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SAP CVN Demand Planning Session - Forecasting Model Selection

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Plan4Demand's SAP CVN Supply Chain Management Summit Demand Planning Breakout Session Chicago 6-19-12

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SAP CVN Demand Planning Session - Forecasting Model Selection

  1. 1. © Plan4Demand Solutions, Inc. 2012 SAP CVN SUPPLY CHAIN MANAGEMENT SUMMIT APO Demand Planning Session June 19th, 2012 Welcome!
  2. 2. © Plan4Demand Solutions, Inc. 2012  Introduction to Plan4Demand  Demand Planning Business Challenges  Tools & Accelerators for Optimization  Q&A
  3. 3. © Plan4Demand Solutions, Inc. 2012 3Supply Chain Planning Consulting Firm specializing in:• Sales and Operations Planning(S&OP)•Demand Sensing/Planning/Forecasting•Supply Replenishment Planning•Enterprise Inventory Optimization•Production Planning/Finite Scheduling•Supply Chain Response Management•Change Management/ End User Adoption &SustainabilityServices:•SAP SCM Optimization to Maximize Benefit of Investment•Package Fit Validation/Selection Services•Operational Strategy and Road Mapping•Business Case Development and Prioritization•Assessments/Blueprinting•Process and Technology Implementation•Customized End User Training and Education Selected as “Pros-to-Know” for the past 4 years in a rowWhy Partner with Plan4Demand? Named to Supply & Demand Chain Executive’s Top 100 List•Experts in Supply Chain Process SAP and Technology•Strong References We Celebrate•Deep Resources: Minimum 10+ years Supply Chain Process and Technology Experience Business Results•Business Case Development to Support Investment in SAP 3•Rapid, High Value Optimization Techniques Not “Go-lives”•Proven Change Management for User Community
  4. 4. © Plan4Demand Solutions, Inc. 2012  Cluttered Process  Planning Book / Data Views spanning multiple demand planning processes  Not reviewing and resolving generated alerts because too many to manage  Statistical Forecasting Not Being Optimized  Client Example  Perception of APO being High Maintenance  Design Considerations
  5. 5. © Plan4Demand Solutions, Inc. 2012  How to Unclutter the Process?  Build Data Views which Align to DP Processes  Pointed Data View for key DP Processes  History Management  Statistical Forecast Management  Final Consensus forecast Management
  6. 6. © Plan4Demand Solutions, Inc. 2012  How to Unclutter the Process?  Exception Based Management  Too many business rules generating too many alerts.  Alerts set too ridged for the process’s maturity stage  Lack of education on using alert monitoring and alert profiles to better manage exceptions (e.g. Using thresholds for forecast alerts)
  7. 7. © Plan4Demand Solutions, Inc. 2012  Cluttered Process  Statistical Forecasting Not Being Optimized  Client Examples  Perception of APO being High Maintenance  Design Considerations
  8. 8. © Plan4Demand Solutions, Inc. 2012  Statistical Forecasting Not Being Holistically Optimized  Typicaldemand planner skill is solid from business/product knowledge but lacks statistical forecasting skills  Implementers create a standard set of forecast profiles, trend dampening profiles, etc. but no post go-live checkpoints to assess if the standard approach is working  Demand planners not comfortable using statistical forecasting process available in APO. Let’s take a deeper dive into the statistical forecasting pain points and how to be comfortable using the tool... First, are you familiar with the models available in APO?
  9. 9. © Plan4Demand Solutions, Inc. 2012 9  Statistical Models / Techniques to select:  5 – Constant  Copy History  4 – Trend  Manual Forecasting  Linear Regression  2 – Seasonal  Season + Linear Regression  2 – Seasonal trend  Median Method   6 – Automatic model selection 1  Croston’s Method  1 – Automatic model selection 2  External Forecast / No Forecast Model(s) are assigned to Profiles Profiles Assigned to SSelections
  10. 10. © Plan4Demand Solutions, Inc. 2012 • Based on discussions with business areas and analysis conducted in current environment defined client as having components of “Aware” and “Functional” • Largest area of opportunity was statistical forecasting and exception based management both available in APO
