Inventory Optimization: Final Strategy for Success

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Inventory Optimization Management

• Presenter Robert Wang
• 07/25/2019

_at_NexInfoSolution
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Reminder Submitting Questions
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Who Is NexInfo?

• SUMMARY
• Consulting company focused on helping clients
  achieve Operational Excellence via an optimal
  blend of Business Process Software consulting
  services
• Deep domain expertise, including Integrated
  Business Planning (IBP/SOP), Enterprise Resource
  Planning (ERP), Product Lifecycle Management
  (PLM), Customer Relationship Management (CRM),
  Enterprise Planning Management (EPM), Human
  Capital Management (HCM), Predictive Data
  Analytics, Security, Business Transformations
• Founded in 1999 and managed by computer industry
  business process professionals
• Clients include emerging companies and Fortune
  1000 corporations
• Recognized in the industry, including features in
  Gartner Reports, The Silicon Review (50 Smartest
  Companies of the Year 2016 and 10 Fastest Growing
  Oracle Solution Providers 2017), and CIO Review
  (100 Most Promising Oracle Solution Providers
  2015)
• PARTNERS
• CORPORATE INFO
• HQ in Orange County, CA with offices in Redmond,
  WA, Chicago, IL, Bridgewater, NJ, Dublin,
  Ireland, Chennai Bangalore, India
• Operations across the United States, Europe
  (Ireland, UK, Switzerland, Belgium) India

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Presenter Information

• Name Robert Wang
• Principal of Supply Chain Optimization, Nestle
  USA
• Adjunct Professor, Marshall School of Business at
  USC
• Experience
• In 2001, Robert joined the Business Analytics and
  Optimization Group at Nestle USA. As a principal
  of the group, he is the mastermind behind many
  holistic solutions for some very complex business
  problems. He specializes in using OR, large-scale
  optimization, machine learning, statistics,
  visualization, and other analytic techniques to
  solve business challenges. He has successfully
  lead the design, development, and implementation
  of solutions for Supply Chain Network Design,
  Inventory Optimization, Supply Planning,
  Deployment Planning, Network Capacity Planning,
  Trade Optimization, and Transportation.
• Robert also shares his expertise on campus as an
  Adjunct Professor at the University of Southern
  Californias Marshall School of Business. Prior
  to joining USC, Robert spent 7 years as a
  management consultant with Ernst Young and
  Deloitte Touch.

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Its 2019, But Inventory Issues have not gone away
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Why Have Inventory?
1. Uncertainty
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Why Have Inventory?
2. Products Made/Bought/Moved in Batches
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Why Have Inventory? 3. Seasonal Demand or
Production Capacity
Production Capacity
Demand
Week
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Why Inventory 4. Transit or Incubation
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Types of Inventory

• Safety
• Minimum required to maintain customer service
• Cycle
• Created by production cycles due to change-over
  cost
• Stock Build
• Due to limited production capacity
• Pipeline
• In-transit and quality hold
• Slack
• Unnecessary

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Inventory Measurements

• Relative Measure
• Relative to the demand
• Can be used to compare among companies
• Common Measurements
• Inventory Turns
• Weeks (Days) Cover

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Safety Stock

• Safety Stock protects against uncertainty in
  demand and supply
• Uncertainty demand forecast accuracy (FA),
  factory attainment, lead time variance
• Risk Customer service level
• Supply Chain Responsiveness (Also known as
  Replenishment Lead Time) planning time, frozen
  period, production, incubation, transportation
• Note longer the Replenishment Lead-Time (RLT),
  higher the uncertainty

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Inventory Impact of Customer Service

• Based on
• 67 forecast accuracy
• 30 day replenishment lead-time
• no supply uncertainty

Key Take-away Linear up to 98, then
exponential after
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Inventory Over Time
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A Dynamic Inventory Calculator

• Safety Stock
• Forecast Accuracy
• Replenishment Lead-Time
• Other Uncertainties
• Cycle Stock
• Product Cycle
• How do we know?
• Inventory Build
• Production Capacity
• How do we know?
• Pipeline Stock
• Transit / Incubation
• How do we know?
• Max Stock
• WSL
• Forecast Accuracy within WSL

Interactive Model InventoryCalculator
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Inventory Optimization Phases

• Limited change to the current SC environment
  (short-term)
• No change on Forecast Accuracy (FA),
  Replenishment Lead-Time (RLT), Service Level
  Target (SLT), etc.
• Use inventory model to calculate the right
  inventory level necessary to maintain the current
  service level.
• Low hanging fruit about 5 - 10 inventory
  reduction
• Optimize current SC environment (longer-term,
  continuous process)
• Improve FA
• Optimize Customer Service Level
• Right size production capacity
• Reduce RLT by Increasing production flexibility
  and shortening supplier response time
• Reducing Cycle and Build Inventory by optimizing
  production plan
• Improve production attainment
• Minimize production setup cost and time
• Savings opportunity 10 to 30 reduction

