CSCMP India 2012 Conference 1-2 June Mumbai, India ITC Maratha MUMBAI

Transcription

1 CSCMP India 2012 Conference 1-2 June Mumbai, India ITC Maratha MUMBAI Creative Approaches to Supply Chain Profitability: A Global Perspective from India

2 Sales, Inventory, and Operations Planning: Fueling Your Company s Growth Jeff Metersky Vice President, Sales, Inventory & Operations Planning Chainalytics

3 Agenda Who is Chainalytics? Asia Market Growth and Implications Sales & Operations Planning Introduction Analytical Enablers for Effective S&OP

4 Who is Chainalytics? Our Genesis Market Lacked Proven, Focused Supply Chain Analytics Competence Best Analytical Minds in Supply Chain 1 st Named to 100 Great Supply Chain Partners List by SupplyChainBrain; Recognized for 8 Years Running Launch of Freight Market Intelligence Consortium (FMIC) Mike Kilgore named a Pro to Know by Supply & Demand Chain Executive; Steve Ellet, Gary Girotti, Irv Grossman, Jeff Metersky, Matt Harding, and Kevin Zweier also named Pros to Know Established Chainalytics India Private Limited in Bangalore FMIC named Top Supply Chain Innovation by Supply & Demand Chain Executive Named to ARC Advisory s 10 Coolest Supply Chain Boutiques Launch of Sales & Operations Variability Consortium (S&OVC) Strategic Growth via Mergers & Acquisitions Supply Chain Operations (Chainnovations) Packaging Optimization (Adalis Packaging Solutions Group) TODAY Over 80 FTEs Worldwide Our Clients More Than 180 Unique Clients 14 of AMR s Top 25 Supply Chains 57 Fortune 500 Companies 5 of Top 10 Retailers 7 of Top 10 Food & Beverage Manufacturers 5 of Top 10 CPG Companies 6 of Top 10 Forest, Paper and Packaging Companies Our Experience More Than 375 Engagements Empowering Fact-Based Decisions Across Your Supply Chain 4

5 Value-Driven Supply Chain Decisions Years Supply Chain Design Quarters Packaging Optimization Months Weeks Planning Horizon Sales, Inventory & Operations Planning Logistics Operations Transportation Service Supply Chain When should we buy or make product to make the best use of our capacity? What is the best flowpath? How much and where should inventory be positioned in the supply chain? At what service level can we profitably satisfy demand? Should our warehousing and material operations be insourced or outsourced? How should we transport product through the supply chain? Can we reduce our transport and logistics costs by improving cube utilization? How well do our current operations mitigate repair and warranty costs? How can we increase visibility to stakeholders? 5

6 Agenda Who is Chainalytics? Asia Market Growth and Implications Sales & Operations Planning Introduction Analytical Enablers for Effective S&OP

7 % Worldwide Middle Class Rapid Rise in Asian Middle Class Population 25% 20% 15% 10% 5% 0% 3% 2% 24% Asian Population 16% Asian Purchasing Power 1 1 Asia's middle class is expected to continue it s growth trajectory to reach 2 Billion by (More than double current figure.) By 2030, middle class Asians will be the next global consumers and assume the role of US & European middle classes 1 Historical Data Excludes Japan Source: Rise of middle classes in India, China key to growth in Asia, The Economic Times, April 4, 2012

8 Millions Rapid Rise in Indian Middle Class Population India s middle class is projected to reach 267 Million by Indian Middle Class Population Source: India's middle class population to touch 267 million in 5 yrs, Hindustan Times, February 6, 2011

9 Significant Expenditure on Food in Emerging Markets Food Share of Household Expenditures RUSSIA 28% NIGERIA 40% MEXICO 24% INDIA 35% PAKISTAN 46% ITALY 14% GERMANY 11% EGYPT 38% BRAZIL 25% JAPAN 14% KENYA 45% CHILE 23% FRANCE 14% SPAIN AUSTRALIA13% 11% CANADA 9% U.S. 7% UK 9% INDONESIA 43% CHINA 33% Source: Nielson Emerging Markets Global Forces White Paper March 2012

