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Demand planning session

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Demand planning session

  1. 1. Demand Planning/Supply Chain 101 Microsoft Partner Summit, Phoenix, AZ February 12, 2013
  2. 2. Agenda • Introduction • Definition of Demand Planning • Why Demand Planning • Demand Forecasting • Inventory Planning • Replenishment Planning • Summary of Benefits from integrated Demand Planning • Q&A  2013 JustEnough Software 2
  3. 3. Introduction  2013 JustEnough Software 3
  4. 4. Introduction • Jeff Livingston – Director, Partner Development  15+ years Supply Chain Planning Industry Experience  Supply Chain Planning experience across SMB and Tier 1 businesses with domain expertise in Demand Planning, Inventory Optimization, Replenishment/Supply Planning and S&OP.  Experience with Logility, Oracle/Demantra, JustEnough and other applications.  B.S. Mathematics – Purdue University, MBA California Polytechnic  2013 JustEnough Software 4
  5. 5. What is “Demand Planning” • Demand planning is a multi-step operational supply chain planning process used to create reliable forecasts of customer demand and align inventory levels and supply plans to achieve the targeted level of customer service desired by a business. • In Short: “ Having the Right Product, at the Right Place, at the Right Time and at the Right Price, to satisfy customer demand.”  2013 JustEnough Software 5
  6. 6. Realities of the New Business Environment Companies encounter continuous change and require the ability to rapidly adapt in a fast changing business environment © 2013 JustEnough Software 6
  7. 7. We Live in Turbulent Times Things beyond your control can have a major impact on your supply chain. © 2013 JustEnough Software 7
  8. 8. Traditional Planning Systems Don’t Work Anymore • Traditional tools (spreadsheets and disconnected, fragmented systems) can not respond quickly enough to the rapid pace of change:  Global Sourcing  Longer lead-times  Increased Demand Volatility  Faster Product Lifecycles  More choices & new competitors  Fewer Resources, People, Capacity…doing more with less. Greater Demand + Longer + Variability Lead-Times More Full Container Shipments = Increased Inventory Risk © 2013 JustEnough Software 8
  9. 9. Traditional Approach = Disconnected Slow Processes, limited collaboration, no consensus forecasting Typical Company Finance Budget Manual processes Sales Forecasts/Quotas Marketing New Products E-mail overload Inventory Planning Manufacturing Capacity/Scheduling Multiple, non-integrated systems Low forecast accuracy Departmental/Silo orientation to Supply Chain Planning Misalignment between metrics and objectives Reactive vs. Proactive/Exception based Multiple versions of “The Truth” © 2013 JustEnough Software 9
  10. 10. A Better Approach = Integrated Sales Forecasting, Inventory Planning and Replenishment Planning Integrated Supply Chain Planning – Driving the business via ONE PLAN: Demand Forecasting • • • • • • Statistical Forecasting Market Intelligence Seasonality Lost Sales Supersessions Promotion Planning Merchandise Financial Planning Inventory Planning Order Planning & • Strategic Inventory Replenishment • • • Management ABC Stratification Scenario Analysis Time-phased Optimization • • • • Recommended PO’s, WO’s and Transfer Orders Constrained Orders Alerts/Exceptions (Potential Stock Outs, Excess, Defers, Cancels, Expedites, etc.) Opportunity Buying © 2013 JustEnough Software 10
  11. 11. Better Approach = Significant Benefits (Supply Chain Champs) • Demand-Driven Supply Chain Planning Leaders Have:  15% Less Inventory  17% Better Order Performance  35% Shorter Cash-to-Cash Cycle times • Which Translates To:  60% Better Profit Margins  65% Better EPS  2-3 X ROA Source:  1/10 the Stock outs of their peers © 2013 JustEnough Software 11
  12. 12. Better Approach - People, Plans & Objectives Aligned © 2013 JustEnough Software 12
  13. 13. Demand Planning Core Components Integrated Forecasting, Inventory Planning and Replenishment Planning A holistic planning system that is also linked/integrated to the ERP backbone execution system (i.e. MS Dynamics) MS Dynamics ERP Events, Promotions & Market Intelligence Sales History Demand Forecasting Forecasts, and Statistical Standard Deviation On Hand balance Open Orders MOQ, Multiples, etc. Inventory Planning Time-phased Inventory Policies & Strategy, ABC Stratification, Order Constraints, Lead times, etc. Time-Phased Inventory Plan Recommended Orders: Purchase Orders, Work Orders & Transfer Orders Replenishment Planning Exceptions: Potential Stock outs, Excess, Defers, Cancels, Expedites, etc. © 2013 JustEnough Software 13
