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Logipharma
10-04-2019
LightsOutPlanning:
How to drive real business value
from our Virtual Supply Chain
Twin
2
Good morning!
Anneleen Tronquo Valérie Vandenbroucke
Anneleen.Tronquo@bluecrux.com Valerie.Vandenbroucke@bluecrux.com
Practice lead @LightsOutPlanningPartner @ bluecrux
3
#WeAreNotThe80sAnymore
4
The end of Supply Chain as we know it…
DEVELOP PLAN SOURCE MAKE DELIVER SELL SUPPORT
DOWNSTREAM
UPSTREAM
5
#Connecting the dots
Planning
DistributionOperations
Finance
Customer
Workforce
Digitalization
6
TODAY TOMORROW
7
Qué?
8
Connect. Learn. Aim. Shine.
Future Technology Landscape – Example View
10
5 core capabilities
to drive better supply chain decisions
Create a
virtual twin
Set smart
parameters
Get
end-to-end
visibility
Optimize
end-to-end
financials
Monitor the
control tower
Use Cases
A Pharma
Use Case
#E2E Visibility
IT Landscape
Business Context
Network Products
▪ Global
▪ 20+ Internal & 50+
External
Manufacturing Sites
▪ 120+ Distribution
Centers
▪ 33.000+ Routes
▪ 150+ Brands
▪ 10.000+ SKUs
▪ 5 different ERP
systems
▪ 1 APS target system
Business Challenges
Scattered IT landscape
no E2E view on brand flows
Non-harmonized definitions of
planning sensitive parameters
Inaccurate and missing
planning master data
1
2
3
15
Get
end-to-end
visibility
Optimize
end-to-end
financials
Monitor the
control tower
5 core capabilities
to drive better supply chain decisions
Create a
virtual twin
Set smart
parameters
16
Virtual Twin
Data View
17
Virtual Twin
Multi-Level Network View
18
Virtual Twin
Brand View
Prod X Prod Y
Smart Parameters
Transfer Time – Brand YXZ
20
APS LightsOutPlanning
1 Integrated Solution
Network Synchronization
Prescriptive ParametersBetter Simulations
Frictionless Plan
ERP
Plan & KPIs
Plan Simulations
Master Data Transactional DataPlanning Data
Model Parameters
Network Sync
Self-healing
parameters
Business Results
E2E Visibility
Less friction in the Plan
Dynamic E2E Planning Parameters
↑ Product flow
understanding
Automation ↑ /
manual activity ↓
Planning accuracy &
service ↑ &
Inventory ↓
Other Use Cases
Demonstratedasset throughput and forward
looking influencing factors
‘Golden’ batch sizes & output rates for
low volume SKU’s
Determine demonstrated throughput and
key influencing parameters
Qualitative Benefits
• ↑ Asset throughput
• ↓ Energy use & cost
Quantitative Benefits
• Capacity: 262 TDS/dy -> 282 TDS/dy
• Yield accuracy 49,9% -> 50,2%
Qualitative Benefits
• ↑ Scheduling accuracy
• ↑ Factory output
Use cases, creating value from day 1!
CASE 1 CASE 2
OperationsOperations
Determine actual product average batch size to be used
in Master Production Scheduling for low volume SKU’s
Real release times between secondarypacking
and qualityrelease
Determine real lead times and
scrap rate and identify key influencing parameters
Qualitative Benefits
• ↑ remaining shelf-life for retail customers
• ↑ visibility into site Quality Release WoW
• ↑ ‘available’ plant capacity
• ↓ Safety stock due to accurate LT parameters
Quantitative Benefits
• 10% Quality Release Time reduction
• 2% Scrap Rate improvement identified
CASE 3
QA
LOP Virtual Twin & Smart Parameters LOP Virtual Twin & Smart Parameters LOP Virtual Twin & Smart Parameters
E2E financiallyoptimal supply network based on
true capacities
Qualitative benefits
• E2E thinking & acting across SC, OPS, Sales, FI, Proc.
• Awareness created at C-level to start formal IBP
• Key enabler for IBP process
Quantitative benefits
• BU1: +10% EBIT improvement identified (25%
realized during project mode / first 6 months)
• BU2: +8% EBIT improvement identified
Use cases, creating value from day 1!