10 New Product Introductions New Product Introductions Food and Beverage Nonfood 50,000 45,000 40,000 35,000 30,000 25,000 20,000 15,000 10,000 United States From in the USA there were only 10 times were new product introduction declined for CPG products (1) 2009 India ranked 6 th Globally for Personal Care product introductions (2) 2010 FMCG Companies introduced 10,000+ New SKUs in India (3) 5, Sources: (1) Datamonitor; (2) Personal Care in India Research and Markets May 2010; (3) Eat, pray, love innovations Business Today India June 12, 2011

11 New Economy Based on Information Age Brick & Mortar Set Pricing Supply Economy Traditional Media Boundaries Negotiated Pricing Boundless Demand Economy + Varied Distribution Points + Traditional and New Media FIXED MODEL FLEXIBLE MODEL Source: Nielson Emerging Markets Global Forces White Paper March 2012

12 Challenge for Asian FMCG Companies and Retailers Build and Maintain Brand Loyalty Under Rapid Pace of New Product Introduction Associated SKU Proliferation Demand Uncertainty and Volatility Expanded Supply Chains with Global Coordination and Local Execution Multi-Channel Fulfillment Designed for: Flexibility, Responsiveness, Adaptability

13 Agenda Who is Chainalytics? Asia Market Growth and Implications Sales & Operations Planning Introduction Analytical Enablers for Effective S&OP

14 Sales & Operations Planning is Crucial for Success CORPORATE Business Strategy Competitive Differentiation Geo Strategy Financial Targets Financial Planning Revenue Forecast Budgeting Capital Plans Cost Control DEMAND R & D Category Mgmt New Prod Into Prod Lifecycle Plan Prod Mix/ Pricing / Placement Market Planning Prod Forecast Promo Plans Brand/Channel Strategy & Pricing Sales Planning Sales Forecasts Customer Business Policies/Plans Demand Planning Historical Demand Stat Forecasts SUPPLY Demand Management Product Allocation Supply Planning Prod Forecast Promo Plans Brand/Channel Strategy & Pricing Operations Planning Sales Forecasts Customer Business Plans Product Allocation Logistics Planning Historical Demand Stat Forecasts 14

15 Selected S&OP Objectives CORPORATE Increase Profits Business Strategy Competitive Differentiation Geo Strategy Financial Targets Financial Planning Revenue Forecast Budgeting Capital Plans Cost Control Increase Flexibility Focus Resources DEMAND R & D Category Mgmt New Prod Into Prod Lifecycle Plan Prod Mix/ Pricing / Placement Market Planning Prod Forecast Promo Plans Brand/Channel Strategy & Pricing Sales Planning Sales Forecasts Customer Business Policies/Plans Demand Planning Historical Demand Stat Forecasts Free Up Capacity Manage Complexity SUPPLY Demand Management Product Allocation Supply Planning Prod Forecast Promo Plans Brand/Channel Strategy & Pricing Operations Planning Sales Forecasts Customer Business Plans Product Allocation Logistics Planning Historical Demand Stat Forecasts 15

16 Effective S&OP Enhances Company Performance Company Performance Performance Drivers Value Chain Solutions Revenue Growth Sales Price Forecast accuracy and fill rates Improved new product introduction Market segmentation and target pricing Margin management and dynamic pricing Return on Capital Employed Cost Reduction COGS SG&A Product Portfolio Management Sourcing strategies Supply Chain efficiency B2B transaction cost management Asset Utilization Working Capital Fixed Assets Demand supply matching Inventory level / placement optimization Network optimization Capacity Utilization Improvement

17 19% Four Stages of S&OP Maturity 14% 19% Many Companies 14% Stuck in Early Stages Stage Balance: S&OP Goal 47% Ownership Metrics Techniques/ Technology 20% S I Reacting Development of an operational plan S = Sales OP = Factory capabilities OP Order fill rate, asset utilization, inventory levels Excel spread sheets, ERP Supply chain capabilities 47% S 20% II Anticipating OP Demand and supply matching S = Sales and Marketing Plans OP = Planning and factory capabilities Order fill rate, forecast error, inventory turns, functional costs Excel, demand forecasting, inventory management, general supply chain planning tools, inventory optimization 47% III Collaborating 19% 14% S Profitability 20% OP 47% S = Go to Market Plans OP = Design of demand driven plan, make & deliver processes Demand error, customer service, working capital, total costs what if analysis for demand shaping, what if analysis for reconciliation with financial plans, cost to serve, 19% 14% S IV Orchestrating 20% OP Demand sensing, and conscious tradeoffs for demand shaping to drive an optimized demand - response S = Go to Market Strategies and Solutions OP = Translation of demand into plan, make, deliver, source and service strategies, with connection to execution Demand risk, customer service, cash flow, market share and profit Analytics to find risk - value trade offs, risk management techniques, price optimization, complex simulation Source: Gartner (AMR Research) 2009 S&OP Study of 182 Companies

