CHAINalytics, Empowering Fact Based Decisions Across Your Supply Chain
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This document discusses strategies for optimizing supply chain networks through the use of analytics. It provides examples of how optimization analyses often produce results that contradict conventional wisdom, such as recommending closing an existing plant rather than investing in it. The document emphasizes that simple strategies are often not as effective as tailored approaches informed by demand characteristics. It also outlines factors to consider when designing tailored supply chain networks, such as demand volume, variability, and velocity to determine appropriate inventory deployment and distribution strategies.
CHAINalytics, Empowering Fact Based Decisions Across Your Supply Chain
- 1. Confidential Enablers for Maturing Your S&OP Processes
- 2. Click to edit Master title style Demand (customer) Transportation Distribution & Inventory Supply & Manufacturing How much demand will we generate? At what service level can we profitably satisfy demand? At what point in my supply chain should I decouple push vs. pull? What is the best flow path? How should we transport product through the supply chain? What activities should we outsource? How much and where should inventory be positioned in the supply chain? When should we buy or make product to make best use of capacity? What infrastructure is required for manufacturing & distribution? 2 We Support Value-Driven Supply Chain Decisions
- 3. Click to edit Master title styleSome of Our Consulting Clients 3 FOOD AND BEVERAGE RETAIL HOME/OFFICE DURABLES HEALTHCARE HOME/OFFICE NON DURABLES OTHER INDUSTRIES SERVED • 62 of the Fortune 500 • 9 of the Top 15 US Retailers • 13 of AMR’s Top 25 Supply Chains • 5 of the Top 20 Global Forest and Paper Companies • 8 of the World’s 25 Largest Food & Beverage Mfgs • 9 of the Top 10 Consumer Goods Supply Chains., SC Digest Packaging LSPChemical/ProcessAuto/Industrial Utilities/ Telecomm/Media
- 4. Click to edit Master title style 4 Selected S&OP Objectives Increase Profits Free Up Capacity Increase Flexibility Manage Complexity Business Strategy • Competitive Differentiation • Geo Strategy • Financial Targets Financial Planning • Revenue Forecast • Budgeting • Capital Plans • Cost Control Market Planning • Prod Forecast • Promo Plans • Brand/Channel Strategy & Pricing R & D CategoryMgmt • New Prod Into • Prod Lifecycle Plan • Prod Mix/ Pricing / Placement Sales Planning • Sales Forecasts • Customer Business Policies/Plans Demand Planning • Historical Demand • Stat Forecasts SUPPLY DEMAND CORPORATE Supply Planning • Prod Forecast • Promo Plans • Brand/Channel Strategy & Pricing Demand Management • Product Allocation Operations Planning • Sales Forecasts • Customer Business Plans • Product Allocation Logistics Planning • Historical Demand • Stat Forecasts
- 5. Click to edit Master title style 5 Selected S&OP Objectives Analytical Enablers Increase Profits Free Up Capacity Increase Flexibility Manage Complexity Cost-To-Serve Models Product & Customer Portfolio Management Segmentation/ Tailored SC Networks Network Design and Analysis Inventory Deployment and Policy Optimization
- 6. Click to edit Master title style Reasons Companies Initiate Network Studies Cost Reduction Clear Leader and Growing Source: 184 Chainalytics’ employee project experiences 1995-1999 2000-2004 2005-2009 Never Done Thought It Was Time 11% 2% 0% Develop Internal Compentancy 4% 4% 8% New Markets 9% 9% 2% New Management 0% 6% 11% Excess/Insufficient Capacity 20% 9% 8% Merger/Acquisition/Divestiture 9% 15% 12% Cost Reduction 35% 38% 46% 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Cost Reduction 41% Merger, Acquisition, Divestiture 12% Excess/Insufficient Capacity 11% NewManagement 6% NewMarkets 6% Develop Internal Compentancy 6% Never Done Thought It Was Time 3% Process Re-engineering 3% Annual Planning Process 3% Politcal/Regulatory 2% NewProduct Introductions 2% Sourcing Change 2% Assess 3PL Outsourcing 2% IncreaseService 1% Trend Last 10 Years Trend Last 5 Years 6
