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AUSSENWIRTSCHAFT AUSTRIA
Webinar | 24.11.2020 | 10:00 CET
CHINA: SUPPLY CHAIN
INNOVATIONEN FÜR KMU
Das Webinar beginnt in Kürze
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SPRECHER
Dr. Michael Berger
Wirtschaftsdelegierter
AußenwirtschaftsCenter Peking
Rainer Schmitz
Vice President
4flow China
AUSSENWIRTSCHAFT AUSTRIA
CHINA: SUPPLY CHAIN INNOVATIONEN FÜR KMU
Webinar | 24.11.2020 | 10:00 CET
3
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Was Sie technisch wissen sollten…
4
AGENDA
1. Begrüßung und Hinweise
2. Rückblick auf die Supply Chain Herausforderungen durch Covid
3. Lösungen und Best Practices für eine für innovativere, resilientere Supply Chains
4. Q&A
KMPG Umfrage 2020 mit 315 CEOs: What are your greatest risks to growth?
Jänner 2020: 2% aller befragten CEOs antworteten „Supply Chain Risk“
August 2020: 18% aller befragten CEOs antworteten „Supply Chain Risk“
(zweit wichtigsten Risikos nach „Talent Risk“)
Supply Chain Themen, die an Bedeutung gewinnen werden:
Stripping complexity and cost out of supply chains
Building end-to-end visibility
Investing in automation and other advanced technologies
Building agility into the network of suppliers and partners
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Supply Chain Management wird wichtiger
Ziel: Österr. Einkaufsleiter in den verarbeitenden Industrien dabei zu unterstützen, robuste Supply Chains in Asien zu bilden & Abhängigkeit von einzelnen Lieferanten und Lieferländern zu reduzieren (dual sourcing)
Branchenreport: Sourcing-Situation in China und Asien (für ausgewählte wichtige Produktgruppen)Aufzeigen von Entwicklungen/Risiken und Empfehlungen für Alternativländer zu China in den verschiedenen Produktgruppen
Workshops: mehrere Workshops in Wien im 1. Quartal 2021 geplant
Firmenspezifische Analysen: Ausgewählte Konsulenten bieten begünstigte Einzelberatungen für Unternehmen zu deren individuelle Beschaffungssituation an
Ansprechpartner: AUSSENWIRTSCHAFT Industry/Machinery/Material,Mag. Eric Savoye, E [email protected], T +43 5 90 900-3727
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Hinweis zum Strategieprojekt: Global Value Chains
der AUSSENWIRTSCHAFT AUSTRIA
© 4flow | publicPage 7 11/24/2020
4flow is your partner for supply chain management and logistics
Optimizing the entire supply chain
About 4flow Our business model
Supply chain expertise Global presence
Hier stehen ein bis zwei
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Hier stehen ein bis zwei
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team members
globally
projects annually
around the world
650+ 200+ 16offices in Europe,
Asia, North America
and South America
year of
foundationHier stehen ein bis zwei
Zeilen Text
customers
globally
300+ 2000 100%management-
owned
Supply chain
consulting
4flow consulting
Supply chain
software
4flow software
Supply chain
services
4flow management
Supply chain research 4flow research
Transport
network
design
Cost
optimization
SCM
processes
Site
engineeringDigitization
© 4flow | publicPage 8 11/24/2020
The spread of the coronavirus resulted in multiple challenges for global
supply chains
Global
supply chains with
all end-to-end functions
Network
Transportation
Intralogistics
Inventory
Organization
❯ Inbound
❯ Outbound
❯ Overseas
❯ …
❯ Raw materials
❯ Work in progress
❯ Finished goods
❯ …
❯ Plants
❯ Warehouses
❯ Cross docks
❯ …
❯ Productivity
❯ Organization structure
❯ Span of control
❯ …
❯ Putaway
❯ Picking
❯ Empties
❯ …
Shutdowns &
closings
Limited
capacities & delays
Reduced
workforce
Supply
shortages
Working
models
© 4flow | publicPage 9 11/24/2020
The current crisis shows critical disruptions but also offers significant
potential to improve on more resilient supply chains in future
Challenges
and risks
Chances
Network performance
❯ Supply shortages of critical
parts
❯ Insufficient inventories
❯ Unilateral network setup
Limited capacities
❯ Transportation disruptions
and delays
❯ Production stoppages
❯ Increased logistics and
production costs
Operations
❯ Lack of transparency
❯ Unreliable information
❯ Unclear demand situation
❯ Wrong forecasting
Organization
❯ Lack of flexibility
❯ Functional focus
❯ Unclear responsibilities
Supply chain
reconfiguration
❯ Optimized supply chain
setup
❯ Increased network maturity
❯ Improved flexibility
Capacity
management
❯ Strategic security of
required capacities
❯ Flexible capacities
New
technologies
❯ Gain speed in digitization
❯ Enhance IT infrastructure
❯ Integration of supply chain
partners
Collaboration
❯ Internal and external
collaboration
❯ Strategic partnerships
