Sense, Shape and Respond to Demand

2. Sense, Shape and Respond to Demand John Bermudez Senor Director, SCM Product Strategy

3. The following is intended to outline our general product direction. It is intended for information purposes only, and may not be incorporated into any contract. It is not a commitment to deliver any material, code, or functionality, and should not be relied upon in making purchasing decisions.The development, release, and timing of any features or functionality described for Oracle’s products remains at the sole discretion of Oracle.

4. Demantra Demand Management Enables real time demand sensing and shaping … • Sense demand real-time • Improve forecast accuracy • Shape demand for profitability • Evolve to real-time sales and operations planning

5. Improve Forecast Accuracy Designed for planners, not programmers (“PhD in a box”) • Engine supports all statistical models - Complexity is hidden for casual users but can be fine-tuned by statisticians • Self-tuning engine • Better than best-fit model with unlimited causal factors • Use key accuracy metrics • MPE, MAPE, WMAPE (Weighted MAPE) Self-Tuning Forecasting Engine PhD in a box: advanced statistical models Built-in key accuracy metrics

6. Promotion Events Seasonality Causal Analysis Trend Cyclical Patterns Outlier Detection Improve Forecast Accuracy Leverage Advanced Forecasting and Demand Modeling option Historical data Bayesian Estimator • Mixed models used in same time series adjust for multiple causal factors including seasonality, market trends, and promotions • Each model contributes different forecast characteristic to the overall model • Automatic model selection provides improved accuracy of “best fit” approaches • One forecast based on multiple models instead of only using best-fit model • Self-tuning engine • Forecast trees automatically find level with statistically relevant data • Forecasts stored at lowest level • Proportion rules applied when necessary • Can incorporate external information such as weather, market drivers, forward indicators, and competitive data Multiple causal factors Bayesian Optimizer Forecast Combined model

7. Model 2 Model 4 Model 11 Model 2 Automatic Short/Long Term Forecast Accuracy Mixed models automatically adapt in single, precise forecast

8. MPE - Forecast Bias Improve Forecast Accuracy Built-in accuracy metrics MAPE – Mean Absolute Percent Error WMAPE – Weighted MAPE by revenue, cost, and so on

9. The Difference is in the Details Granular causal factors and coefficients Product/Group • Demand history and causal factors maintained at lowest level • Coefficients calculated and maintained at the lowest level for which there is demand history • Forecasts and promotion predictions reflect local, regional, product group customer, time period, sensitivity, and so on • Demantra approach yields most granular analysis of demand for more accurate forecasts Item Item Item Item at a Customer Item at a Customer/Ship-to A Demand history Promotion Lift Seasonality Cannibalization Other Causal Factors Item at a Customer/Ship-to B Demand history Promotion Lift Seasonality Cannibalization Other Causal Factors Per time period (week/day/month)

10. Demantra Demand Management Enables real time demand sensing and shaping … • Sense demand real-time • Improve forecast accuracy • Shape demand for profitability • Evolve to real-time sales and operations planning

11. Chaining Shape Modeling Attribute-Based Forecasting Shape Demand for Profitability Accurately forecast demand for new products based on existing data • New products present forecasting challenges • Limited or no demand history for a given item • May combine characteristics of several previous products • Price points, changing market conditions may be different • Product demand changes over product life cycle • Apply shapes, scaled for volume and time • Re-scale base on initial demand data Model new item based on past behavior of other items with similar attributes New Product C = 30% Product A + 75% Product B

12. Shape Demand for Profitability Accurately forecast demand for new products based on existing data View demand of comparable products based on characteristics Automatically detect outliers Derive forecast for new product and adjust forecast based on actual demand

13. Past Future Shape Demand for Profitability Leverage Advanced Forecasting and Modeling to understand the real impact of promotions and sales incentives • What incremental volume will result from a marketing program? • How will it impact the sales of other products? • How does a marketing program at a brand or product family level impact a specific item? • What were the indirect effects such as cannibalization and consumer stockpiling? • What is the ROI on my marketing and trade spending? • What is the predicted impact of future activity? • How does a promotion impact shipments and DC replenishments?

14. Shape Demand for Profitability Leverage Advanced Forecasting and Modeling to understand the real impact of promotions and sales incentives Typical Demantra AFDM • Baseline versus incremental volume • Provides decomposition of incremental volume from advertising, promotions, or sales incentives • Granular lift analytics • Incremental volume lift coefficients maintained at lowest level • Localized promotion analysis • Allows shipments/replenishments to be adjusted by ship-to location • Cross product and customer effects • Determines cross-product cannibalization impact • Adjusts forecasts for product and customer cannibalization • Configure system for assumption based forecasting • Structured tracking and categorization of forecast adjustment reasons, such as market and geopolitical changes • Evaluation of impact on demand as driver for future forecasts • Examples • Semicon: forecast based on chip design wins • High-Tech: forecast based on probability of winning an opportunity • Life Sciences: long-term forecast based on drug approval and patent regulations Cross product cannibalization Pre and Post promotion effect Incremental Long term growth Competitive switching Baseline Baseline

15. Demantra Demand Management Enables real time demand sensing and shaping … • Sensedemand real-time • Improve forecast accuracy • Shape demand for profitability • Evolve to real-time sales and operations planning

16. Sales Supply Chain Customers Finance Suppliers Marketing Evolve to Real-Time S&OP Profitably balance supply, demand, and budgets Develop predictable business plans Shape demand to meet financial goals Align supply chain to support plan Monitor performance to plan Shape demand to close gaps Drive decisions into ERP

