapping the pubmed data under different suptopics using NLP.pptxMapping the pubmed data under different suptopics using NLP.pptx
Mapping the pubmed data under different suptopics using NLP.pptxVenkatasubramani13
 
Elements of language learning - an analysis of how different elements of lang...
Elements of language learning - an analysis of how different elements of lang...Elements of language learning - an analysis of how different elements of lang...
Elements of language learning - an analysis of how different elements of lang...PrithaVashisht1
 
CI, CD -Tools to integrate without manual intervention
CI, CD -Tools to integrate without manual interventionCI, CD -Tools to integrate without manual intervention
CI, CD -Tools to integrate without manual interventionajayrajaganeshkayala
 
Master's Thesis - Data Science - Presentation
Master's Thesis - Data Science - PresentationMaster's Thesis - Data Science - Presentation
Master's Thesis - Data Science - PresentationGiorgio Carbone
 
MEASURES OF DISPERSION I BSc Botany .ppt
MEASURES OF DISPERSION I BSc Botany .pptMEASURES OF DISPERSION I BSc Botany .ppt
MEASURES OF DISPERSION I BSc Botany .pptaigil2
 
Strategic CX: A Deep Dive into Voice of the Customer Insights for Clarity
Strategic CX: A Deep Dive into Voice of the Customer Insights for ClarityStrategic CX: A Deep Dive into Voice of the Customer Insights for Clarity
Strategic CX: A Deep Dive into Voice of the Customer Insights for ClarityAggregage
 
ChistaDATA Real-Time DATA Analytics Infrastructure
ChistaDATA Real-Time DATA Analytics InfrastructureChistaDATA Real-Time DATA Analytics Infrastructure
ChistaDATA Real-Time DATA Analytics Infrastructuresonikadigital1
 
TINJUAN PEMROSESAN TRANSAKSI DAN ERP.pptx
TINJUAN PEMROSESAN TRANSAKSI DAN ERP.pptxTINJUAN PEMROSESAN TRANSAKSI DAN ERP.pptx
TINJUAN PEMROSESAN TRANSAKSI DAN ERP.pptxDwiAyuSitiHartinah
 
How is Real-Time Analytics Different from Traditional OLAP?
How is Real-Time Analytics Different from Traditional OLAP?How is Real-Time Analytics Different from Traditional OLAP?
How is Real-Time Analytics Different from Traditional OLAP?sonikadigital1
 

Dernier (17)

SFBA Splunk Usergroup meeting March 13, 2024
SFBA Splunk Usergroup meeting March 13, 2024SFBA Splunk Usergroup meeting March 13, 2024
SFBA Splunk Usergroup meeting March 13, 2024
 
Persuasive E-commerce, Our Biased Brain @ Bikkeldag 2024
Persuasive E-commerce, Our Biased Brain @ Bikkeldag 2024Persuasive E-commerce, Our Biased Brain @ Bikkeldag 2024
Persuasive E-commerce, Our Biased Brain @ Bikkeldag 2024
 
5 Ds to Define Data Archiving Best Practices
5 Ds to Define Data Archiving Best Practices5 Ds to Define Data Archiving Best Practices
5 Ds to Define Data Archiving Best Practices
 
Cash Is Still King: ATM market research '2023
Cash Is Still King: ATM market research '2023Cash Is Still King: ATM market research '2023
Cash Is Still King: ATM market research '2023
 
The Universal GTM - how we design GTM and dataLayer
The Universal GTM - how we design GTM and dataLayerThe Universal GTM - how we design GTM and dataLayer
The Universal GTM - how we design GTM and dataLayer
 
YourView Panel Book.pptx YourView Panel Book.
YourView Panel Book.pptx YourView Panel Book.YourView Panel Book.pptx YourView Panel Book.
YourView Panel Book.pptx YourView Panel Book.
 