18 Agenda Who is Chainalytics? Asia Market Growth and Implications Sales & Operations Planning Introduction Analytical Enablers for Effective S&OP

19 Analytical Enablers for Effective S&OP Integrated Scenario Cost-to-Serve Models Increase Profits Increase Flexibility Product & Customer Portfolio Management Segmentation / Tailored SC Networks Network Design and Analysis Free Up Capacity Manage Complexity Inventory Deployment and Policy Optimization Planning Financial Planning 19

20 Total Cost-to-Serve Perspective To drive consensus, objectivity is needed driven by a comprehensive understanding of the cost and revenue elements associated with customer/product portfolios. Resources Price Leakages Resource Pool Supporting Activity Gross Sales Price Volume Discounts Payment Terms Freight Promotions Bonuses Allowance Pocket Price Waterfall Activity Net Sales Price (Pocket Price) PROFIT Cost Cost o Cost object Object 2 n Object 1 COG Acquired Mfg Distribution Transport Account Mgmt Sales Rep Visits Cost-to-Serve Waterfall Cost Object Supply Chain Marketing & Sales

21 Decisions are Influenced by Total Cost-to-Serve Proper allocation of costs can be an important differentiator between effective and ineffective profitability management. ore Cost-to-Serve Analysis After Cost-to-Serve Analysis duct A - $20K Profit Product A - $20K Loss Before Before Cost-to-Serve Analysis Analysis After After Cost-to-Serve Analysis Analysis enue $ 230,000 Revenue $ 230,000 Product S Product A - $20K $ A - 140,000 $20K Profit Profit COGS Product Product A - $20K A - $ $20K Loss 140,000 Loss Revenue Revenue$ $ 90, ,000 $ 230,000 GMRevenue Revenue $ 90, ,000 $ 230,000 cation COGS COGS $ $ 70, ,000 $ 140,000 Cost-to-Serve COGS COGS $ 110, ,000 $ 140,000 GM GM Net $ $ 20,000 $ 90,000 90,000 GM GMNet (20,000) 90,000 90,000 Allocation Allocation $ $ 70,000 70,000 Cost-to-Serve 110, ,000 Net Net $ $ 20,000 20,000 Net Net (20,000) (20,000) $ Attributed Costs $ Orders $ 30,000 $ $ $ Cust. Srv. Attributed $ Attributed 25,000 Costs Costs $ $ Vendor Orders Mgt. Orders $ $ 25,000 30,000 $ 30, $ $ Channel Cust. Mgt. Srv. Cust. $ Srv. $ 30,000 25,000 $ 25, Vendor Vendor Mgt. Mgt. $ 25,000 $ 25, Channel Channel Mgt. $ Mgt. 30,000 $ 30,

22 Customer & Product Portfolio Management Who is driving our profitability? 12% 15% 15% 46% 4%0% 5%0% 8% A B C D 10% 22% 24% Items 18% Revenue Margin 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. 60% 80% 81% A Products (22%) account for 80% of revenue, 81% of contribution margin, and 10% of the space C Products (46%) account for 5% of revenue, 4% of margin contribution, and 60% of storage space Number of Products

23 Customer & Product Portfolio Management What is driving our profitability? 7% 5% 0% 15% 5%0% 15% 1% 6% 8% 8% Customers Revenue Margin 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. 14% 85% A B C D 80% 71% Storage Space 80% A Customers (6%) account for 80% of revenue, 71% of contribution margin, and 5% of the space C Customers (85%) account for 5% of revenue, 15% of margin contribution, and 80% of storage space Number of Customers