CASE 5
Network
Determine the E2E financial optimized network based
on actual supply parameters
Planning Sensitive Parameters & Multi
Echelon Inventory Optimization
Determine the E2E planning sensitive parameters
for an optimized supply network
Qualitative benefits
• ↓ E2E lead time
• ↑ Planning performance
• Removal of double stock points
• Better supply chain visibility & control
Quantitative benefits
• Inventory savings: 20 MIO USD or 7% of addressable
PoV inventory (in $ value)
• PoV payback period: 3 months
CASE 4
Supply
LOP Virtual Twin & Smart Parameters LOP Virtual Twin & E2E Financial
AI based order patternrecognition & forecasting
Qualitative benefits
• Improved order quantity prediction
• Better insights into influencing factors
• Peak alert mechanisms
Includes:
• Advanced machine learning
• Neural networks
CASE 6
Demand
Use AI/ML to improve sales prediction & influencing
factors
LOP Virtual Twin & Smart Parameters
End-to-end value chain mapping as a dynamic
virtual twin
Use cases, creating value from day 1!
CASE 8
Network
Map the end-to-end brand flows from API till final
DC/Customer across multiple legacy systems
AI based demand management incl. leading
indicators
Use AI/ML to improve sales prediction & influencing
factors
Qualitative benefits
• ↑ Fct performance
• ↑ Level of automation
• Increased forecast ability & reduced bias
• Better supply chain visibility & control
Quantitative benefits
• LOP outperforms traditional TOY FCT with 50+%
CASE 7
Demand
LOP Virtual Twin & Smart Parameters LOP Virtual Twin
Qualitative benefits
• ↑ Flow visibility
• ↑ Network synchronization
• Better supply chain accuracy & control
• Platform for further value creation
Quantitative benefits
• Planning accuracy increase / frictionless planning
Your Case ?
Chooseyour digital starting point
Connect your data now &
start creating value
Bluecrux & LightsOutPlanning -what makes us different?
2
Predesign
Get the journey started
Design
Pave the way
Implement
A 1+1 = 3 collaboration
Embed
Your knowledge
Definition
Your planning sensitive
parameters
Create virtual Twin
Create clarity on your network
Smart parameters
Capture the value of your
APS
Govern & sustain
Using our LOP platform Sustain
Define
We support your
OMP BUSINESS DESIGN & TRANSFORMATION
We support your
DATA FACTORY
We support your journey towards
TOUCHLESS PLANNING
# Data is the new oil…
Our proud
CUSTOMERS
We bring a unique & holistic set of capabilities leveraging planning design expertise, advanced data methods & strong implementation skills
Connect. Learn. Aim. Shine.
Think big. Start small. Scale fast.

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How to drive real business value from your virtual Supply Chain twin?

  • 1. Logipharma 10-04-2019 LightsOutPlanning: How to drive real business value from our Virtual Supply Chain Twin
  • 2. 2 Good morning! Anneleen Tronquo Valérie Vandenbroucke Anneleen.Tronquo@bluecrux.com Valerie.Vandenbroucke@bluecrux.com Practice lead @LightsOutPlanningPartner @ bluecrux
  • 4. 4 The end of Supply Chain as we know it… DEVELOP PLAN SOURCE MAKE DELIVER SELL SUPPORT DOWNSTREAM UPSTREAM
  • 9. Future Technology Landscape – Example View
  • 10. 10 5 core capabilities to drive better supply chain decisions Create a virtual twin Set smart parameters Get end-to-end visibility Optimize end-to-end financials Monitor the control tower
  • 13. IT Landscape Business Context Network Products ▪ Global ▪ 20+ Internal & 50+ External Manufacturing Sites ▪ 120+ Distribution Centers ▪ 33.000+ Routes ▪ 150+ Brands ▪ 10.000+ SKUs ▪ 5 different ERP systems ▪ 1 APS target system
  • 14. Business Challenges Scattered IT landscape no E2E view on brand flows Non-harmonized definitions of planning sensitive parameters Inaccurate and missing planning master data 1 2 3
  • 15. 15 Get end-to-end visibility Optimize end-to-end financials Monitor the control tower 5 core capabilities to drive better supply chain decisions Create a virtual twin Set smart parameters
  • 20. 20 APS LightsOutPlanning 1 Integrated Solution Network Synchronization Prescriptive ParametersBetter Simulations Frictionless Plan ERP Plan & KPIs Plan Simulations Master Data Transactional DataPlanning Data Model Parameters Network Sync Self-healing parameters