Virtuosoft SmartSync Product Introduction
Virtuosoft SmartSync Product IntroductionVirtuosoft SmartSync Product Introduction
Virtuosoft SmartSync Product Introduction
 
AI for Sustainable Development Goals (SDGs)
AI for Sustainable Development Goals (SDGs)AI for Sustainable Development Goals (SDGs)
AI for Sustainable Development Goals (SDGs)
 
Mapping the pubmed data under different suptopics using NLP.pptx
Mapping the pubmed data under different suptopics using NLP.pptxMapping the pubmed data under different suptopics using NLP.pptx
Mapping the pubmed data under different suptopics using NLP.pptx
 
Elements of language learning - an analysis of how different elements of lang...
Elements of language learning - an analysis of how different elements of lang...Elements of language learning - an analysis of how different elements of lang...
Elements of language learning - an analysis of how different elements of lang...
 
CI, CD -Tools to integrate without manual intervention
CI, CD -Tools to integrate without manual interventionCI, CD -Tools to integrate without manual intervention
CI, CD -Tools to integrate without manual intervention
 
Master's Thesis - Data Science - Presentation
Master's Thesis - Data Science - PresentationMaster's Thesis - Data Science - Presentation
Master's Thesis - Data Science - Presentation
 
MEASURES OF DISPERSION I BSc Botany .ppt
MEASURES OF DISPERSION I BSc Botany .pptMEASURES OF DISPERSION I BSc Botany .ppt
MEASURES OF DISPERSION I BSc Botany .ppt
 
Strategic CX: A Deep Dive into Voice of the Customer Insights for Clarity
Strategic CX: A Deep Dive into Voice of the Customer Insights for ClarityStrategic CX: A Deep Dive into Voice of the Customer Insights for Clarity
Strategic CX: A Deep Dive into Voice of the Customer Insights for Clarity
 
ChistaDATA Real-Time DATA Analytics Infrastructure
ChistaDATA Real-Time DATA Analytics InfrastructureChistaDATA Real-Time DATA Analytics Infrastructure
ChistaDATA Real-Time DATA Analytics Infrastructure
 
TINJUAN PEMROSESAN TRANSAKSI DAN ERP.pptx
TINJUAN PEMROSESAN TRANSAKSI DAN ERP.pptxTINJUAN PEMROSESAN TRANSAKSI DAN ERP.pptx
TINJUAN PEMROSESAN TRANSAKSI DAN ERP.pptx
 
How is Real-Time Analytics Different from Traditional OLAP?
How is Real-Time Analytics Different from Traditional OLAP?How is Real-Time Analytics Different from Traditional OLAP?
How is Real-Time Analytics Different from Traditional OLAP?
 