© 4flow | publicPage 10 11/24/2020
Best practices for innovative and resilient supply chains in uncertain times
Increasing digitization and utilizing innovative applications
Smart factories and
automated warehouses
Integration and operational
intelligence:
Business analytics and
process automation
Big data and
machine learning
Creation of knowledge from
large amounts of data and
independent
performance improvement
Robotic process
automation (RPA)
Increasing process
efficiency and
quality in your organization
© 4flow | publicPage 11 11/24/2020
❯ The real value add lies in the smart integration of feedback loops between automation and analytics
Smart factories and automated warehouses
Taking intralogistics and production to the next level through analytics
Process
automation
Business
analytics
Layers Integration and operational intelligence
Goods receiving Warehouse Picking Material staging Production Goods issue
Warehouse
management
system (WMS)
Transport
control
system (TCS)
Manufacturing
execution
system (MES)
Warehouse
analytics
❯ Inventory optimization
❯ Demand forecasting
❯ Ad-hoc order processing
Transport
analytics
Production
analytics
❯ Internal traffic optimization
❯ Battery charging patterns
❯ Autonomous vehicle control
❯ Dynamic order scheduling
❯ Smart replenishment
❯ Intelligent maintenance
© 4flow | publicPage 12 11/24/2020
Smart factories and automated warehouses
Concrete examples of business analytics value-add in intralogistics
Use case description Value add and business impact
Picking demand forecasting
❯ Integration of order picking system
(pick-by-vision) and analytics (tableau)
❯ Increase short-term demand forecast
accuracy and optimize picking routes
Efficiency increase and cost reduction
❯ Shorter picking times and higher picking efficiency
❯ Reduced labor demand in order preparation
❯ Real-time transparency on picking efficiency
-20%
Intelligent vehicle routing
❯ Implementation of a transport control
system to increase transparency
❯ Controlled internal material flows and
real-time track & trace
Higher transparency and service level
❯ Shorter transport order lead times
❯ Optimal transportation equipment selection
❯ Higher production flexibility and service level
+11%
Continuous stock optimization
❯ Reduction of inventory through
integrated automation and analytics
❯ System integration (SAP, Power BI)
and continuous parameter optimization
Lower inventories and more space
❯ Higher storage density, less space consumption
and less cost of tied-up capital
❯ Continuous ABC/XYZ analysis and direct
feedback loop into warehouse control systems
-27%
Cost
Service
level
Inventory
level
© 4flow | publicPage 13 11/24/2020
Business case
Solution B
Smart factories and automated warehouses
Step-sequenced selection and evaluation of suitable technologies
Requirements evaluation
Technology Requirements Investment
Hardware
Software
Integration costs
License fees
Service costs
Operating costs
¥
¥
¥
¥
¥
¥
¥
Overall costs ¥
FTE
Operating costs
Process costs
- ¥
- ¥
- ¥
Overall savings ¥
Target planningDetailed planning
Concept planning
Technology overview Qualitative analysis Quantitative analysisTechnology selection
Flexibility
Scalability
Transparency
Flexibility
Scalability
Transparency
Feasibility Feasibility
Infrastructure
❯ Greenfield vs. brownfield
❯ IT infrastructure: Compatibility and
integrability, interfaces, open
standards
❯ Building infrastructure: e.g.
necessity of navigation elements
and communication technology,
consideration of safety regulations
Solution A
© 4flow | publicPage 14 11/24/2020
Big data - Creating of knowledge from large amounts of data
Analytics tools can be used to deal with various problems
Methods Applications
Identification of process
gaps: process mining❯ High performance tool sets to analyze big data
❯ Advantages
Very large data
quantity
Complex
computations
and diagrams
Reliability and
robustness
Data plausibility: Automated
data checks and correction
methods
Illustration of material and
information flows:
clustering/aggregation
Estimation of missing
master data: Mathematical-
statistical methods
© 4flow | publicPage 15 11/24/2020
Machine learning - Independent and continuous performance improvement
Recognition of patterns as well as regularities in existing data sets
Machine learning basics Applications
General applicabilityHigh compatibility with existing
processes.
Big data processingEnables the analysis of data that
cannot be processed manually.
Advanced forecastsFaster and more reliable forecasts
allow for better planning.
Proactive behaviorQuickly adapts to changing data and
new underlying conditions.
