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Data Driven Operating Models
Theodor Schabicki
April 2019
Enabled by Process Mining
LEGACY
DATA
CULTURE
NEW PIC
Culture ORGANIZATION
6
Important market trends
• Open Innovation
• User centricity
• Blockchain
• Skunk Works
• Purpose driven
• Event driven
• Open API
• QuantumComputing
• Mobile / P2P Payments
• Customization/ batch size 1
• Natural UI
• DevOps
• Cyber Security
• Virtual Assistants
• Banking as a Service
• Internet of Things
• Internal product mgmt.
• DesignOps
• Serverless architecture
• Poly cloud
• New banking rails
• Streamlined UX
• Digital Twins
• Platformification
• Brain Computer Interface
Technology
• AR/VR
• Beyond Banking Services
• Cognitive Agents
• Smart Workspace
• Agile management
• Next Gen Workflow
• Microservices
• Machine/
Deep Learning
Process Mining
Robotic Process
Automation
BPM-Tools
Cognitive
Capturing
Artificial
Intelligence
RPA
AI
With technologies hitting the next level of maturity, automation will expand its reach significantly. Combined with the right use cases,
competencies and next generation tools, automation can be elevated to the next level
Technologies hit a new level of maturity enabling innovative architectures fuelling the rapid
growth of automation in this decade
Data Analytics
“Transformation into a fully
digital business cannot exist without
Data Driven Operations”
8
100% digital & structured
Normalization
DataInput
Smart Distribution
STP NI BPO
>80% <20%
Execution
Processing
Integration Service Layer
Systems
Operating Model Transformation
Enabler
RPA
5%R
PA
The Vision
The combination of strict data and process orientation together with core elements from
isolated automation enables new architectural concepts and efficiency levels
Data Driven Operations
Current State of Operations
Quantification &
Analytics
5%R
PA
Non-digital and
unstructured
Support
Functions
...on too many different operating
systems
Externa
l
65%
Manual
30%
STP
Processing approx…
5%
RPA
Order ProcessingOperations
Human-centric, only a view Robots & no real STP …
… operating with a lot of interfaces
AI
The transformation of operations with a truly Data Driven Operating Model driven by operational efficiency will
increase quality levels while reducing costs
Größer
9
Potential target vision of Intelligent Process Automation: Smart Workflows serving as an IPA-link
Blue Print: Process chain for Operations 4.0 (Video)Schematic representation of Operations 4.0
Structured and unstructured data (forms, E-mails, call center) for different clients from
different entry channels is recorded/targeted by open API and the integration layer
The digitalization layer and the normalization layer represent the central part of the
automated processing on a huge scale
An intelligent distribution allows the work steps to be processed modularized as well as
parallelized by using Workflow-Tools or RPA and AI
Generally the modules are set up independently and self-optimizing
NEW
10
Three horizons of automation
The leap from isolated to integrated automation through the use of new technologies
enables a significant increase in efficiency
Managed Autonomy
Autonomous, human-controlled systems with minimal
intervention
EfficiencyLevel
Isolated Automation
Automation initiatives that combine STP and RPA of isolated
processes
Integrated Automation
Integrated and combined automation of value streams with
OCR, workflow tools, RPA & AI
Maturity Level
API Business Model
Fully Digital Input
New CollaborationModel
IntelligentAutomation
Operations 4.0
RPA
AI & Scaling RPA
RPA Farms
Three waves of automation are currently affecting banking operations. The services and solutions to be developed
require not only IT know-how, but in particular methodological knowledge in process analysis and process
optimization
Process Focus is Key to
build the vision of data
driven operating models
How do I achieve fully
Data driven Ops? →
Process orientation to gain
efficiency reduce costs etc
12
Process Mining is the
foundation and enables
everything that comes
afterwards
Over to Process Mining
and why it is so important
13
After Sales
Business Model
NPA
IKS
Monitoring
Process Design
RPA & AI & BPM
Sourcing
KPIs
Cause-Effect
STP-Rate
Quality
SLA’s
Benchmarking
Personnel costs
Customer
Journey
Cross-Selling
Growth
Variations
Contract Management
Non-Financial Risk
Data-Driven Operating Models Enabled by Process Mining