  • 21. Business Results E2E Visibility Less friction in the Plan Dynamic E2E Planning Parameters ↑ Product flow understanding Automation ↑ / manual activity ↓ Planning accuracy & service ↑ & Inventory ↓
  • 23. Demonstratedasset throughput and forward looking influencing factors ‘Golden’ batch sizes & output rates for low volume SKU’s Determine demonstrated throughput and key influencing parameters Qualitative Benefits • ↑ Asset throughput • ↓ Energy use & cost Quantitative Benefits • Capacity: 262 TDS/dy -> 282 TDS/dy • Yield accuracy 49,9% -> 50,2% Qualitative Benefits • ↑ Scheduling accuracy • ↑ Factory output Use cases, creating value from day 1! CASE 1 CASE 2 OperationsOperations Determine actual product average batch size to be used in Master Production Scheduling for low volume SKU’s Real release times between secondarypacking and qualityrelease Determine real lead times and scrap rate and identify key influencing parameters Qualitative Benefits • ↑ remaining shelf-life for retail customers • ↑ visibility into site Quality Release WoW • ↑ ‘available’ plant capacity • ↓ Safety stock due to accurate LT parameters Quantitative Benefits • 10% Quality Release Time reduction • 2% Scrap Rate improvement identified CASE 3 QA LOP Virtual Twin & Smart Parameters LOP Virtual Twin & Smart Parameters LOP Virtual Twin & Smart Parameters
  • 24. E2E financiallyoptimal supply network based on true capacities Qualitative benefits • E2E thinking & acting across SC, OPS, Sales, FI, Proc. • Awareness created at C-level to start formal IBP • Key enabler for IBP process Quantitative benefits • BU1: +10% EBIT improvement identified (25% realized during project mode / first 6 months) • BU2: +8% EBIT improvement identified Use cases, creating value from day 1! CASE 5 Network Determine the E2E financial optimized network based on actual supply parameters Planning Sensitive Parameters & Multi Echelon Inventory Optimization Determine the E2E planning sensitive parameters for an optimized supply network Qualitative benefits • ↓ E2E lead time • ↑ Planning performance • Removal of double stock points • Better supply chain visibility & control Quantitative benefits • Inventory savings: 20 MIO USD or 7% of addressable PoV inventory (in $ value) • PoV payback period: 3 months CASE 4 Supply LOP Virtual Twin & Smart Parameters LOP Virtual Twin & E2E Financial AI based order patternrecognition & forecasting Qualitative benefits • Improved order quantity prediction • Better insights into influencing factors • Peak alert mechanisms Includes: • Advanced machine learning • Neural networks CASE 6 Demand Use AI/ML to improve sales prediction & influencing factors LOP Virtual Twin & Smart Parameters
  • 25. End-to-end value chain mapping as a dynamic virtual twin Use cases, creating value from day 1! CASE 8 Network Map the end-to-end brand flows from API till final DC/Customer across multiple legacy systems AI based demand management incl. leading indicators Use AI/ML to improve sales prediction & influencing factors Qualitative benefits • ↑ Fct performance • ↑ Level of automation • Increased forecast ability & reduced bias • Better supply chain visibility & control Quantitative benefits • LOP outperforms traditional TOY FCT with 50+% CASE 7 Demand LOP Virtual Twin & Smart Parameters LOP Virtual Twin Qualitative benefits • ↑ Flow visibility • ↑ Network synchronization • Better supply chain accuracy & control • Platform for further value creation Quantitative benefits • Planning accuracy increase / frictionless planning Your Case ? Chooseyour digital starting point Connect your data now & start creating value
  • 26. Bluecrux & LightsOutPlanning -what makes us different? 2 Predesign Get the journey started Design Pave the way Implement A 1+1 = 3 collaboration Embed Your knowledge Definition Your planning sensitive parameters Create virtual Twin Create clarity on your network Smart parameters Capture the value of your APS Govern & sustain Using our LOP platform Sustain Define We support your OMP BUSINESS DESIGN & TRANSFORMATION We support your DATA FACTORY We support your journey towards TOUCHLESS PLANNING # Data is the new oil… Our proud CUSTOMERS We bring a unique & holistic set of capabilities leveraging planning design expertise, advanced data methods & strong implementation skills
  • 27. Connect. Learn. Aim. Shine. Think big. Start small. Scale fast.