  14. 14. Do You Have an Accurate Picture of Customer Demand? © 2013 JustEnough Software 14
  15. 15. Demand Forecasting Demand Forecasting “Best Practice” process approach There are four generally applied and recognized forecasting methods that when combined help generate an accurate demand plan: Future statistical Time Series Forecasting Generating forecasts based on pre-defined profiles and continuously maintaining those profiles based on performance Experimental Forecasting Total Demand Forecast Judgment and Collaborative Forecasting projections/extrapolations based on historical data patterns and trends Causal Forecasting Predict and incorporate the effect of particular events, promotions, and other factors Seeking extrinsic knowledge from internal or market sources and coming to a forecast consensus © 2013 JustEnough Software 15
  16. 16. Demand Forecasting Time Series/Statistical Forecasting • The Process Starts with a Statistical Forecast as a baseline forecast  Premise – Historical customer demand patterns are the best indicator of future demand patterns.  Requires import/integration of Historical Sales Demand from ERP/Transaction system as foundation data (Typically 2 to 3 years of prior monthly/weekly demand) • Statistical Forecast Engine analyzes demand history/patterns  Evaluates multiple forecast methods/algorithms to determine “best-fit” or most statistically accurate method/model.  Determines appropriate level of expected sales, projected growth/decline trends and seasonal patterns.  Statistical Mean Square Error or Standard Deviation used to select best-fit model (Standard Deviation can be used as input to “Statistical Safety Stock” calculation in Inventory Planning) © 2013 JustEnough Software 16
  17. 17. Demand Forecasting Statistical Forecasting and selecting best statistical method Typical Types of Statistical Methods/Models applied: Constant Trend Seasonal Sporadic Straight/flat line Linear or non-linear growth projection Repetition at fixed intervals Random pattern © 2013 JustEnough Software 17
  18. 18. Demand Forecasting Statistical Forecasting and selecting best statistical method Typical Types of Statistical Methods/Models applied: © 2013 JustEnough Software 18
  19. 19. Demand Forecasting Add Market Intelligence and Demand Shaping activities • The Process Continues – Improve the forecast with market intelligence inputs & forecast overrides • Demand Shaping for Profitability:  Plan promotions, events & incentives  Plan new product introductions  Identify cross-selling opportunities © 2013 JustEnough Software 19
  20. 20. Demand Forecasting Group/Hierarchical & Attribute Forecasting • Forecasts are often required or better managed at multiple levels of detail/aggregation:  Top-Down - Forecast by Product Family/Groups Fair-share disaggregation to SKU Leverage “Law of Large Numbers” Product Family Strategy/Budget focused Greater visibility to Seasonality or Trends Item  Bottoms-up - Sum SKU history/forecasts to family/groups Operationally/customer focused Item-Location  Middle –Out - Blended Method © 2013 JustEnough Software 20
  21. 21. Demand Forecasting Forecasting New Products Need to polish-up your Crystal Ball? © 2013 JustEnough Software 21
  22. 22. Demand Forecasting New Product Forecasting • Forecasting New Items – Approaches to forecasting items that have no prior demand history?  Manual Forecast (Judgment)  Like-Item Forecasting - Supersessions/Chaining - Copy/Merge similar product  Profile/Curve Shaping - Life Cycle Profiling - Attribute based Profiling - Seasonality “Group Profiling” © 2013 JustEnough Software 22
  23. 23. Demand Forecasting Measure/Monitor Forecast Accuracy • Measure and monitor forecast accuracy for continuous improvement:  Typical forecast accuracy measurements include: - MAD (Mean Absolute Deviation) – Used for inventory calculations MAPE (Mean Absolute Percent Error) – Common Forecast Accuracy metric Relative Error – Relative measure of error for diagnostic purposes – exceptions  Measure Accuracy of Multiple Inputs: - Accuracy of Statistical Forecast Accuracy of Overrides & Market Intelligence inputs (Did inputs help/hurt the forecast accuracy?) © 2013 JustEnough Software 23
