Supply Chain Segmentation & Analytics
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Supply chain consultant and author Dr. Gerhard Plenert and AIMMS' Chris Gordon discuss a practical approach to Supply Chain Segmentation & Analytics.
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Supply Chain Segmentation & Analytics
- 1. Supply Chain Segmentation & Analytics - Moving from Theory to Implementation
- 2. Meet the Presenters Dr. Gerhard Plenert – Consultant and Author Dr. Gerhard Plenert has been helping organizations execute operational and supply chain transformations for more than twenty years. He was a tenured full professor at California State University, Chico, and a professor at BYU Provo, BYU Hawaii, the University of Malaysia, and the University of San Diego. He has worked for the largest companies in the world, including companies like Aramco, Microsoft, Cisco, HP, Johnson and Johnson, Shell, Apple, Ford, Nike, Google, Cisco, and Rolls Royce. Chris Gordon –VP NorthAmerica at AIMMS Chris has worked in supply chain consulting and operations across Europe, the US and India for more than 25 years. He’s driven dozens of supply chain initiatives with a heavy focus on leveraging analytical evidence to promote major business change.
- 3. Objectives • Share a consumable definition of Supply Chain Segmentation • Provide a step-by-step guide to achieving segmentation value • Share a series of examples to increase initiative speed and time to value • Share where supply chain segmentation can go next with leading edge use of optimization • An opportunity to engage in this ongoing dialogue with the presenters and your industry peers
- 4. What is Supply Chain Segmentation (SCS)? SCS is about Differentiating Groupings by: • Region / Location • Volumes • Product Characteristics • Etc.
- 5. What is Supply Chain Segmentation (SCS)? • SCS finds common Characteristics within the differentiated groupings • SCS identifies optimal methodologies around each group
- 6. SCS – How it works 3-Pronged Approach to Maximize Return on Availability B – Reduce Cost • Production • Logistics • Warehousing • Inventory holding cost • Planning Misalignments • Technology • Obsolescence A – Manage Product Lifecycle Stages • Launch / New product introduction • Active – Growth • Stable - Maturity • Declining • End-Of-Life C – Increase Benefits • Revenue • Margin • Establish Yourself as the Preferred Supplier • Market Share • Competitor Substitution Avoidance • Ease of Doing Business • Economies of Scale
- 7. DeclineMaturityGrowthIntroduction New Product – Phase In Demand Planning Horizon Identify the Life Cycle Stages of the Product End of Life Product – Phase Out ROA B A C
- 8. Identify cost drivers that impact return on availability Cost of Availability High Medium Low Minimize Cost ROA B A C Cost Drivers Impact of the Driver Attributes Lifecycle length Product avaiability / obsolesence Long Medium Short Volatility Level of inventory buffering Low Medium High Product Customization Interdependencies / stock outs Low Medium High Product Criticality Customer operational shutdowns Low Medium High Geography / Location Pipeline length / inventory staging Onshore Nearshore Farshore Product Turnaround Shelf Life / inventory levels Fast Medium Slow Gross Margin Risk / profitability High Medium Low Seasonality Inventory buildup / planning Heavy Medium None Channel Hazards Planning / inventory costs High Medium Low
- 9. Identify the customer segments that drive benefits Segments Definition Tier-1 High-priority customers with strategic / critical importance to our company (The 20 % of the customers that make up 80 % of our business) Tier-2 Medium priority customers who deserve the next best level of Supply chain support Tier-3 Low-priority customers who are relatively at the lowest level in the hierarchy (The majority of our customers, around 50 to 60 %, who make up only about 20 % of our business) ROA B A C
- 10. Segmentation tailored to your key business drivers Attribute Impact Cost Drivers Impact of the Driver Low High Lifecycle length Product avaiability / obsolesence Volatility Level of inventory buffering Product Customization Interdependencies / stock outs Product Criticality Customer operational shutdowns Geography / Location Pipeline length / inventory staging Product Turnaround Shelf Life / inventory levels Gross Margin Risk / profitability Seasonality Inventory buildup / planning Channel Hazards Planning / inventory costs
- 11. Example – Segmentation Matrix to maximize return on availability LifecycleStage CostofAvailability Tier 1 Customers Tier 2 Customers Tier 3 Customers Launch Low Med High Active Low Med High EndofLife Low Med High
- 12. LifecycleStage CostofAvailability Tier 1 Customers Tier 2 Customers Tier 3 Customers Availability Lead Time SC Business Model Availability Lead Time SC Business Model Availability Lead Time SC Business Model Launch Low High 5 Days Custom Medium 25 Days Agile Medium 30 Days Agile Med High 5 Days Custom Medium 30 Days Agile Low 35 Days Efficient High High 5 Days Custom Medium 35 Days Efficient Low 40 Days Efficient Active Low High 10 Days Efficient High 25 Days Efficient High 30 Days Efficient Med High 10 Days Efficient High 25 Days Efficient Medium 30 Days Efficient High High 30 Days Agile Medium 30 Days Efficient Low 35 Days Efficient EndofLife Low High 15 Days Efficient Medium 35 Days Efficient Low 40 Days Efficient Med High 35 Days Agile Low 40 Days Efficient Low 45 Days Efficient High High 40 Days Agile Low 45 Days Efficient Low 50 Days Efficient Example – Segmentation Matrix to maximize return on availability