- 7. Click to edit Master title style Customer/Channel Segmentation Flow Path Service Level Strategy Service Territory Alignment Inventory Deployment Mode Usage Supply Chain Risk Assessment Master/Tactical Planning Social Responsibility Recent Focus Areas in Supply Chain Network Design Best Use of Current Networks Network Optimization Inventory Optimization Simulation Transportation Modeling Total Cost to Serve Portfolio Management Types of Analysis Modeling Technologies 7
- 8. Click to edit Master title style 8 Periodic versus Continuous Analysis Approach Keeps Network In Tune, Ability to React EFFORTNETWORKCOSTS Lost OpportunityActual $ Optimal $ Typically 24+ Months TIME •Require months of concentrated, cross-functional effort •Do not support answering tactical or ad-hoc questions with holistic, fact-based analysis in the interval between major studies •Require resources to “re-learn” the model (and perhaps the business) •Lose potential opportunities by allowing the network to atrophy during the typical 12-24 month gap between major studies Periodic EFFORTNETWORKCOSTS TIME Initial Study Actual $ Optimal $ •Does not completely eliminate spikes in effort, but reduces their effort & duration •Supports ad-hoc questions with holistic, fact-based analysis •Changing costs, demand, customers & requirements, and product mix •Potential M&A activity •Support freight, labor, and procurement negotiations •Ensures the network remains optimal: • Plant-DC-Customer assignments, Manufacturing line configuration •Allows resources to remain constant ,maintain expertise in model & business Continuous
- 9. Click to edit Master title style Design Projects Supported by Analytics and Optimization Results Typically Contrary to Conventional Wisdom 81.8% 73.2% 83.6% 83.4% 83.6% 95% 100% 100% 100% 100% 85% 62.1% 55.0% 61.4% 61.4% 61.4% 50% 55% 60% 65% 70% 75% 80% 85% 90% 95% 100% BASELINE 1 Best Use of Existing 2 Optimal Machine Deployment 3a Close Garland 3b Close St Joe %Make Commodity Wire M/B Filler M/B Pocket Only M/B Sewn Book M/B Company planned to outsource these products. Using Activity Based Costing in the study showed they should maintain or increase amount made in plants. $0 $10 $20 $30 $40 $50 $60 $70 $80 Millions Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Company had always built a significant amount of inventory in non-peak season (Sep-Nov). Studied demonstrated ability to not build during this timeframe. 9 138.3 129.7 129.2 127.2 124.8 124.1 121.2 120.6 116.6 135.2 127.0 122.2 117.9 124.3 126.7 130.7 Achievable St Joe Total Costs In Play Targeted St Joe Total Costs In Play Company planned to invest significantly in existing Plant 1. Greatest savings came from closing down Plant 1.
- 10. Click to edit Master title style Design Projects Supported by Analytics and Optimization Results Typically Contrary to Conventional Wisdom%ofSKUs Base 0% 0% 1% 18% 80% 2% Strategy 20% 6% 9% 9% 57% 12% Strategy 58% 8% 6% 9% 20% 18% Strategy 69% 7% 5% 4% 14% 1 2 3 4 5 Company believed that vast majority of their SKU’s (80%) should be stocked at ALL locations. Optimal deployment strategy indicated 70% of SKU’s should only be stocked at ONE location. $- $10 $20 $30 $40 $50 $60 $70 $80 $90 Network Devices Displays Printers & Office Equipment Supplies & Media Security Devices Millions Inventory Value Inventory Value - SMO 17% 8% 17% 11% 10% Company believed that all SKU’s within a Group needed to have the same service level. By optimizing the service level of each sku to maximize profit, while retaining the overall service level for the Group, inventory was reduced by 14% 10
- 11. Click to edit Master title style 11 Simple Strategies and Policies Typically Do Not Provide Best Results Blackjack Strategies Betting: Hit/Stick: Split/Double: House Advantage: Typical Player Same Base Unit/Random Hit only if cant bust Split Pairs/Double on 10/11 1.5 to 5% 8 decks, H17, DAS, No Surrender, Peek Estimated casino edge for these rules: 0.69 % Dealer Upcard You r Han d 2 3 4 5 6 7 8 9 10 A 5 H H H H H H H H H H 6 H H H H H H H H H H 7 H H H H H H H H H H 8 H H H H H H H H H H 9 H D D D D H H H H H 10 D D D D D D D D H H 11 D D D D D D D D D D 12 H H S S S H H H H H 13 S S S S S H H H H H 14 S S S S S H H H H H 15 S S S S S H H H H H 16 S S S S S H H H H H 17 S S S S S S S S S S A,2 H H H D D H H H H H