24 Percent of Demand Designing Tailored Supply Chain Networks Demand Patterns Drive Design and Policy 60% Items Demand 50% Phase in, 19% Seasonal, 11% Phase in, 9% Seasonal, 1% 40% 30% Stable, 35% Phase out, 18% Stable - Phase out, 18% Stable, 69% Stable - Phase out, 19% Phase out, 1% 20% 10% 0% Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug Sep Phase out 43.8% 11.9% 10.2% 10.7% 7.4% 5.6% 0.8% 0.8% 1.3% 0.3% 0.1% 0.9% 0.2% 0.1% 0.4% 0.3% 0.8% 2.4% 2.0% Stable - Phase out 7.2% 6.8% 6.6% 9.2% 7.8% 8.7% 6.4% 6.9% 8.2% 5.6% 6.2% 5.0% 5.4% 3.4% 2.5% 1.5% 1.2% 0.9% 0.6% Stable 5.3% 4.5% 4.6% 5.9% 4.9% 6.1% 4.8% 4.9% 5.8% 4.5% 4.8% 5.2% 6.6% 4.9% 6.4% 4.9% 4.8% 6.2% 4.9%

25 Demand Variability Demand Variability Demand Variability Demand Variability Demand Variability Demand Variability Demand Variability Demand Variability Designing Tailored Supply Chain Networks Demand Characteristics Drive Demand Planning Strategies Company A Nestle - Infant Nutrition Company B Nestle - Prepared Foods Company Nestle -Beverage C Company Del Monte D High Med Low Highest FCA Most Low Variability Most High Velocity 11% 11% 0% 0% 1% 0% 0% 0% 19% 16% 3% 0% 4% 2% 1% 0% 70% 13% 22% 35% 95% 3% 13% 79% % Item Locations 39% 26% 35% % Demand 5% 15% 80% Low Med High Demand Velocity High Med Low 32% 30% 1% 0% 3% 2% 1% 1% 35% 20% 10% 5% 23% 2% 6% 14% 34% 7% 10% 16% 74% 1% 8% 65% % Item Locations 57% 22% 22% % Demand 5% 15% 80% Low Med High Demand Velocity High Med Low 24% 23% 1% 0% 2% 1% 0% 0% 36% 25% 9% 3% 18% 3% 6% 9% 40% 9% 13% 18% 81% 1% 9% 70% % Item Locations 57% 22% 21% % Demand 5% 15% 80% Low Med High Demand Velocity High Med Low 36% 29% 5% 2% 7% 2% 2% 4% 38% 19% 13% 5% 23% 3% 6% 13% 27% 4% 12% 11% 70% 1% 7% 63% % Item Locations 52% 30% 18% % Demand 5% 15% 80% Low Med Demand Velocity High Lowest FCA 2 nd Most High Variability Company E Nestle - Confectionary Company F Con Agra Company G Church & Dwight Company Henkel H High Med Low 57% 36% 16% 5% 19% 3% 8% 8% 35% 12% 12% 11% 52% 1% 6% 44% 8% 1% 3% 4% 29% 0% 1% 27% % Item Locations 49% 31% 20% % Demand 5% 15% 80% Low Med High Demand Velocity High Med Low 46% 42% 3% 1% 6% 2% 1% 2% 34% 19% 12% 3% 33% 2% 7% 24% 19% 3% 8% 8% 61% 0% 6% 54% % Item Locations 65% 23% 12% % Demand 5% 15% 80% Low Med Demand Velocity High High Med Low 24% 22% 2% 0% 4% 1% 1% 2% 41% 27% 11% 4% 26% 3% 6% 17% 34% 10% 12% 13% 70% 1% 8% 61% % Item Locations 59% 24% 17% % Demand 5% 15% 80% Low Med Demand Velocity High High Med Low 55% 46% 8% 1% 10% 3% 5% 3% 34% 11% 13% 10% 48% 2% 9% 38% 11% 2% 2% 7% 42% 0% 2% 40% % Item Locations 59% 23% 19% % Demand 5% 15% 80% Low Med Demand Velocity High