  24. 24. Demand Forecasting Collaboration and Consensus Forecasting Consensus forecast process results in best single number to drive downstream planning process Statistical Baseline Forecast Input from Sales, Marketing and Finance Input Events, Promo’s and Incentives Customer & Competitor Information New Products Consensus Forecast © 2013 JustEnough Software 24
  25. 25. Demand Forecasting Gain Competitive Advantage via Better Forecasting • Improved forecast accuracy hits the bottom line: 5% Forecast Accuracy Improvement 10% Perfect Order Fulfillment $0.50 Greater EPS  Costs go down & earnings go up: - 17% stronger perfect order fulfillment 15% less inventory 35% shorter cash-to-cash cycle times 1/10 of the stock outs of their peers © 2013 JustEnough Software 25
  26. 26. Inventory Planning Balancing Inventory Investment with Desired Service Level Inventory Planning – Optimizing inventory investment. © 2013 JustEnough Software 26
  27. 27. Inventory Planning Why Do Businesses Carry Inventory/Safety Stock? • Economic Reasons - Lot Sizes/Ordering Costs - Minimum Order Quantities • Transportation Inventory - Pipeline fill • Special Events - Promotions/Incentives, etc. • Fluctuation Inventory – Due to Uncertainty (Safety Stock) - Uncertainty of Demand (Forecast Error) - Uncertainty of Supply (Supplier Delivery variability) © 2013 JustEnough Software 27
  28. 28. Inventory Planning The Inventory/Service Level “Exponential Relationship” Safety Stock Quantity Safety Stock Inventory Increases dramatically as Service Levels approach 100% 80 85 90 95 100 Service Level % © 2013 JustEnough Software 28
  29. 29. Inventory Planning Forecast Accuracy & Safety Stocks Forecast Error has a direct relationship with Safety Stocks: Small Standard Deviation Item A Low Standard Deviation Item requires less Safety Stock Carrying too much Safety Stock would be costly!!! Item A Big Standard Deviation Item B Higher Standard Deviation item requires more safety stock Item B Having too little Safety Stock increases the risk of stock outs!!  2013 JustEnough Software Confidential 29
  30. 30. Inventory Planning Not All Items are the Same • Inventory Stratification – Pareto Principle – ABC Classifications  ABC stratification can be used to set strategic inventory policies  Focus investment attention on “A” items  Apply Uniform Rules to Like Items  Reduce Decision Time © 2013 JustEnough Software 30
  31. 31. Inventory Planning Safety Stock Policy Setting • Common techniques/policies for setting safety stocks and inventory objectives:  Fixed Safety Stock Levels  Periods of Supply ( 2 weeks of Supply)  Statistical Safety Stock Policy - Target Service Level (i.e. 98% Service Level) - Accounts for Variability of Supply/Demand - Accounts for Lead-time and Order Quantities  Policies can be dynamic for optimization over time/season. © 2013 JustEnough Software 31
  32. 32. Inventory Planning Time-Phased Supply Chain Network Planning • Modeling the Distribution Network – Nodes, Sources and Lead Times: Manufacturing/Vendors East Region USA DC West Region USA DC Midwest USA DC Canadian DC Customers/Consumers © 2013 JustEnough Software 32
  33. 33. Inventory Planning Planning for the Entire Supply Chain Network An optimal replenishment plan – demand-driven pull planning Manufacturing/Vendors Dependent Demand Dependent Demand East Region USA DC Dependent Demand Midwest USA DC West Region USA DC Optimal replenishment policy considers all network dependencies – dependent and independent demand Dependent Demand Canadian DC Independent Demand Customers/Consumers © 2013 JustEnough Software 33
  34. 34. Replenishment Planning Time-Phased Supply Chain Network Planning Traditional Re-order Point (ROP systems) trigger orders when stock falls below a defined level Re-Order Point Logic DRP Planning Logic Reactive process – orders are initiated based on inventory level only Assumes inventories in supply chain network are independent Orders are needed NOW – not forward looking based on the true need date Static ordering settings (i.e. min & Max levels) Promotes PUSH planning © 2013 JustEnough Software 34