Ability to autonomously interpret
problems and recognize patterns
Dynamic algorithms incorporating
new data into existing models to
improve performance
Holistic view of
structured and
unstructured
data
Flexibility
towards new
conditions
Supporting the
analyst by
independently
recognizing
data patterns
Advantages for data processing
© 4flow | publicPage 16 11/24/2020
Big data and machine learning
Use cases along the supply chain
Procurement
❯ More precise requirements
planning by improving sales
forecasting
Transportation management
❯ Determination of ETA using
❯ Telematics data
❯ Traffic prediction
❯ Efficient dock assignment
❯ Personnel and resource planning
Risk management
❯ Early recognition of environmental,
political and social risks
Business management
❯ More agile management through increased
transparency along the supply chain
❯ Decision-making support for location and
distribution planning
Dispatch
❯ Track and trace
❯ Increase transportation
mode utilization
Cloud
❯ Increased transparency & data quality
through decentralized data storage
External data sources
❯ Social media or weather data to
recognize trends early and better
assess customer needs
Forecasting
❯ Increased accuracy through
❯ Data exchange across
companies
❯ Early prediction of trends
Serialization
❯ Analysis of
product and
part data on
article level
Staff & resource planning
❯ Increased accuracy through
❯ More precise forecast
❯ Prediction of maintenance
Warehouse management
❯ Optimized processes and layout through
simulation
❯ Better inventory and operations
management due to increased transparency
© 4flow | publicPage 17 11/24/2020
Use case – Improved forecasting with machine learning
Reducing the risk of stock-outs
❯ Application: Fashion items are transported from East Asia
to Germany by sea or air freight
❯ Challenge: Often it is realized only at short notice which
orders use expensive air freight
❯ Objective: Detect air transportation at an early stage and
take measures to prevent it
Prediction of transportation mode Model development and optimization
Orders Risk profile
machine
learning
Determine
measures
Reduce air
freight
Historical
transportation data
Supply chain and
process analysis
Master data
In total, 78k
orders
Sea and air
freight
Classification models for estimating air
freight risk
❯ Random forest
❯ Support vector machine
❯ Boosting algorithms
10% 11%
25% 2%
0%52%
high
medium
low
No Yes
Shipped via air freight
Ris
k o
f air
fre
igh
t
© 4flow | publicPage 18 11/24/2020
Use case – Development of recommender system
Increasing production utilization
❯ Application: 20,000 different parts are produced on 442
different machines around the world.
❯ Challenge: For most parts, only very few machines are
explicitly known to be able to produce them (and vice
versa). This leads to bottlenecks and low utilization.
❯ Objective: Determine further possible part to machine
combinations to allow better production planning with
improved utilization and higher overall throughput.
Part-machine-matching Model development and optimization
Part-
machine-
matching
Recom-
mender
system
Better
planning
Better
utilization
Historical part-
machine-matching
Recommender
Systems
Overall Project Scope
System
based on
known part-
machine-
matching
Extension for
parameter
entry
(new parts)
Calculation of
„Top 4“-
supply chain
scenarios
Automated
collaboration
in the
production
network
Reflect
production
cost on
different
machines
Level 1 Level 2 Level 3 Level 4 Level 5
25,000 known combinations
Master data
Parts
CAD files
Machines
❯ Collaborative filtering:
❯ Memory based
❯ Model based
❯ Content based
systems
© 4flow | publicPage 19 11/24/2020
Robotic process automation (RPA) improves productivity and quality
RPA implementation is still in early stage within supply chain management
What is RPA? Degree of RPA implementation
Automated technological approach in which software
robots imitate humans in the execution of repetitive, rule-
based processes
Repetitive Rule-based
Electronic
data input
Multiple IT
systems
Stable
Time-
consuming
Manual
Few
exceptions
RPA-suitable processes
Banking and insurance
Telecomm. and IT
Industry
Supply chain
Despite its significant potential, RPA implementation in
logistics and supply chain management is still in its early
stages.
© 4flow | publicPage 20 11/24/2020
Robotic process automation (RPA) improves productivity and quality
Realizing efficiency potential in freight management
Background Solution
❯ Actual process: Freight volumes recorded in system
deviate from real freight volumes, which must be identified
and manually adjusted in the system
❯ No automation: Employees manually carry out process
across various systems
(TMS, xls, Outlook)
❯ Automation using RPA (implementation time: 3 weeks)
❯ Implemented target process: A robot carries out the
comparison and adjustment process in the system and
automatically generates a report.
❯ Outcome
Automation Process times Error rate
0%>95 % -65%
© 4flow | publicPage 21 11/24/2020
Building innovative and resilient supply chains
Important points to consider when starting first lighthouse initiatives
Process
identification
Complexity
Know-how
Project setup
Change and
acceptance
Key dimensions Your takeaways
Identify the right process for a lighthouse project
Select a suitable scope with a manageable complexity
Invest in external know-how for concept and ensure knowledge transfer
Set up of agile project structure with an experienced and competent team
Facilitate change by continuously communicating the new direction
22
Dr. Michael Berger
Wirtschaftsdelegierter
AußenwirtschaftsCenter Peking+86 10 85 27 50 [email protected]
Noch Fragen? Zeit für Q&A!
Rainer Schmitz
Vice President
4flow China
+86 136 8172 4557
AußenwirtschaftsCenter Peking
No. 37 Maizidian Street Chaoyang District
100125 Beijing, China
4flow China
304-305 T1 Building, SCG Parkside
868 Ying Hua Road, Pudong New District
201204 Shanghai, China
4flow Austria
Ungargasse 64-66
1030 Vienna, Austria
4flow Headquarters
Hallerstrasse 1
10587 Berlin, Germany
Elisabeth Moritz
Manager
4flow Austria
+43 664 2511004
Kontaktdaten