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Optimization Cycle and Build Inventory

• Minimize total costs impacted by production
  planning
• Inventory cost
• Production cost
• Costs of labor and over-time
• Setup or change-over cost
• Costs of shortage and freshness
• Master Production Scheduling Optimization (MPSO)
  Model
• Optimize production frequency and batch size for
  every product on a production line
• Production line capacity constrained
• Perform What-If analysis to optimize line
  capacity, over-time usage
• Evaluate options for production flexibility and
  capability

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Service Level Optimization

• This trade-off could be different for every
  different product and industry
• A good inventory optimization software should
  have this capability
• A Tableau Model
• Cost vs Fill Rate Dashboard
• Sales Lost Factor
• WACC
• A Story Behind
• A new inventory initiative given from the top for
  COF 99.5
• Use case education

Costs
Optimal Service Level for Lowest Costs
Combined Costs
Cost of Inventory
Cost of Lost Sales
Service Level
90
95
100
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Optimization Network Design

• Minimize Total Costs Impacted
• Transportation
• Inventory
• Fixed Distribution
• Handling
• Network Configuration
• Plant Direct
• DC
• Hub Spoke
• Inventory Strategy
• Push
• Pull

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Optimization Supply Chain Collaboration

• Think out side of the box
• Walmart Case for Retail Business
• DOT Food Case for Food Service
• Background
• Distributor for Food Service Industry
• Has its own SC network
• Value proposition
• Collaboration Opportunity
• Benefit Sharing

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Network Collaboration

• Current State

Minor Inventory
Minor Inventory
Major Inventory
Minor Inventory
Major Inventory

• Future State

Collaborative Network
MFG 2 FACTORY
Customer Store
Minor Inventory
Minor Inventory
Major Inventory
MFG 3 FACTORY
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QA
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Contact Us
Dublin, Ireland
Bellevue, WA
Bridgewater, NJ
Orange, CA Santa Ana, CA
Chicago, IL
Bangalore, India
Chennai, India
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Appendix
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Cycle Stock

• Cycle Stock stems from economy of scale
• Minimum batch due to labor and other physical
  constraints, e.g. production in increments of
  shifts, container size, transportation payload,
  etc.
• Labor cost and material waste involved in
  production change-over
• Manufacturing vs Retail
• Opportunities exist through improving production
  flexibility such as reducing change-over time as
  well as improving production scheduling
  capability

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Inventory Build

• Inventory Build pre-production to cover capacity
  shortfalls or demand peaks
• Demand seasonality
• Price fluctuation
• Production capacity not matching with demand
• Opportunities exist through reducing demand
  fluctuation, improving production efficiency, as
  well as improving production scheduling
  capability

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Pipeline Stock

• Pipeline stock is the goods that have been
  produced, but not ready to be shipped to customer
  yet
• Goods in quality or incubation hold
• Goods in transit from plant to DC
• Opportunities exist through reducing and
  pipeline period by reducing incubation hold
  period, or transit during incubation

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Inventory Reduction Approach

• Reduce slack inventory (or unexplained
  inventory)
• Safety Stock (Cross Functional)
• Improve Forecast Accuracy
• Realign Service Level
• Reduce Replenishment Lead-time
• Cycle Stock (Supply Planning/Manufacturing)
• Reduce change-over cost
• Reduce Batch size
• Optimize Production Plan
• Inventory Build (Supply Planning/Manufacturing)
• Smooth out production volume
• Add line capacity
• Optimize Production Plan
• Pipeline Stock (Supply Chain Network)
• Reduce Incubation time
• Incubation on Transit

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Optimization Service Level Optimization

• Understand the Trade-Off
• High Service Level leads to high safety stock
  exponentially, therefore higher inventory cost
• Low Service level leads to high chance of stock
  out, therefore lost of sales
• Measuring the cost of lost sale could be
  challenging
• Back order allowed, no lose after all
• Lost sale completely, but the remains to be
  customer
• Tangible cost Gross Margin Selling Price
  COGS
• Lost sale and as a customer in the future
• Measuring the probability of all the possible
  outcome could be challenging
• Sensitivity Analysis is a must to understand the
  range of impact
• Worst, Likely, and Best cases
• A Simple Prototype Model
• Simulation Model

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Optimization Law of Square Root

• Network Problem
• Assuming we have 5 DCs in the current network,
  each DC carries its own safety stock to meet the
  service level. What would be the impact on safety
  stock if we want to change the network to 3 or 7
  DCs?
• Law of Square Root
• ?? ?? ?? ?? ?? ?? / ?? ??
• Where ?? ?? , ?? ?? are future and current
  safety stock respectively and ?? ?? , ?? ??
  are future and current number of DCs
• Inventory Strategy Push vs Pull
• Hub Spoke Pull
• DC Push

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Optimization Multi-Echelon

• Each Node has its own inventory management
  problem
• Global inventory strategy
• Which node carry inventory and how much
• Minimize total inventory costs
• Postpone Strategy