  11. 11. © Plan4Demand Solutions, Inc. 2012  Forecast Review / Buy-In Approach  Worked with demand team to define representative set of products and customers to use for deriving proposed modeling approach for POS and Shipment demand  Reviewed historical demand patterns in APO DP to get a sense on which statistical forecast models / strategies to use  Reviewed statistical forecast results and conducted further model parameter tuning to get a reasonable result but not bias the forecast  Compared APO generated statistical forecast to Final POS Forecast (what is supplied by the client demand team)  Documented and shared findings with team by conducting several working sessions  Developed a Roadmap for Forecast Optimization
  12. 12. © Plan4Demand Solutions, Inc. 2012 12 Understand History • Completeness and accuracy of data available • Group products based on similar demand patterns • This leads you to a Forecasting Pick Forecast Strategy Model Type within Model Type (e.g. Seasonal Models) • Profiles aligned to Forecast Strategy • Constant Models • Seasonal Models • Trend Models • Seasonal Trend Models • Holt-Winter’s (Strategies 40 &41) • Seasonal Linear Regression (45) Build Selections ID • Models attached to Profiles of products based on Model Type  When fitting models to data, it is often useful to analyze how well the model fits the data and how well the fitting meets the assumptions of the business
  13. 13. © Plan4Demand Solutions, Inc. 2012 Suspect Data?  Walk Through Session (Example – Weekly POS)  Using a Seasonal + Linear Regression model and you can see the fit is reasonable with a MAPE of 23% and a MPE of -7%  Note the graph indicates a reasonable fit but there may be some suspect outliers (Aside: After incorporating outlier correction MAPE went / improved by 10 ppt.)
  14. 14. © Plan4Demand Solutions, Inc. 2012 Q3 - 2012 Q4 - 2012 Q1 - 2013 Est. # WorkDays Phase 2 JUN JUL AUG SEP OCT NOV Client Client P4DDP Roadmap Items Description 28 4 11 18 25 2 9 16 23 30 6 13 20 27 3 10 17 24 1 8 15 22 29 5 12 19 IT Resource DP Resource Resource Make Copy of APO_DP1 Planning Area in QA IT 3 0 0 Add Fiscal Month to Storage Bucket Prfl 5 0 3 Fcst Key Figures: Prop. Factors for Time Disagg Bi-Weekly Conference Call Touchpoint 1 0 1 Conduct Incorporate use of Proportional Factors 0 1 3Conference Room ~ 3 Wks Macros: Unconsumed Demand & Proj. Inv. 0 1 5 Pilot Consumption Data View Update 0 1 1 Define Promote to Production Strategy 1 0 1 Define Process for Populating Store Counts 1 1 1 Confirm Business Blueprint 0 1 1Develop Business Define Business Scenarios to be Tested 0 3 4 Scenarios 2 Wks Prepare detailed project plan 0 0 2 Map POS History to Loc 8255 3 0 1 APO DP Structure Promote Prototype to Production 2 Wks 4 0 2 Store Counts for H&G populated in APO DP 3 1 1 Statistical Statistical Forecasting / Outlier Correction 0 5 5 Forecasting Stat. Forecast Alerts / Exception Based Mgmt ~ 3 Wks 0 3 3Training / Working Determine if macro alerts sufficient; Create new? 0 2 4 Sessions Lifecyle Management (e.g. New / Disc Items) 0 2 3 Incorporate Capturing Promotional & Other Adj. 1 3 3 Promotional Using Promotion Planning Functionality 2 Wks 0 2 4 Adjustments Use of Promotional Attribute Types 0 2 3 Note: Bi-Weekly Conference Calls will be for 1 hour with demand team  The activities in the roadmap are cumulative in nature – they build upon each other  Fills the gaps identified in Phase I Assessment and Opportunities  Different from our original Phase II Plan (inclusion of Conference Room Pilot) in order to:  Maintain change management momentum  Recognizes Demand Planning calendars  Should aid in preparing IT and other divisions – road show approach
  15. 15. © Plan4Demand Solutions, Inc. 2012  Cluttered Process  Statistical Forecasting Not Being Optimized  Perception of APO being High Maintenance  Design Considerations
  16. 16. © Plan4Demand Solutions, Inc. 2012  Build a Prototype and get the business engaged immediately…don’t wait until a task on a project plan  Align Data Views and Key Figures to Demand Processes (e.g. Clean History / Develop Statistical Forecast / Promotion Planning / Review Final Forecast)  Create Macro Alerts (i.e. business rules) that result in a manageable amount of exceptions  Focus on Critical Training like statistical forecast and CVC realignment
  17. 17. © Plan4Demand Solutions, Inc. 2012 17 For More Information… www.Plan4Demand.com Contact Join our Demand Planning  Lisa Kustra, CEO Leadership Exchange lisa.kustra@plan4demand.com on LinkedIn O: 412.733.5050 to continue the discussion and for more C: 412.996.7090 learning opportunities!  Jaime Reints jaime.reints@plan4demand.com O: 412.733.5011

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