- 13. LifecycleStage CostofAvailability Tier 1 Customers Tier 2 Customers Tier 3 Customers Availability Lead Time SC Business Model Availability Lead Time SC Business Model Availability Lead Time SC Business Model Launch Low High 5 Days Custom Medium 25 Days Agile Medium 30 Days Agile Med High 5 Days Custom Medium 30 Days Agile Low 35 Days Efficient High High 5 Days Custom Medium 35 Days Efficient Low 40 Days Efficient Active Low High 10 Days Efficient High 25 Days Efficient High 30 Days Efficient Med High 10 Days Efficient High 25 Days Efficient Medium 30 Days Efficient High High 30 Days Agile Medium 30 Days Efficient Low 35 Days Efficient EndofLife Low High 15 Days Efficient Medium 35 Days Efficient Low 40 Days Efficient Med High 35 Days Agile Low 40 Days Efficient Low 45 Days Efficient High High 40 Days Agile Low 45 Days Efficient Low 50 Days Efficient Example – Segmentation Matrix to maximize return on availability
- 14. Example – Segmentation Matrix to maximize return on availability - Aerospace LifecycleStage CostofAvailability Tier 1 Suppliers Tier 2 Suppliers Tier 3 Suppliers Criticality Lead Time SC Business Model Criticality Lead Time SC Business Model Criticality Lead Time SC Business Model Launch Low High 120 Days Custom Medium 120 Days Efficient Medium 120 Days Efficient Med High 120 Days Custom Medium 120 Days Efficient Low 120 Days Efficient High High 120 Days Custom Medium 120 Days Efficient Low 120 Days Efficient Active Low High 10 Days Efficient High 20 Days Efficient Low 30 Days Efficient Med High 10 Days Agile High 20 Days Efficient Medium 30 Days Efficient High High 10 Days Agile Medium 20 Days Agile Low 30 Days Efficient EndofLife Low High 20 Days Efficient Low 30 Days Efficient Low 40 Days Efficient Med High 30 Days Efficient Low 40 Days Efficient Low 45 Days Efficient High High 40 Days Efficient Low 50 Days Efficient Low 50 Days Efficient 1 6 2 4 3 5
- 15. Example – Segmentation Matrix to maximize return on availability - Pharmaceutical LifecycleStage CostofAvailability Tier 1 Customer Tier 2 Customer Tier 3 Customer Shipping Criticality Lead Time SC Business Model Shipping Criticality Lead Time SC Business Model Shipping Criticality Lead Time SC Business Model Launch Low Low 2 Days Custom Low 2 Days Efficient Low 3 Days Efficient Med Medium 2 Days Custom Medium 2 Days Efficient Medium 3 Days Efficient High High 1 Day Custom High 1 Day Efficient High 1 Day Efficient Active Low Low 2 Days Efficient Low 2 Days Efficient Low 3 Days Efficient Med Medium 2 Days Efficient Medium 2 Days Efficient Medium 3 Days Efficient High High 1 Day Efficient High 1 Day Efficient High 1 Day Efficient EndofLife Low Low 2 Days Efficient Low 2 Days Efficient Low 3 Days Efficient Med Medium 2 Days Efficient Medium 2 Days Efficient Medium 3 Days Efficient High High 1 Day Efficient High 1 Day Efficient High 1 Day Efficient 1 2 4 3
- 16. Example – Segmentation Matrix to maximize return on availability – Hi Tech LifecycleStage CostofAvailability Tier 1 Customer Tier 2 Customer Tier 3 Customer Product Availability Safety Stock / Inventory Buffering Levels SC Business Model Product Availability Safety Stock / Inventory Buffering Levels SC Business Model Product Availability Safety Stock / Inventory Buffering Levels SC Business Model Launch Low High Max Custom High Max Custom High Medium Custom Med High Max Custom High Max Custom High Medium Custom High High Max Custom High Max Custom High Medium Custom Active Low High Medium Agile High Medium Agile High Medium Agile Med High Medium Agile High Medium Agile High Medium Agile High High Medium Agile High Medium Agile High Medium Agile EndofLife Low Low Minimum Efficient Low Minimum Efficient Low Minimum Efficient Med Low Minimum Efficient Low Minimum Efficient Low Minimum Efficient High Low Minimum Efficient Low Minimum Efficient Low Minimum Efficient 1 2 4 3
- 17. Supply Chain Characteristics High Tech Segmentation Example 1 2 3 4 Forecast S&OP Time Series Associative Production Planning and Scheduling S&OP ATP CTP Demand Pull EOQ BTS/MTS BOO/MTO Min/Max OIL 2-Bin ROP Operational Processes VMI LSS JIT SS Automat ion Levels Manual Shop Floor MES Metrics Motivation Inventory Operating Costs Customer Quality SCS Characteristics Mapping Example – High Tech
- 18. Supply Chain Characteristics Aerospace Segmentation Example 1 2 3 4 5 6 Targets Planning Cadence Bi-Weekly Bi-Weekly Weekly Bi-Weekly Bi-Weekly On Demand % of SKUs 15% 40% 5% 15% 20% 5% % of Revenue 20% 50% 3% 10% 15% 2% % of Inventory 15% 40% 5% 15% 20% 5% % of Planning Effort 50% 5% 10% 20% 5% 10% Touch Level of Planners High Low Low Medium Low Low SCS Goal Mapping Example - Aerospace
- 20. AIMMS is being used by leading companies to gain a competitive edge 4 time co-winner of the Franz Edelman award Trusted by leading companies: With award-winning results:
- 21. Thank You! • If you have any questions, please contact the presenters: Dr. Gerhard Plenert, PhD gerhard@gerhardplenert.com www.gerhardplenert.com 916-233-9758 Chris Gordon VP North America, AIMMS Chris.Gordon@AIMMS.com 425-458-4024
- 22. Experience Business Optimization Like Never Before Empower your teams with advanced analytics to drive better decisions 425-458-4024 info@AIMMS.com