Nicki Sommer Principal Sales Consultant NCOAUG, August 15, 2008

Nicki Sommer Principal Sales Consultant NCOAUG, August 15, 2008
Hi, My name is ____ and I’m here to talk to you about some of the exciting new features added to Oracle Advanced Planning for Release 12. What’s new in release 12 manufacturing? Nicki Sommer Principal Sales Consultant NCOAUG, August 15, 2008

Safe Harbor Statement 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. Before we start . . .

Advanced Planning Command Center
Service Parts Planning Demand Signal Repository Let’s start with executive level business scenario planning … Manufacturing Operations Center

Let’s start with executive level business scenario planning …

Today’s Supply Chain Executives’ Agenda
New world: continuously adapting to changing supply chain business model Uncertainty Volatility Risk Consolidation Virtualization Changing Supply Chain Business Model Compliance Globalization Chaos Continuous Innovation Operational Flexibility Risk Management and Compliance CEO’s Agenda Drivers For Success Increased Shareholder Value and Sustainable Growth Supply chain executives today face a tough battle of trying to adhere to the CEO’s agenda of sustainable growth and shareholder value while dealing with an ever changing supply chain business model. The drivers for success are operational flexibility, risk management, and continuous innovation and they can really only achieve this by bringing analytics and optimization together into a common platform, as also described by AMR in one of their recent studies. “What is required is a new type of decision support platform, one that integrates analytics and optimization. 15 years after the birth of Supply Chain Planning (SCP), we are now just starting to see analytics and optimization converge on a common platform” AMR Research Report “How to measure your supply chain today “ 5 5

The Great Information Divide Still Exists
Operational Efficiency Risk management and Compliance How do the supply chain executives get access to actionable information? Continuous Innovation Volatility Compliance Virtualization Uncertainty Chaos Globalization Consolidation Risk Spreadsheets, Reports s, Phone calls Manual Co-ordination Across Functional Groups SNO ASCP DM PS IO DRP So how do executives get access to actionable information? Today, this mostly happens to be a manual exercise – the executive delegates via or phone calls what he needs and in return with a great deal of latency he gets the information in spreadsheets, presentations, and maybe some custom reports, even if the planning information is readily available in the planning applications that they invested in. Key point here is that they do no have time to learn the deep and rich user interfaces that planners use for their day to day operations. In some cases the decide to build a data warehouse with the problem that any drill down into actionable information is not feasible as it is disconnected. So how do we bridge this still existing great information divide between planners and their management chain? Typically, they don’t have access to correlated and aggregate planning data unless it is presented in a comprehensive spreadsheet or on paper Often, the decision is made to design and build a custom data warehouse that has no integration to the source of the data and that is a limited representation of the data Supply chain executives have no time to learn power user interfaces that were developed for purposed planning applications

Oracle Advanced Planning Command Center
BUSINESS INSIGHT Business insight for supply chain executives BUSINESS DRIVERS Scenario, Activity and Process Management Drill downs to details Pre-built, self-service Dashboards Oracle Advanced Planning Command Center provides planning analytics for key decision makers – pre-built self service configurable dashboards. In addition, decision makers can define business scenarios that need to be executed by their planners. When performing their analysis the divide between analytics and planning disappears as seamless transition from analysis to taking actions (planning) is supported. And to make it easier, the product comes with very rich content out-of-the-box so that you can get started immediately. Preconfigured Analytics Model Planning analytics for key decision makers – Pre-built, self service, configurable dashboards Executive level business scenario planning – Planners and executives share accountability No separation between analytics and planning – Seamlessly drill down to lowest level of detail Rich content out-of-the-box – Get started immediately for fast ROI

Oracle Advanced Planning Command Center
Key capabilities Planning Analytics for Supply Chain Decision Makers Pre-Built Dashboards and Reports Get the right answers Self service, pre-built Rich content and KPIs Seamless integration with planning apps Analyze Analytical Data Plans and Archived Plans Business scenario planning Analyze and compare scenarios and plans Decide which scenarios to plan Compare baseline to alternative scenarios Assign scenarios to planners for execution Scenario and Activity Management Plan Execute scenarios Archive plans Preconfigured Planning Processes Oracle Advanced Planning Command Center provides the following key capabilities: Planning analytics for supply chain decision makers Business scenario planning Planning process automation We will talk about these in more detail next. Execute automated processes Planning process automation Notify constituents of assigned activities Link processes for manual or automated execution Auto-archive plans Forecasting Supply Planning Orchestrate Web Service enabled Planning Processes

Business insight for supply chain executives Executive level business scenario planning Planning analytics for supply chain decision makers Planning process management automation Let’s start with executive level business scenario planning …