Process Mining in Action: Self-service data science for business teams

  • 1. Process Mining in Action Self-service data science for business teams Marlon Dumas Professor of Information Systems @ University of Tartu Co-founder @ Apromore
  • 2. Meet Tom - Customer Excellence Manager @ XYZ - Tom cares about customers, recurrent sales revenue, efficient service delivery, … - Every week, he has different questions: - Why did our churn rate increased last month? - Why did the number of customer complaints keep rising? - Why are our response times so slow even though we have added more staff? - Should I automate parts of my customer service process? Should I buy this brand new chatbot? Should I buy the brand new co- browsing platform I saw last week?
  • 3. Tom’s company has tons of data in their information systems! - Customers’ web site visits - Customers’ orders - Customers’ complaints - The activity of salespeople - The activity of customer service staff - Your shipments, product returns, … - etc.
  • 4. How to use these data? 4 https://www.youtube.com/watch?v=z9b9ZeU5aac • Nice option, very useful to address specific challenges • …but will you keep calling on them every day you need an insight? Hire a data science consultancy that delivers successfully on 85% of its projects • Possible in larger companies, but how much time it takes them to gain your domain & business knowledge? Hire a data scientist or data science team • Is it possible? Set up a self-service-system that allows you to analyze the data yourself.
  • 5. Digital Footprint Every process leaves digital footprints (transactions) Data Preparation Data is prepared (e.g. multiple datasets are merged) Event Collection Transactional data is collected from enterprise systems and other sources Process Analysis Process mining algorithms are used to extract process models and other process analytics. Step 01 Step 02 Step 03 Step 04 Process Mining: Self-Service Data-Driven Process Analysis
  • 7. Process Mining event log discovered process model Automated Process Discovery
  • 8. Enter Loan Application Retrieve Applicant Data Compute Installments Approve Simple Application Approve Complex Application Notify Rejection Notify Eligibility CID Task Time Stamp … 13219 Enter Loan Application 2007-11-09 T 11:20:10 - 13219 Retrieve Applicant Data 2007-11-09 T 11:22:15 - 13220 Enter Loan Application 2007-11-09 T 11:22:40 - 13219 Compute Installments 2007-11-09 T 11:22:45 - 13219 Notify Eligibility 2007-11-09 T 11:23:00 - 13219 Approve Simple Application 2007-11-09 T 11:24:30 - 13220 Compute Installements 2007-11-09 T 11:24:35 - … … … … Process Map (directly follows graph) BPMN process model Automated Process Discovery 8
  • 9. Process Mining / event log discovered process model Automated Process Discovery Conformance Checking Business rules / normative model
  • 10. END-TO-END PROCESS IMPROVEMENT Copyright 2020, Apromore Pty Ltd Copyright 2020, Apromore Pty Ltd Conformance checking PROCESS MINING 101 Modeled process (Expected: 8 hours) Actual process (In reality: 18 hours) 10
  • 11. Process Mining / event log discovered process model Automated Process Discovery Conformance Checking Performance Mining Enhanced process model Business rules / normative model
  • 12. Process map with duration overlay Process performance dashboards Performance Mining
  • 13. Process Mining / event log discovered process model Automated Process Discovery Conformance Checking Variants Analysis Difference diagnostics Performance Mining Business rules / normative model Enhanced process model event log’
  • 15. HSPI, Process Mining: A Database of Applications, 2020 Where is it used?
  • 16. Uptake by organization size MarketsandMarkets, Process Analytics Market – Global Forecast to 2023, May 2018
  • 17. Case 1: Process mining @ Nordic financial company • Context: Mid-sized European payment systems provider operating in multiple countries • Goal: Analysis of customer onboarding and customer support processes (B2B sales) • Questions: Why are we performing in terms of customer satisfaction and resolution times better in some countries and for some customer segments and not for others? • Data sources: SAP CRM and ServiceNow, centralized via a data warehouse solution • Timeframe: 8 weeks of data extraction & analysis, continued use aftewards
  • 18. Positive deviance Practices prevalent in best-performing countries. For example, we found that performing some activities earlier in the process lead to better customer feedback. Negative deviance Practices associated with poor customer feedback. For example, certain rework loops caused by incorrect data collection (for a type of customer) lead to delays. Outcomes (after ca. 6 months) • Process changes leading to reductions in customer onboarding time of several days in lower-performing countries • Changes leading to reductions in rework loops, increase in NPS • Analysts are able to perform regular review of the process in days, instead weeks (more than 3 x speed-up) Case 1: Process mining @ Nordic financial company
  • 19. Case 2: Process mining @ Australian pension fund Identifying Inefficiencies in the Claims Process Identifying Complexity of the Claims Process Augmenting the Speed to Analysis Proactive Conformance/Compliance Analysis Variant Analysis Showcase the Flexibility of the Tool Model the new Claims Process Validate the Cost to Serve
  • 20. Case 2: Process mining @ Australian pension fund 82% of all pension claims cases were following the “happy path”, i.e. were compliant with the process model (straight-through processing). But the 82% only accounted for 2 out of the total of 474 case variants, suggesting there were various non- compliant cases.
  • 21. Case 2: Process mining @ Australian pension fund The remaining 18% of cases had various errors, rework loops, or were withdrawn at different stages of the pension claims process.
  • 22. Case 2: Process mining @ Australian pension fund Significant expected ROI  Estimated annual ROI of over AUD  Cost savings of AUD 150K during project phase Increased Speed to Process Improvement  2.6 times faster compared to traditional PI approaches Increased Process Efficiency  Expected process efficiency gains between 5-30% 1 2 3
  • 23. Case 3: Process mining @ Cineca Fast facts • One of the major EU computational centers • 600 IT staff • 2000+ requests per month Processes analyzed • Change request process • Help request process • Fault handling process • Variants per geographical region and university served • 10 months of data
  • 24. Case 3: Process mining @ Cineca Adoption of positive deviances • Replicating behavior of top performing offices • Training of IT service operators Changes in ticket management system • Identified reasons for some types of bounce-backs between teams • Alerts for real-time monitoring of certain state changes
  • 25. HSPI, Process Mining: A Database of Applications, 2020 Process Mining is Everywhere!