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Data-Driven Operating Models Enabled by Process Mining

  • 1. Data Driven Operating Models Theodor Schabicki April 2019 Enabled by Process Mining
  • 6. 6 Important market trends • Open Innovation • User centricity • Blockchain • Skunk Works • Purpose driven • Event driven • Open API • QuantumComputing • Mobile / P2P Payments • Customization/ batch size 1 • Natural UI • DevOps • Cyber Security • Virtual Assistants • Banking as a Service • Internet of Things • Internal product mgmt. • DesignOps • Serverless architecture • Poly cloud • New banking rails • Streamlined UX • Digital Twins • Platformification • Brain Computer Interface Technology • AR/VR • Beyond Banking Services • Cognitive Agents • Smart Workspace • Agile management • Next Gen Workflow • Microservices • Machine/ Deep Learning Process Mining Robotic Process Automation BPM-Tools Cognitive Capturing Artificial Intelligence RPA AI With technologies hitting the next level of maturity, automation will expand its reach significantly. Combined with the right use cases, competencies and next generation tools, automation can be elevated to the next level Technologies hit a new level of maturity enabling innovative architectures fuelling the rapid growth of automation in this decade Data Analytics
  • 7. “Transformation into a fully digital business cannot exist without Data Driven Operations”
  • 8. 8 100% digital & structured Normalization DataInput Smart Distribution STP NI BPO >80% <20% Execution Processing Integration Service Layer Systems Operating Model Transformation Enabler RPA 5%R PA The Vision The combination of strict data and process orientation together with core elements from isolated automation enables new architectural concepts and efficiency levels Data Driven Operations Current State of Operations Quantification & Analytics 5%R PA Non-digital and unstructured Support Functions ...on too many different operating systems Externa l 65% Manual 30% STP Processing approx… 5% RPA Order ProcessingOperations Human-centric, only a view Robots & no real STP … … operating with a lot of interfaces AI The transformation of operations with a truly Data Driven Operating Model driven by operational efficiency will increase quality levels while reducing costs Größer
  • 9. 9 Potential target vision of Intelligent Process Automation: Smart Workflows serving as an IPA-link Blue Print: Process chain for Operations 4.0 (Video)Schematic representation of Operations 4.0 Structured and unstructured data (forms, E-mails, call center) for different clients from different entry channels is recorded/targeted by open API and the integration layer The digitalization layer and the normalization layer represent the central part of the automated processing on a huge scale An intelligent distribution allows the work steps to be processed modularized as well as parallelized by using Workflow-Tools or RPA and AI Generally the modules are set up independently and self-optimizing NEW
  • 10. 10 Three horizons of automation The leap from isolated to integrated automation through the use of new technologies enables a significant increase in efficiency Managed Autonomy Autonomous, human-controlled systems with minimal intervention EfficiencyLevel Isolated Automation Automation initiatives that combine STP and RPA of isolated processes Integrated Automation Integrated and combined automation of value streams with OCR, workflow tools, RPA & AI Maturity Level API Business Model Fully Digital Input New CollaborationModel IntelligentAutomation Operations 4.0 RPA AI & Scaling RPA RPA Farms Three waves of automation are currently affecting banking operations. The services and solutions to be developed require not only IT know-how, but in particular methodological knowledge in process analysis and process optimization
  • 11. Process Focus is Key to build the vision of data driven operating models How do I achieve fully Data driven Ops? → Process orientation to gain efficiency reduce costs etc
  • 12. 12 Process Mining is the foundation and enables everything that comes afterwards Over to Process Mining and why it is so important
  • 13. 13 After Sales Business Model NPA IKS Monitoring Process Design RPA & AI & BPM Sourcing KPIs Cause-Effect STP-Rate Quality SLA’s Benchmarking Personnel costs Customer Journey Cross-Selling Growth Variations Contract Management Non-Financial Risk