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Solving For The Supply Demand Mis-Match: Strategy and Case Study
Solving For The Supply Demand Mis-Match: Strategy and Case Study
Solving For The Supply Demand Mis-Match: Strategy and Case Study
Solving For The Supply Demand Mis-Match: Strategy and Case Study
Solving For The Supply Demand Mis-Match: Strategy and Case Study
Solving For The Supply Demand Mis-Match: Strategy and Case Study
Solving For The Supply Demand Mis-Match: Strategy and Case Study
Solving For The Supply Demand Mis-Match: Strategy and Case Study
Solving For The Supply Demand Mis-Match: Strategy and Case Study
Solving For The Supply Demand Mis-Match: Strategy and Case Study
Solving For The Supply Demand Mis-Match: Strategy and Case Study
Solving For The Supply Demand Mis-Match: Strategy and Case Study
Solving For The Supply Demand Mis-Match: Strategy and Case Study
Solving For The Supply Demand Mis-Match: Strategy and Case Study
Solving For The Supply Demand Mis-Match: Strategy and Case Study
Solving For The Supply Demand Mis-Match: Strategy and Case Study
Solving For The Supply Demand Mis-Match: Strategy and Case Study
Solving For The Supply Demand Mis-Match: Strategy and Case Study
Solving For The Supply Demand Mis-Match: Strategy and Case Study
Solving For The Supply Demand Mis-Match: Strategy and Case Study
Solving For The Supply Demand Mis-Match: Strategy and Case Study
Solving For The Supply Demand Mis-Match: Strategy and Case Study
Solving For The Supply Demand Mis-Match: Strategy and Case Study
Solving For The Supply Demand Mis-Match: Strategy and Case Study
Solving For The Supply Demand Mis-Match: Strategy and Case Study
Solving For The Supply Demand Mis-Match: Strategy and Case Study
Solving For The Supply Demand Mis-Match: Strategy and Case Study
Solving For The Supply Demand Mis-Match: Strategy and Case Study
Solving For The Supply Demand Mis-Match: Strategy and Case Study
Solving For The Supply Demand Mis-Match: Strategy and Case Study
Solving For The Supply Demand Mis-Match: Strategy and Case Study
Solving For The Supply Demand Mis-Match: Strategy and Case Study
Solving For The Supply Demand Mis-Match: Strategy and Case Study
Solving For The Supply Demand Mis-Match: Strategy and Case Study
Solving For The Supply Demand Mis-Match: Strategy and Case Study
Solving For The Supply Demand Mis-Match: Strategy and Case Study
Solving For The Supply Demand Mis-Match: Strategy and Case Study
Solving For The Supply Demand Mis-Match: Strategy and Case Study
Solving For The Supply Demand Mis-Match: Strategy and Case Study
Solving For The Supply Demand Mis-Match: Strategy and Case Study
Solving For The Supply Demand Mis-Match: Strategy and Case Study
Solving For The Supply Demand Mis-Match: Strategy and Case Study
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Solving For The Supply Demand Mis-Match: Strategy and Case Study

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Presented at ACS 2004 Symposium. ACS is an educational extension of APICS Region XI representing twenty-four APICS chapters from North Carolina, South Carolina

Presented at ACS 2004 Symposium. ACS is an educational extension of APICS Region XI representing twenty-four APICS chapters from North Carolina, South Carolina

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    • 1. Solving For The Supply Demand Mis-Match: Strategy and Case Study Mark Kelly General Manager Modus Media International www.modus.com ACS 2004 Symposium “ Winning with Certainty in Uncertain Times” April 21 st – 23 rd , 2004 Myrtle Beach, SC – Kingston Plantation
    • 2. Agenda
      • The Supply Demand Mis-Match Challenge
        • Product life cycle
        • Bullwhip effect
      • Solving the Mis-Match
        • SKU Stratification: Volume Variability Profiling
        • Multi-Tier Manufacturing and Distribution
      • Case Study
        • Modus Media
    • 3. The Product Life Cycle Exacerbates the “Demand” Problem Launch Date End of Life Units per period EOL Core Products Launch Build awareness Mass produce and distribute Ongoing Fulfillment to support demand (med volume) Support aftermarket (low volume) Trials/ New Products Illustration of a Product Life Cycle Replenishment Mode Train for use