A,3 H H H D D H H H H H A,4 H H D D D H H H H H A,5 H H D D D H H H H H A,6 H D D D D H H H H H A,7 DS DS DS DS DS S S H H H A,8 S S S S DS S S S S S A,9 S S S S S S S S S S 2,2 P P P P P P H H H H 3,3 P P P P P P H H H H 4,4 H H H P P H H H H H 5,5 D D D D D D D D H H 6,6 P P P P P H H H H H 7,7 P P P P P P H H H H 8,8 P P P P P P P P P P 9,9 P P P P P S P P S S T,T S S S S S S S S S S A,A P P P P P P P P P P Dlr 2 3 4 5 6 7 8 9 10 A Key: H = Hit S = Stand P = Split D = Double (Hit if not allowed) DS = Double (Stand if not allowed) Basic Strategy Same Base Unit/Structured Player/Dealer Cards Player/Dealer Cards 0.5% Card Counter Base Unit Multiplier via Remaining Card Favorability (Running Count) Basic altered by Favorability Basic altered by Favorability -2% (Hit and run ~ -4%)
- 12. Click to edit Master title style 12 Designing Tailored Supply Chain Networks Demand Characteristics Drive Inventory Deployment Item-Locations 194 1% COGS $250,900,000 34% Item-Locations 3,395 20% COGS $428,000,000 59% Item-Locations 13,791 79% COGS $51,100,000 7% Item-Locations 11,283 65% Item-Locations 4,001 23% Item-Locations 2,096 12% COGS 41% COGS 23% COGS 35% Fast: >1,000/Week Demand Variability DemandVelocity High: >1.5 $302,900,000 Medium: 0.6 - 1.5 $170,200,000 Low: < 0.6 $256,900,000 Slow: < 25 Units/Week Medium: > 25 Units and <1,000/Week COV (Std Dev Demand / Mean Demand) 0 10 20 30 40 50 60 70 80 BEAUTY HOMECARE NUTRITION PERSONALCARE Item-Locs(H's):100.29, 57.7% COGS:$(M's) 22.9, 3.1% 0 10 20 30 40 50 60 70 80 BEAUTY HOMECARE NUTRITION PERSONALCARE Item-Locs(H's):11.63, 6.7% COGS:$(M's) 159.9, 21.9% 0 10 20 30 40 50 60 70 80 BEAUTY HOMECARE NUTRITION PERSONALCARE Item-Locs(H's):0.91, 0.5% COGS:$(M's) 120.1, 16.5% 0 10 20 30 40 50 60 70 80 BEAUTY HOMECARE NUTRITION PERSONALCARE Item-Locs(H's):30.5, 17.5% COGS:$(M's) 18.9, 2.6% 0 10 20 30 40 50 60 70 80 BEAUTY HOMECARE NUTRITION PERSONALCARE Item-Locs(H's):9.22, 5.3% COGS:$(M's) 120.1, 16.5% 0 10 20 30 40 50 60 70 80 BEAUTY HOMECARE NUTRITION PERSONALCARE Item-Locs(H's):0.29, 0.2% COGS:$(M's) 31.2, 4.3% 0 10 20 30 40 50 60 70 80 BEAUTY HOMECARE NUTRITION PERSONALCARE Item-Locs(H's):7.12, 4.1% COGS:$(M's) 9.3, 1.3% 0 10 20 30 40 50 60 70 80 BEAUTY HOMECARE NUTRITION PERSONALCARE Item-Locs(H's):13.1, 7.5% COGS:$(M's) 148, 20.3% 0 10 20 30 40 50 60 70 80 BEAUTY HOMECARE NUTRITION PERSONALCARE Item-Locs(H's):0.74, 0.4% COGS:$(M's) 99.6, 13.6% Candidates for Centralization Candidates for Full Stocking or Direct Ship
- 13. Click to edit Master title style Reducing Stocking Locations Increases Product Velocity and Reduces Demand Variability 0% 200% 400% 600% 800% 1000% 1200% 1400% 1600% 1800% 0.0 50.0 100.0 150.0 200.0 250.0 Mean Days Between Ships COVDailyDemand 0% 200% 400% 600% 800% 1000% 1200% 1400% 1600% 1800% 0.0 50.0 100.0 150.0 200.0 250.0 Mean Days Between Ships COVDailyDemand Product Stocked at All Locations Product Stocked at Single Location 0 1 2 3 4 5 6 7 8 1 2 3 4 5 Stocking Locations Days 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 DemandVariability Avg Mean Days Between Shipments Avg Demand Variability 13
- 14. Click to edit Master title style 14 Key Attributes Determine Bulk & Direct to Store Articles Determine Stored vs. Not Stored Determine Cross Dock vs. Flow Through 59,619 total Items 56,199 Items through the future DCs 44,687 Items either Flow Through or Cross Determine Flow Through Manual & Automation 16,770 Items Flow Through • 994 Bulk Items • 2,426 Direct to Store Items • 11,512 total Items Stored • 8,114 Items Seasonally stored • 27,917 Items Cross Docked • 14,112 Items Flow Through Automation • 2,658 Items Flow Through Manual The process that mapped Items to Flow Channels is outlined here. Key Items attributes and costs drivers were considered in assigning Articles to Flow Channels. Designing Tailored Supply Chain Networks Product Characteristics Drive Flow Paths Attributes Live Goods Hazmat Remote Vendor/Store Imported Seasonal High Demand Variability Long Lead Time Short Lead Time High Product Value Small Cube/Carton Sizes Low Pick Density Conveyable Long Lead Time Low Product Value Not Small Cube/Carton Sizes High Pick Density Conveyable=Automation NonConveyable=Manual Directto Store StorageCrossDockFlowThrough