17. Evolve to Real-Time S&OP Profitably balance supply, demand, and budgets • Seeded templates for S&OP collaboration • Seeded consensus planning worksheets • Easily tailored to your business • Configurable and extensible • Collaborate at any level • Manage by exception instantly • Exceptions and visual cues easily point to important issues immediately • Document all assumptions with a complete audit trail of decisions taken • Leverage POS data to alert planners to exceptions real time (versus batch month by month) • Integrated • Seeded data streams for data commonly used in the process

18. Evolve to Real-Time S&OP Highly interactive simulation and analysis • Continuous real-time process • Simulate demand and supply strategies • Analyze multiple business scenarios • Achieve consensus on plans through internal collaboration • Generate and analyze exceptions • Use workflow to automate process • Adaptable • Custom demand and supply streams • Multi-dimensional • Extensible hierarchies and dimensions • User-defined reports and exceptions

19. Evolve to Real-Time S&OP Inputs display from entire collaboration group – Finance, Marketing, Operations, Key Customers and Suppliers Each S&OP participant has a configurable role-based view Integrated approval workflow process Review historical accuracy for each input

20. Achieve Incremental Value Implement additional Advanced Planning components quickly by leveraging the same foundation • Shipment history • Booking history • Sales forecast • Manufacturing forecast • Items and categories • Organizations • Customers • Calendars • UOM and currency conversions • Price lists • Hierarchies (product family and product category, time, ship from, geography, customer, demand class, sales channel) Advanced Planning E-Business Suite Demand Management Predictive Trade Planning and Optimization Promotional lift and decomposition Real-Time Sales and Operations Planning Range forecast and forecast accuracy Demand scenarios and priority Demand variability and forecast error Demand scenarios Strategic Network Optimization Advanced Supply Chain Planning Inventory Optimization Production Scheduling Collaborative Planning

21. <Insert Picture Here> Customers

22. DeRoyal Industries Live on Demand Management Company • Leading manufacturer of medical devices • Manufactures more than 25,000 SKUs and operating from 25 plants and office around the world$1 billion in revenues, operating worldwide Planning problem solved • Aligned customer demand with supply chain planning Unique aspects of implementation • Integrated with JD Edwards ERP • Supports the companies many new product introductions with improved forecast accuracy • Increased forecast accuracy by 5-10% • Increased customer service levels • Reduced inventory by 8% • Enabled a comprehensive S&OP process

23. Welch’s Live on Demand Management, Trade Management Company • Leading producer of juices and jams Planning problem solved • Promotion planning synchronized with demand planning Unique aspects of implementation • Sales reps drive forecasting process from trade promotion planning process • What-if scenario planning enables sales reps to test promotion before selecting it • Increased forecast accuracy at SKU level • Enables trade promotion planning to be integrated with RT S&OP • Reduced supply chain costs • Improved HQ and sales planning productivity

24. VTech Live on Demand Management, Real-Time S&OP Company • $1 billion in revenues, operating worldwide • Manufacturing plants in China • Leading provider of cordless phones and electronic children’s toys Planning problem solved • Real-time S&OP process driven by one demand number Unique aspects of implementation • Generates forecasts from customer POS data • Compares customer and generated forecasts and routes exceptions to planner, sales representative, or customer • Increased order fill rate from 55% to 95% • Increased inventory turns by 100% • Reduced price protection claims by 40% • Reduced logistics costs by 65%

25. <Insert Picture Here> Summary

26. CHANNEL DATA Oracle Demantra Demand Management Real-time demand sensing and collaborative consensus forecasting • Sense demand real-time • Sense demand more frequently, closer to the point of consumption • Capture demand and forecast at more granular level (store, shelf, attributes, product characteristics) • Achieve consensus demand number more quickly by involving all constituents at the same time, including customers • Quickly identify and react to demand changes and exceptions • Improve forecast accuracy • Leverage advanced statistics for more accurate demand number • Use any combination of quantitative or qualitative data to establish your base line forecast • High precision statistical forecasting, no statistical background required – Superior Bayesian-Markov forecast analytics • Forecast based on attributes and characteristics • Leverage Advanced Forecast Modeling for promotion lift decomposition and causal analysis • Shape demand for profitability • Plan new product introductions • Plan promotions and sales incentives • Identify cross selling opportunities • Evolve to real-time S&OP • Profitably balance supply, demand, and budgets Collaboration Workbench Marketing forecast Order history Customer sales Shipments Demand Hub and Seeded Worksheets

27. Oracle Demantra Demand Management Evolve at your own pace to a best-in-class solution Forecast based on attributes and product characteristics Compute promotional lifts and analyze impact of demand drivers Assumption based forecasting Start anywhere Leverage POS and channel data Forecast new product introductions Collaborate with customers Use advanced statistics and causal factors Complex alerts and custom worksheets Leverage POS and channel data Forecast new product introductions Collaborate with customers Use advanced statistics and causal factors Complex alerts and custom worksheets Manage rolling forecasts Collaborate with all constituents on one number Use basic statistics, alerts, and seeded worksheets Tailor worksheets for individual users Manage rolling forecasts Collaborate with all constituents on one number Use basic statistics, alerts, and seeded worksheets Tailor worksheets for individual users Manage rolling forecasts Collaborate with all constituents on one number Use basic statistics, alerts, and seeded worksheets Tailor worksheets for individual users Eliminate spreadsheets From less complex to best in class

28. Why Oracle ! Proven, scalable demand management solution Integrated demand, supply, and sales and operations planning Designed for planners, not programmers Integrated performance management

29. Q & A Q U E S T I O N S A N S W E R S