    • 4. Life Cycle Management Launch Date True End-Customer Demand End of Life Units per period Source: Austin and Lee, Supply Chain Management Review, Summer 1998, pp 24ff At Odds: the typical product life cycle and an inefficient Supply Chain
    • 5. Life Cycle Management Launch Date Channel Orders True End-Customer Demand End of Life Units per period Source: Austin and Lee, Supply Chain Management Review, Summer 1998, pp 24ff At Odds: the typical product life cycle and an inefficient Supply Chain
    • 6. Life Cycle Management Launch Date Channel Orders Production True End-Customer Demand End of Life Units per period Source: Austin and Lee, Supply Chain Management Review, Summer 1998, pp 24ff At Odds: the typical product life cycle and an inefficient Supply Chain
    • 7. Life Cycle Management Launch Date 1 3 Channel Orders Production True End-Customer Demand 1 Production cannot meet initial projected demand, resulting in real shortages Channel partners over-order in an attempt to meet demand and stock shelves 3 As supply catches up with demand, orders are cancelled or returned End of Life Units per period Source: Austin and Lee, Supply Chain Management Review, Summer 1998, pp 24ff At Odds: the typical product life cycle and an inefficient Supply Chain 2 2
    • 8. Life Cycle Management Launch Date 1 3 5 4 Channel Orders Production True End-Customer Demand 1 Production cannot meet initial projected demand, resulting in real shortages Channel partners over-order in an attempt to meet demand and stock shelves 3 As supply catches up with demand, orders are cancelled or returned 4 Financial and production planning are not aligned with real demand; therefore, production continues 5 As demand declines, all parties attempt to drain inventory to prevent write-off End of Life Units per period Source: Austin and Lee, Supply Chain Management Review, Summer 1998, pp 24ff At Odds: the typical product life cycle and an inefficient Supply Chain 2 2
    • 9. Life Cycle Management
      • Initial creation, and ongoing maintenance, of a manufacturing and logistics model to support all production needs throughout a product’s life cycle
      • Integrated support model using various methods of production and inventory models
    • 10. Traditional supply chains amplify instability of demand at each stage WIP WIP Suppliers Primary Manufacturing Secondary Manufacturing Regional Warehouse Distributor Retailer Customer The “Bullwhip” Effect Why is this?
    • 11. The “Bullwhip” Effect WIP WIP Suppliers Primary Manufacturing Secondary Manufacturing Regional Warehouse Distributor Retailer Customer
      • Lead-times
      • Price fluctuations
      • Shortages and excesses
      • Local optimization
      • Forecast updating
      • Number of stocking points
      • Batching:
        • manufacturing
        • transport
      Source: MIT studies have proven the concept of the “bullwhip effect” naturally occurs in almost all supply chains unless directly combated with strong supply chain design techniques and execution
    • 12. The Supply Demand Alignment Challenge
      • Different SKUs have different attributes and needs:
      • How can we capture the profile of what is really happening?
    • 13. Agenda
      • The Supply Demand Mis-Match Challenge
      • Solving the Mis-Match
        • SKU Stratification: Volume-Variability Profiling
        • Multi-Tier Manufacturing and Distribution
      • Case Studies
    • 14. Start with a SKU Stratification
      • What is it?
        • SKU stratifications are a simple ranking of SKUs by an attribute. Typical SKU stratifications are based on Volumes , with
          • A SKUs being high volume
          • B SKUs being medium volume
          • C SKUs being low volume
      • A better way is to look at both Volume, and Variability to understand the logistical challenges of different types of SKUs
    • 15. Top 7% of SKUs account for 80% of units sold !!! Typical ABC SKU Stratification SKUs Cum.%Units 1-2 3-44 45 - 142 143 - 558 22% 80% 95% 100% Example SKU Stratification % SKUs .004% 7% 18% 75% % Units 22% 58% 15% 5% # of SKUS Cum % Volume 100 90 80 70 60 50 40 30 20 10 0 0 25 50 150 200 75 100 125 300 400 450 500 550 A SKUs B SKUs C SKUs
    • 16. Volume AND Variability SKU Profiling is Better! Volume Variability Profile Variability (Standard Deviation) 0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 0 100 200 500 1000 2000 3000 10000 Average Weekly Volume
    • 17.