- 15. Click to edit Master title style 15 Customer & Product Portfolio Management Who and What is Driving our Profitability Number of Products • A products (22%) account for 80% of revenue and 81% of contribution margin, and 10% of the space • While C products (46%) account for 5% of revenue and 4% of margin contribution, and 60% of storage space There may be opportunities to reduce complexity by addressing the portfolio size and business practices associated with the large tail of low revenue-generating PRODUCTS 22% 24% 46% 8% 80% 15% 5%0% 81% 15% 4%0% 10% 18% 60% 12% A B C D Items Revenue Margin Storage Space
- 16. Click to edit Master title style 6% 8% 85% 1% 80% 15% 5%0% 71% 14% 15% 0% 5% 8% 80% 7% A B C D 16 Number of Customers There may be opportunities to reduce complexity by addressing the portfolio size and business practices associated with the very large tail of low revenue-generating CUSTOMERS Customer & Product Portfolio Management Who and What is Driving our Profitability Customers Revenue Margin Storage Space • A customers (6%) account for 80% of revenue and 71% of contribution margin, and 5% of the space • While C Customers (85%) account for 5% of revenue and 15% of margin contribution, and 80% of storage space
- 17. Click to edit Master title style Stage I Reacting II Anticipating III Collaborating IV Orchestrating Balance: S&OP Goal Development of an operational plan Demand and supply matching Profitability Demand sensing, and conscious tradeoffs for demand shaping to drive an optimized demand -response Ownership S = Sales OP = Factory capabilities S = Sales and Marketing Plans OP = Planning and factory capabilities S = Go to Market Plans OP = Design of demand driven plan, make & deliver processes S = Go to Market Strategies and Solutions OP = Translation of demand into plan, make, deliver, source and service strategies, with connection to execution Metrics Order fill rate, asset utilization, inventory levels Order fill rate, forecast error, inventory turns, functional costs Demand error, customer service, working capital, total costs Demand risk, customer service, cash flow, market share and profit Techniques/ Technology Excel spread sheets, ERP Supply chain capabilities Excel, demand forecasting, inventory management, general supply chain planning tools, inventory optimization what if analysis for demand shaping, what if analysis for reconciliation with financial plans, cost to serve, Analytics to find risk - value trade offs, risk management techniques, price optimization, complex simulation 17 Four Stages of S&OP Maturity Companies Stuck in Early Stages Source : AMR Research/ 2009 S&OP Study of 182 Companies S OP S OP S OP S OP 20% 47% 19% 14% 20% 47% 19% 14% 20% 47% 19% 14% 20% 47% 19% 14% SherTrack Demand-Driven Predictive Manufacturing
Editor's Notes
- #4: 3M, Access Point Medical Inc., Acklands Grainger, Acuity Brands, After Hours, Allsteel, Ameren Energy, American Wood Moulding, Anheuser Busch, Arvato, Avery Dennison, Bayer, BIG Lots, Inc., Boeing, Caterpillar Logistics, Colgate-Palmolive, ConAgra Foods, Con-Way Logistics, Convatec, C&S, Clorox, Coca-Cola, Cooper Tire & Rubber Company, Dana Corporation, Dawn Foods, Domtar, Exel Transportation Services, Inc., Fasson, FedEx Express Corp., Ferrero USA, Frito-Lay, Formica, General Mills, Grodej, Georgia Pacific, Harcourt Education, Harman, HEB, Hewlett-Packard Company, Huawei, Ingram Micro, International Paper, INVISTA, Janus, JC Penney, JM Huber, K&N Lead Logistics, Leggett & Platt, Lenovo, LG Electronics, Linens & Things, Lexmark, MeadWestvaco, Lockheed martin, Lyondell, MassTech, Menlo Logistics, ModusLink Mohawk Industries, Nestle , New Breed Logistics, Nicor, Nestle, Ocean Spray, Orco, Owens-Illinois, PepsiCo, PSS Medical, Quaker Oats, Reliance Industries, Ricoh Corporation, Ryder Integrated Logistics, Samsung, Scholle Corporation, Schreiber Foods, Smart & Final, Stericycle, Sysco, Tempur-Pedic, The Home Depot, Toys 'R' Us, Tropicana, Tyco Healthcare, US FoodService, Walmart.com USA LLC, YKK, Simmons, Kroger, Kimbery-Clark, P&G, Oldcastle, Polo, Amway, PapaJohns, Land O Lakes, Niagara Bottling, SC Johnson, Momentive, JMC Steel Group, G3 Enterprises