  35. 35. Replenishment Planning Time-Phased Supply Chain Network Planning An optimal replenishment plan proactively proposes orders over a future horizon based on planned inventory projections Re-Order Point Logic DRP Planning Logic Reactive process – orders are initiated based on inventory level only Proactive process - orders are recommended based on projected inventory position Assumes inventories in supply chain network are independent Orders are Time-Phased over a defined future horizon – based on future need date(s) Orders are needed NOW – not forward looking based on the true need date Dynamic Ordering Policies Static ordering settings (i.e. min & Max levels) Holistic plan for all supply chain network dependencies – dependent demand Promotes PUSH planning Promotes PULL Planning © 2013 JustEnough Software 35
  36. 36. Replenishment Planning How Much to Re-Order and When? The Saw-Tooth Diagram: Orders Recommended (at lead-time) to be received into inventory on the day that you “plan” to dip into Safety Stock. Units Replenishment Plan Orders suggested in lead-time advance OQ Rate of Inventory Depletion As demand occurs, on-hand decreases OQ = 100 Order Date = Sept. 1 CS SS Due Date = Dec. 14 The Saw-Tooth Diagram Order Received In Potential risk for stock out Time © 2013 JustEnough Software 36
  37. 37. Replenishment Planning Output = Recommended Orders + Bonus Prize • The Replenishment Planning “Optimal Order Generation” Engine generates a stream of Recommended Orders into the future:  Purchase Orders  Manufacturing Orders  Transfer Orders  Re-distribution Orders • Plus a Bonus Prize = Actionable Exception/Alert conditions:  Stock Outs/Excess Inventory  Potential Stock Outs/Shortfalls  Surplus/Defer/Cancel Orders  Expedite Orders © 2013 JustEnough Software 37
  38. 38. Replenishment Planning 101 Closed-Loop Planning – Release Orders to ERP Integration of the “Demand Planning” Recommendations with the ERP system for Execution (Closed Loop Planning) MS Dynamics ERP Recommended PO’s, WO’s and Transfer Orders Real/Actual PO’s, WO’s and Transfer Orders Demand Planning © 2013 JustEnough Software 38
  39. 39. Replenishment Planning Inventory Optimization and Process Maturity • Optimizing Inventory across the Supply Chain Network:  Strategically defining where inventory should be kept in the network  Setting specific stocking/ordering policies by item, location, etc.  Advanced Inventory Optimization practices - Postponement – A strategy used to eliminate excess Finished Goods Inventory , by delaying the final activities (assembly, production, packaging, tagging, etc.) until the latest possible time. - Risk Pooling - Risk pooling suggests that demand variability is reduced by aggregating demand across multiple locations, This reduction in variability allows a decrease in safety stock and therefore reduces average inventory. © 2013 JustEnough Software 39
  40. 40. Replenishment Planning Inventory Optimization and Process Maturity • Optimizing Inventory across the Supply Chain Network – what companies are really doing (level of process maturity): © 2013 JustEnough Software 40
  41. 41. Demand Planning Summary Recent Trends • DDSN – Demand Driven Supply Networks  Demand-driven supply networks are driven from the front by customer demand vs. push planning (build it and they will come).  Partners in a supply chain will work more closely to shape market demand by sharing and collaborating information – goal is to bring the supply chain eco-system into balance. • Demand Sensing Closer to the Point of Consumption  Leverage POS Data…better picture of true market demand  Technological Advances (Big Data) enabling use of retail/store data • S&OP, Demand Shaping, and Business Intelligence/Analytics  Make better and more profitable business decisions, more quickly. © 2013 JustEnough Software 41
  42. 42. Demand Planning Summary Competitive Advantage in a Fast Changing World • Improve forecast accuracy • Sense demand changes and respond more quickly • Optimize inventory across the full supply chain • Improve customer service while reducing costs • Increase visibility for better/faster decision making • Increase efficiency/productivity via exception/alert-based workflow • Bottom-line impact/results © 2013 JustEnough Software 42
  43. 43. Demand Planning Summary Makes running a business a little bit easier… © 2013 JustEnough Software 43

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