26 Demand Velocity Designing Tailored Supply Chain Networks Demand Characteristics Drive Inventory Deployment 80 Item-Locs(H's): 0.91, 0.5% COGS: $(M's) 120.1, 16.5% 80 Item-Locs(H's): 0.29, 0.2% COGS: $(M's) 31.2, 4.3% 80 Candidates for Full Stocking or Direct Ship Item-Locs(H's): 0.74, 0.4% COGS: $(M's) 99.6, 13.6% Fast: >1,000/Week Item-Locations 194 1% COGS $250,900,000 34% BEAUTY HOME CARE NUTRITION PERSONAL CARE BEAUTY HOME CARE NUTRITION PERSONAL CARE BEAUTY HOME CARE NUTRITION PERSONAL CARE Item-Locs(H's): 11.63, 6.7% COGS: $(M's) 159.9, 21.9% Item-Locs(H's): 9.22, 5.3% COGS: $(M's) 120.1, 16.5% Item-Locs(H's): 13.1, 7.5% COGS: $(M's) 148, 20.3% Medium: > 25 Units and <1,000/Week Item-Locations 3,395 20% COGS $428,000,000 59% BEAUTY HOME CARE NUTRITION PERSONAL CARE BEAUTY HOME CARE NUTRITION PERSONAL CARE BEAUTY HOME CARE NUTRITION PERSONAL CARE Item-Locs(H's): , 57.7% COGS: $(M's) 22.9, 3.1% Item-Locs(H's): 30.5, 17.5% COGS: $(M's) 18.9, 2.6% Item-Locs(H's): 7.12, 4.1% COGS: $(M's) 9.3, 1.3% Slow: < 25 Units/Week Item-Locations 13,791 79% COGS $51,100,000 7% Candidates for Centralization BEAUTY HOME CARE NUTRITION PERSONAL CARE BEAUTY HOME CARE NUTRITION PERSONAL CARE BEAUTY HOME CARE NUTRITION PERSONAL CARE High: >1.5 Medium: Low: < 0.6 Item-Locations 11,283 65% Item-Locations 4,001 23% Item-Locations 2,096 12% COGS $302,900,000 41% COGS $170,200,000 23% COGS $256,900,000 35% Demand Variability COV (Std Dev Demand / Mean Demand) 26

27 Cross Dock Storage Direct to Store 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 Flow Through 59,619 Total Items Determine Bulk & Direct to Store Articles 56,199 Items Through the Future DCs Determine Stored vs. Not Stored 44,687 Items either Flow Through or Cross Determine Cross Dock vs. Flow Through 16,770 Items Flow Through Determine Flow Through Manual & Automation 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. 27

28 Focus Areas in Supply Chain Network Design Types of Analysis Customer/Channel Segmentation Flow Path Service Level Strategy Service Territory Alignment Inventory Deployment Mode Usage Supply Chain Risk Assessment Master/Tactical Planning Social Responsibility Modeling Technologies Network Optimization Inventory Optimization Simulation Transportation Modeling Total Cost-to-Serve Portfolio Management

29 Reasons US Companies Initiate Network Studies Cost Reduction Clear Leader and Growing 100% 90% 80% 70% Annual Planning Process 3% Process Re-engineering 3% Never Done Thought It Was Time 3% New Product Introductions Assess 3PL Outsourcing 2% Sourcing 2% Increase Service Politcal/Regulatory Change 1% 2% 2% 60% 50% Develop Internal Compentancy 6% New Markets 6% Cost Reduction 41% 40% Excess/Insufficient Capacity 11% Merger, Acquisition, Divestiture 12% 30% New Management 6% 20% 10% 0% 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% Trend Last 10 Years Trend Last 5 Years Source: 184 Chainalytics Employee Project Experiences 29

30 NETWORK COSTS NETWORK COSTS EFFORT EFFORT Periodic vs. Continuous Analysis Approach Keeps Network In Tune, Ability to React Periodic Continuous Typically 24+ Months Initial Study TIME Actual $ Lost Opportunity TIM E Optimal $ Actual $ Optimal $ 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 month gap between major studies Does not completely eliminate spikes in effort, but reduces their 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 and business 30

31 % Make Design Projects Supported by Analytics and Optimization Results Typically Contrary to Conventional Wisdom Company planned to outsource these products. Using Activity Based Costing in the study showed they should maintain or increase amount made in plants. Commodity Wire M/B Filler M/B Pocket Only M/B Sewn Book M/B Company planned to invest significantly in existing Plant 1. Greatest savings came from closing down Plant % 100% 100% 100% 100% % 95% Achievable St Joe Total Costs In Play Targeted St Joe Total Costs In Play 90% 85% 80% 75% 70% 85% 81.8% 73.2% 83.6% 83.4% 83.6% % 60% 55% 50% 62.1% BASELINE Millions $ % 1 Best Use of Existing 61.4% 61.4% 61.4% 2 Optimal Machine Deployment 3a Close Garland 3b Close St Joe $70 $60 $50 $40 $30 Company had always built a significant amount of inventory in non-peak season (Sep-Nov). Studied demonstrated ability to not build during this timeframe. $20 $10 $0 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 31

