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"Global Inventory Management Strategy, Design & Execution: Optimisation & Flexibility Amidst Constant Change" Joel Marusiak, IM Solutions Manager - EMEA, Neovia Logistics presenation at Spare Parts Business Platform 2014. Find out more http://www.sparepartseurope.com/
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Global Inventory Management Strategy, Design & Execution:Optimisation & Flexibility Amidst Constant Change
Joel Marusiak
IM Solutions Manager - EMEA
February 8th 2013
Your future, our history
• Your business is time sensitive?
• Your product is service critical?
• You require an agile partner that addresses all your needs?
You answered YES to these questions?
Then join our customers and chose Neovia Logistics to manage your value chain.
Your business, our expertise
Initial Sales
Revenue
AftermarketRevenue
InitialSalesMargin
2x-5xOpportunity
4x-10xOpportunity
0 5 10 15 yrs 0 5 10 15 yrs
AftermarketSales Margin
Why is Spare Parts Inventory so important?
Inventory is the core of any Supply Chain
• Right Part• Right Place • Right Time
• Product / Plant up-time • Customer Satisfaction • Loyalty• Profitability • Competitive Advantage
Inventory Optimisation Software: Expectation V’s Actual Results
Benefit Value in €
Time
Expectation:• Return on investment• Immediate optimisation of inventory• Quick wins
Reality of software implementation:• High cost – >1.5 x software• Long, iterative process• Continuous Improvement• Trial & error• Optimised point unknown
Define standardisedprocesses
Fill gaps in the systems functionality
Change existing system
Understand world class inventory management philosophy
Understand existing system
Measure & Monitor Impact
Stabilisation
Refine parameter
Implement standard processes
Measure baseline
Small iterative changes
Overall Inventory Optimisation:Managing the product lifecycle
New PartIntroduction
StatisticalForecasting
End of lifeManagement
• Risk: Customer dissatisfaction / obsolescence • Limited / No system functionality
• Risk: Balance between service & inventory under optimised• Mature parts managed by global, multi-echelon system• System configurations set to fulfil targets• Exception management• Expertise for refining configurations
• Risk: High obsolescence• Limited / No system functionality
Must be customised to Client-specific data and goals
New Part Introduction
Issue Impact
Global New Model Launch High customer expectation
Aftermarket support
critical to brand perception
High fill rate required
1000’s of new parts Huge obsolescence risk
No demand history No system forecasting
solution
Collaboration &
Communication
Identify new parts
Collect data on
similar parts
Set statistics
Replenish & deploy
Constant introduction of small numberof new items also require attention tomanage overall parts profile
Overall Inventory Optimisation:Managing the product lifecycle
Mature parts – statistical forecasting
Is your system capturing andusing data effectively?
PART# ABC PART# DEF
Monthly Demand 100 pieces 100 pieces
Cost per piece €10 €10
Lead Time 30 days 30 days
Criticality (Service) Same Same
Monthly Customer Order Lines 2 lines @ 50 pieces 20 lines @ 5 pieces
Which part should have greater safety stock? - Same?
Now which part should have greater safety stock?