      • “ A”s - Build to Stock
      • “ B”s – Assemble to Order
      • “ C”s - Make to Order
      • “ D”s – Make to Order
      Solving the Mis-Match: Using Different Mfg/Distribution Solutions The goal is to match the manufacturing/distribution strategy to the volume and variability of each SKU 0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 0 100 200 500 1000 2000 3000 10000
    • 18. SKU Stratification Logic
      • A SKUs
        • Medium to high volume SKUs
        • Stable order rate/low variability = easy to plan
        • Longer term lifecycle means little risk of obsolescence
      • B SKUs
        • Medium volume SKUs
        • Order rate low or high variability = harder to plan
        • Longer term lifecycle means little risk of obsolescence
      • C SKUs
        • All low volume SKUs regardless of lifecycle
        • Order rate/high variability = hard to plan
        • Short to medium term lifecycle SKUs have higher risk of obsolescent
      • D SKUs
        • Any volume SKU with very short (e.g. primarily launch) lifecycles
        • Any high volume SKU with high variability
    • 19. The Million Dollar Question: How Do You Know The Min Max Levels for Build to Order SKUs?
    • 20. How Do You Know The Right Levels? SL max = Maximum Stock Level SL min = Minimum Stock Level QTY = Average Daily Demand in Units LT = Manufacturing or Purchasing Lead Time in Days SF = Service Factor as specified in Normal Demand Table NSD = Normal Standard Deviation as specified in Normal Demand Table Dig out your Operations Management book and do the math… or develop a program to calculate it for you automatically!!! The “normal demand” rule shown above is an example of one type of planning rule to set target inventory levels.
    • 21. Agenda
      • The Supply Demand Mis-Match Challenge
      • Solving the Mis-Match
        • SKU Stratification: Volume Variability Profiling
        • Multi-Tier Manufacturing and Distribution
      • Case Studies
    • 22. Example of Tiered Mfg/Dist Strategies FG inventory for maximum order quantity projections only. Order > set order quantities have longer lead time Make to Order Assembly Line or Automation D Non Stocking SKU; Make to Order Make to Order Cellular Manufacturing On Demand Manufacturing* C Fill from FG Stock Kanban / Min-Max Build to Order Assembly Line or Cell B Fill from FG Stock Build to Forecast (comp inventory on hand) Rate Based/Level Loading Assemble Line or Automation A Possible Distribution Strategies Possible Manufacturing Strategies Volume
    • 23. What are the Right Building Blocks for Your Supply Chain? Planning Manu- facturing Distri- bution Trans- portation
    • 24. Different Functions Have Different Techniques that Can Be Leveraged Planning Manu- facturing Distri- bution Trans- portation
      • Rail
      • Ocean
      • TL
      • LTL
      • Parcel
      • Fulfill from Stock
        • inventory
        • via plan
        • Inventory
        • via
        • Kanban/JIT
      • Cross Dock
      • Direct to Store (by pass DC)
      • Build to Forecast
        • Assembly Line
        • Automated
      • Build to Order
        • Cellular Mfg
        • Lean Mfg
      • Make to Order
      • Statistical
      • Historical
      • Market Assumption
      Transportation Distribution Manufacturing Planning/ Forecasting
    • 25. Agenda
      • The Supply Demand Mis-Match Challenge
      • Solving the Mis-Match
        • SKU Stratification: Volume Variability Profiling
        • Multi-Tier Manufacturing and Distribution
      • Case Study - Modus
    • 26. Case Study
    • 27. Software Computing Hardware Telecom EMS / ODM Modus Plans, Sources, Makes, Delivers and Handles Returns for Blue-Chip Clients
    • 28. Modus’ Value Proposition
      • World-class supply chain performance (speed X yield)
        • Perfect delivery (OTIFNE, POI)
        • Ease of doing business
        • Simplification, one stop, advanced customer care, CPFR culture, seamless
        • Lowest asset costs to support optimal channel synchronization
        • Price leverage through competitive advantage
        • Lowest total delivered cost per channel, value for price
      • Integrated supply chain strategy clearly linked to client strategy of growth, share gain and value added programs.