32 % of SKUs Millions Inventory Projects Supported by Analytics and Optimization Results Typically Contrary to Conventional Wisdom 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. 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%. Inventory Value Inventory Value - SMO $90 $80 $70 17% $60 $50 $ Base 0% 0% 1% 18% 80% $30 $20 8% 17% 11% 2% Strategy 20% 6% 9% 9% 57% 12% Strategy 58% 8% 6% 9% 20% 18% Strategy 69% 7% 5% 4% 14% $10 $- Network Devices Displays Printers & Office Equipment Supplies & Media 10% Security Devices 32

33 COV Daily Demand COV Daily Demand Inventory Deployment Strategy: Consolidation of Locations Increases Product Velocity and Reduces Demand Variability 1800% Product Stocked at All Locations 1600% 1400% 1200% 1000% 800% 600% 400% 200% 0% Mean Days Betw een Ships Product Stocked at Single Location 1800% 1600% 1400% 1200% 1000% 800% 600% 400% 200% 0% Mean Days Betw een Ships 33

34 Inventory Deployment Strategy: Postponement What is postponement? Economical delay of committing materials and product for as long as possible Holding of inventory in a less finished state. Pushing the point of product differentiation closer to the customer Where to hold? What form to hold in? What are the benefits of postponement? Gain agility in supply chain More responsive to market opportunities Offer wider range of customization options Decreased reliance on finished good forecasting in times of economic uncertainty and shorter product lifecycles Economic Benefits Allows companies to take advantage of low labor markets for building standard/component parts while achieving Reductions of 30-40% reductions in inventory(1) Decrease lead times and lead time variability for finished goods Inventory held in less finished state lower carrying costs Increased Revenue - higher fill rates to customer orders Manage constrained capacity more effectively Don t build what you may not need Increased importance as economy recovers

35 Postponement Opportunities High Product Variety High Value Add at End of Chain High Demand Uncertainty Postponement Candidates Customization not Costly Short Product Lifecycles Global Supply Chain

36 Postponement Example Current State Procure Finished Products Including Retail Configurations Consolidate Shipments Forward Deploy Finished Products at DCs Ship To Customers Deconsolidate Shipments

37 Postponement Example Delay Retail Display Configurations in Asia Procure Finished Products Stock Finished Product Flow Thru DCs To Customers Assemble to Order Retail Display Configurations Deconsolidate Shipments

38 Postponement Example Delay Retail Display Configurations in U.S. Assemble to Order Retail Display Configurations Procure Finished Products Consolidate Shipments Forward Deploy Finished Products at DCs Ship To Customers Deconsolidate Shipments

39 Postponement Example Delay Final Assembly of Finished Goods in U.S. Assemble to Order Finished Products and Retail Configurations Procure Components Consolidate Shipments Ship Components to Plants Ship To Customers Deconsolidate Shipments

40 IV Orchestrating III Collaborating II Anticipating S&OP Analytical Enablers Roadmap Continue S&OP Maturity Journey AS is Assessments Maturity Models BIC Practices Metrics Performance Integrate with Financial Planning Invite Finance to table Synchronize financial and operational plans Consensus plan Budget impact Establish Product Portfolio Management Create Total Cost-to- Serve Models Supply Chain Cost Sales/Mkt/Admin Cost Commercial Items Profit Focused Strategic Time Frame Cross-Functional Team Product Lifecycle Plan Establish Customer Segmentation Overtly Inject Risk into Planning Enterprise-wide Risk Management Framework Uncertainty & Complexity Templates & Tactics Design/Execute Tailored Supply Chain Networks Supply Chain Design Network, Inventory, and Transportation Opt On-going analysis Profit Focused Strategic/Tactical Time Frame Cross-Functional Team Policy/Customer Service Adjustments Incorporate Scenario Planning Predictive Analytics using Probabilistic Methods Risk Response Plans

41 Questions & Answers