Part DEF impacts more customers with lower inventory investment
Using order lines & pieces-per line to forecast & plan inventory provides the foundation to optimising both inventory & service
“Dialling” the system, optimisingyour inventory
FillFillRateRate
OperationOperationWorkloadWorkload
InventoryInventoryInvestmentInvestment
MasterMasterDataData
SystemSystemConfigurationConfiguration
FacilityFacilityPlanningPlanning
SupplierSupplierSchedulesSchedules
IM AnalystIM Analyst
WorkloadWorkload
FillRate
OperationWorkload
InventoryInvestment
MasterData
SystemConfiguration
FacilityPlanning
SupplierSchedules
IM Analyst
Workload
Sales Sales DemandDemand
ProductProductMasterMasterDataData
ConfigurationConfiguration
PricePriceBreaksBreaks
Business Business StrategyStrategy
Bill Of Bill Of DistributionDistribution
Sales Demand
ProductMasterData
Configuration
PriceBreaks
Business Strategy
Bill Of Distribution
10
SimulationSimulation
Demand DrivenDemand Driven
Constraint ConsiderationConstraint Consideration
Discreet Event ProcessingDiscreet Event Processing
Holistic ViewHolistic View
OptimisationOptimisation
Global Parts PopulationGlobal Parts Population
OrderProcessing
OrderProcessing
ForecastForecastStocking EvaluationStocking Evaluation
Receipts &DeploymentsReceipts &Deployments
RequirementPlanning
RequirementPlanning
Simulation
Demand Driven
Constraint Consideration
Discreet Event Processing
Holistic View
Optimisation
Global Parts Population
OrderProcessing
ForecastStocking Evaluation
Receipts &Deployments
RequirementPlanning
Supply chain impacts known prior to Execution
Stocked
Items
Service /
Fill Rate
Average
Inventory
Inv.
Turns
€10
€12
€14
€16
€18
€20
88% 90% 92% 94% 96% 98% 100%
Service / Fill Rate
Avera
ge I
nvento
ry(in m
illio
ns)
Simulation Scenario
#1 – Baseline 26,708 89.4% €18.181 3.69
#2 – Inventory Strategy 20,931 89.4% €11.187 5.98
#3 – Fill Rate Strategy 23,542 98.6% €18.195 3.67
#4 – Optimised Inventory 21,715 94.3% €13.430 4.99
Simulation Results:Choosing a strategy
Simulation Establishes Optimal Service V’s Inventory Exchange Curve & Supply Chain view
Cash Flow & Space
Customer Service
Optimised performance
Facility sizing& capital
Return On Investment
11
Managing varying demand types:
System defined forecast models at SKU level:
“The goal of forecasting is not to predict the future but to tell you what you need to know to take meaningful action in the present.”
Paul Saffo, Harvard Business Review
Agile & Flexible Forecasting
Demand Forecast
Intermittent / Erratic
Time
Random
Time
Seasonal / Cyclic
Time
Trend
Time
Demand Forecast
Demand Trip
Time
Outliers
Time
Campaign / Surge
Time
Change
In the modern economy and worldwide market place, what could change the status quo?...
Everything!Economic crisis - “Great Recession”
Earthquakes
Tsunami
Government policy
Changing supply base
Competition
Market Shifts & Expansion
Overall Inventory Optimisation:Managing the product lifecycle
End of life management
End of product Life
Flexibility enables forecast accuracy, optimised inventory andminimises obsolescence
• Forecast tracks demand changes • Responsiveness to change can be varied
Declining Growth Rate
Time
• Forecast remaining product support period• Investigate commercial opportunity• Decide whether to purchase ATB
All Time Buy
Supersession • Supersession at SKU level• Supersession start date • Demand capture on all levels of the chain• Sales order allocation• Forecasting• Replenishments (DRP/Purchasing & Deployments)• Chain breaks
16
Strategy
ExecutionPerformance Monitoring
People
ProcessTechnology
People, Process & Technology: Core to Flexible and Agile Inventory Management
Benefits: • Rapidly optimised inventory• Cash flow increased• Maximised customer service• Minimal disruption to supply chain• Immediate Return On Investment
“Big Bang” Return On Investment
Benefit Value in €
Time
Strategy
ExecutionPerformance Monitoring
People
The true value of world class inventory planning technology can only be realised when tightly managed by experts using best-practice processes
• Inventory -20%
• Maintained fill >95%“Great
Recession”
• Inventory -7%
• Fill rate +3%
• Inventory Turns +65%
50% Sales Growth
• Inventory -42%
• Facing (local) fill rate +13%
• Inventory turns + 49%
Network Restructuring
Actual Results
Thank you for listening
18
Joel MarusiakIM Solutions Manager – EMEANeovia Logistics
Please feel free to get in touch…
Strategy
Forecasting & Inventory Planning
Replenishment & Deployment
Client Collaboration
Performance Monitoring & Analytics