      • Collaborative framework with key customers and suppliers
    • 29.
      • Non-integrated supply chain end-to-end.
        • reactive vs. planned -- corrective vs. preventive
      • De-coupled processes: inventory-people-operating plans, metrics
      • High supply and demand variability resulting in sub-optimal order fulfillment, inventory utilization and costs
      • Ineffective planning and forecasting, lack of visibility of end user demand.
      • Ineffective replenishment in response to fluctuations in demand
      • No formalized S&OP (Sales and Operations Planning) process, no established metrics and rules or contingency planning for demand/supply risks
      • Lack of integrated, balanced metric structure to drive optimal performance
      Problem Statement after Client Assessment
    • 30. Typical Client Objective
      • Create an intelligent supply chain, synchronized through effective use of business process, technology and people to…
        • Maximize customer-facing operational performance
          • OTIFNE fulfillment
          • Total cost as % of revenue
        • Maximize internal-facing operational performance
          • Forecast error during total cycle time (planning and manufacturing)
          • Inventory turns (or DoS) …client and channel
          • Total SCM cost as % of revenue
        • Shrink total cycle time
          • Order to delivery (product from scratch)
          • NPI to market
        • Maximize financial performance
          • Shareholder value add (EVA)
          • Return on net assets
          • Cash Conversion Cycle
    • 31.
      • Agree on shared vision/value proposition
      • Structure organization for change
        • Governance
        • Process leadership
        • Skills/capabilities assessment
      • Assess/process map current state of supply chain: time phased for product and information flow:
        • Concentrated 4 week effort to assess existing structure, vendor sources, facilities, product flow, inventories, supporting information technology, distribution practices, inbound/outbound logistics, performance metrics, etc.
      • Launch formal project … resourced, funded, goaled and governed for results.
      • Establish war room for strategic model simulation and customization.
      • Define and deliver quick wins to gain momentum and credibility.
      • Initiate closed loop metric review process.
      Outline for Action after Initial Assessment
    • 32. Differentiators for Modus
      • Quick time to value: business results driven
      • Quantitative approach: data driven decision analysis
      • Not just consulting, we do the work.
      • Have a total understanding of end-to-end extended supply chain.
      • Track record on operational excellence.
      • Innovative approach. Track record on innovation. Thought leadership.
      • Blended expertise: breadth and depth, cross industry representation.
      • Testimonials and awards.
    • 33. Vision of a Synchronized, Intelligent Supply Chain
      • Develop collaborative vision & single shared view of supply chain
      • Link demand-based decisions to extended supply chain planning & execution
      • Provide analysis, strategy, tactics for integrating sales, operations & fin. plans
      • Align/balance demand requirements with critical supply chain resources
      Supply Chain Planning Decision Support Demand Forecasting Manufacturing (SFC) Order Mgmt/Fulfillment Logistics/Transportation
      • Rules/algorithm-based technology to balance price, quality, availability & product characteristics
      • Modeling & visualization software to simulate full stream supply-demand balancing
      • IFS Demand Planning software
      • Web-based solutions
      • Track all current & future demand information as key input to S&OP
      • Apply dynamic demand planning & forecasting techniques to condition supply chain
      • Apply advanced, tailored product returns forecasting techniques
      • Design tailored returns forecasting methodology
      • Set up demand-driven execution
      • Implement IRG rules to site-based MRP run
      • Deploy “pull” manufacturing practices (MTO, postponement)
      • Apply customized, color-coded Kan-Ban scheduling system for shop orders
      • Deploy SCE rules to integrate supplier commits with operating plans
      • Implement VMI hub best practices
      • Monitor supplier metrics and performance to plan
      • Design/implement rapid response fulfillment/ distribution network and processes
      • Execute based on demand-pull, build to order practices
      • Link logistics partners into shared, collaborative view
      • Route orders to optimal delivery system
      • Real time track & trace: order/delivery status
      • Balance landed cost/service objectives
      CONDITIONING CONDITIONING EXECUTION EXECUTION
      • Establish contract-based collaborative community among reverse logistics partners
      Returns Management Supply Base Execution
      • Incorporate relevant data to S&OP process
      • Tailor SCC/E practices to optimize returns channel
      Supply Base Conditioning
      • Develop strategic sourcing plans
      • Design joint service agreements
      • Provide full demand stream view
      • Set up VMI Hubs
      • Design/monitor effective inbound transportation process
    • 34. Managing the Supply Chain Sales & Operations Planning Inventory Rules Generator Rough-Cut Capacity Planning MRP & Stock Replenishment Shop Orders Purchase Orders Supply Chain Conditioning Supply Chain Execution Customer Forecasts & MMI Customer Intelligence Agreed Forecast Demand History Inventory Targets Daily Customer Orders Key Suppliers Receive Inspect, Put away Issues & Returns Kitting & Ass’y Distribution& Fulfillment Component Deliveries Component Deliveries Suppliers Finished Goods Manufacturing Warehousing Deliveries to Customers
      • Customer
      • Sales
      • Business Management
      • Planning
      • Purchasing
      • Mostly Automated
      • Purchasing
      • Receivers
      • Pickers
      • Assemblers
      • Shippers
    • 35. Modus’ Bolt On Tool: The Inventory Rules Generator Planner
      • Modus’ Inventory Rules Generator (IRG) software tool designed to generate inventory targets and batch sizes based upon the forward demand plan, historical demand data and product characteristics, e.g. Lead-time, batch size constraints, value etc.
      • Inventory targets and batch sizes are calculated for FG and component parts
      • All links to ERP are automated
      • Client specific
      • parameters
      • Service levels
      • EOL dates
      • Targets for Critical Part
      Modus’s Inventory Rules Generator Best view demand Plan from S&OP Meetings Historical Demand From ERP BOMs from ERP
      • Inventory Targets & Lot Sizes
      • Dynamic Shop Floor Signals
      Lead-time from ERP and batch constraints from ERP
    • 36. Stocking SKUs: Setting the ‘safety stock’
        • Safety stock logic will re-order a part as soon as the on-hand inventory falls below the Safety Stock level
        • Kanbans/Reorders can be prioritized (e,g Red/Yellow/Green) for easy identification of what needs to be focused on or expedited
      Target Safety Stock Red Kanbans Yellow Kanbans Green Kanbans Time Inventory
    • 37. Modus’ Mfg/Dist Strategies
      • Use Volume Variability to segment SKUs
      • Developed a bolt-on ERP tool to dynamically trigger shop floor builds
      • Used a mixed model manufacturing and distribution strategy based on SKU profile
      Product Launch SKU’s Retails displays direct to store Longer planning horizons Make to Order typically Product Launches D Non Stocking SKU; Make to Order direct to store or end user Make to Order Cellular Manufacturing & On Demand Manufacturing* C Fill from FG Stock or manufacturing order direct to store or DC Build to Stock from Orders Assembly Line or Cell B Fill from FG Stock direct to store Build to Stock from Forecast (comp inventory on hand) Assemble Line or Automation A Distribution Strategies Manufacturing Strategies Type
    • 38. Results -- Resolving the Tension Between Inventory and Service Level IRG planning tool & processes applied part availability issues resolved in 45 days
    • 39. Overall Impact of Efforts After 1 Year
    • 40. © 2003 Modus Media International, Inc. All rights reserved.
    • 41. Client Satisfaction “Sampling” Sun Micro 2003 Meritorious Vendor Award Intuit Inc. Supplier Award for Supply Chain Excellence Microsoft 2003 Value Excellence Award Handspring 2003 Supply Chain Award SanDisk Continuous Improvement Award Retail Quality 2003 Macromedia 2003 Supply Chain Award Adobe 2004 Partner Award Intuit 2003 Supply Chain Excellence Award
    • 42. Solving For The Supply Demand Mis-Match: Strategy and Case Study Mark Kelly General Manager Modus Media International www.modus.com ACS 2004 Symposium “ Winning with Certainty in Uncertain Times” April 21 st – 23 rd , 2004 Myrtle Beach, SC – Kingston Plantation

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