Role Based Dashboard Process – Executive Review
Executive Review reports Executive Summary Top Diff – Operating Plan and Budget by Category Consensus Change by Customer Consolidated Analysis Profit and Loss Statement Constrained Forecast Comparison Budget Analysis KPI reports: Forecast Accuracy; Customer Service; Inventory and Production Executive Review Consolidated Analysis This trend report consolidates total demand, total supply and resulting inventory levels and is available in both units and reporting currency. Additional measures include inventory turns and days of cover. Total Supply is the sum of all supplies in units. Total Demand is the sum of all demands in units. Projected Available Balance (PAB) is net cumulative supply minus demand in units. PAB Value is PAB multiplied by standard cost. PAB Days of Cover is PAB divided by average daily demand for the item in the plan. Inventory turns is calculated by dividing Annualized COGS by Avg PAB where: Annualized COGS = (item standard cost x sum of independent demand quantity in plan x 365) / number of days in plan Avg PAB = average of beginning value and ending value of each bucket Profit and Loss This report shows Total Revenue, Total Cost, Profit Margin and Margin % for the Baseline scenario. Total Revenue from expected sales is equal to the sum of (Independent demand quantity * (list price - discount)). Total (Supply Chain) Cost is the sum of manufacturing, purchasing, transportation and carrying costs in reporting currency. Profit Margin is the difference between Total Revenue and Total Cost. Margin % is calculated as ((Total Revenue - Total Cost) / Total Revenue) *100. Constrained Forecast Comparison This trend report shows actual sales, stakeholder and constrained forecasts and is available in both units and reporting currency. Navigation reports rank the absolute difference and absolute % difference between the consensus, constrained and budget forecasts for the Baseline scenario only. Cumulative Budget Tracking This trend report compares the cumulative constrained forecast and cumulative budget in reporting currency and supports scenario comparison. The budget shortfall is the difference between cumulative constrained forecast and cumulative budget. Key Performance Indicators (KPI) This KPI report is broken out by Forecast Accuracy, Customer Service and Inventory metrics and measures business performance. Forecast Accuracy This KPI report shows the accuracy of the Consensus Forecast lagged at 4-week, 8-week and 13-week intervals. Absolute Percent Error is calculated by taking the absolute value of the difference between actual sales and the consensus forecast divided by actual sales. Customer Service Perfect Order Index is the fill rate of the end demands measured as a multiple of two factors - percentage of end demands met on time (even partial quantity) and percentage of end demands met in full quantity (even late). It is calculated as (% of independent demands met on time) * (% of independent demands met in-full-quantity). Shipments to Plan is the percentage of actual shipments to planned shipments. It is calculated as (shipment history quantity / Total Independent Demand quantity scheduled to be shipped) * 100. Line Fill rate (count) is the fill rate of the end demands measured as a percentage of number of lines at least partially satisfied on time. It is calculated as (count of independent demands where at least part quantity is met by due date) / (count of all independent demands). Actual backlog represents all sales order booked but not yet fulfilled. Projected backlog is the sum of actual backlog and the difference between the bookings forecast and shipments forecast. Inventory and Production KPI Inventory To Plan is (actual onhand history quantity / planned inventory quantity) * 100 . Inventory Value is PAB Units multiplied by standard cost. Safety Stock is safety quantity in units. Production To Plan is (production history quantity / Total Make order quantity) * 100. Note: The ADS demo will include additional KPI reports in the Executive Review page. These reports include Profit and Loss KPI and Cost Breakdown KPI and have the same design as the three KPI reports that are preseeded. These extra reports are quick to create and illustrate just how easy it is to add additional reports to the S&OP Interactive Dashboard.

Translate Strategy to Actions
Problem ► Cause ► Alternative Solution Evaluation Why do I have this problem? Change product mix What problem do I have? Competitor promotion Launch promotion Sales selling wrong product mix Adjust pricing Sales below target Promote alternate product Pricing issues What actions should I evaluate? Revenue below target Plan overtime Critical part shortage Supply shortages Outsource production Lost production capacity To determine how to deal with metrics that are off from target, you will try to translate problem (what problem do I have) to cause (why do I have this problem) to possible actions that you should evaluate to solve the problem (actions = planning scenarios). Speaker note: talk through example if required. Lost sales due to lack of supply Change inventory levels Hedge supply Analysis Planning

Scenario Management Decide what baseline and alternative scenarios to run to make decisions Supply chain decision makers define business planning scenarios Unlimited number of baseline scenarios Unlimited number of alternative scenarios Assign scenarios and tasks to planners for execution Shared accountability for supply chain planning metrics Planners execute plans using Planner Workbenches Attach key documents Financial analysis External market data and industry reports Assign and monitor scenario activities Personal Activity List Personal Activity List Personal Activity List Advanced Planning Command Center provides robust Scenario Management which enables you to define business planning scenarios for which you can assign tasks (activities) to planners for execution. You can also attach key documents as backup to the scenarios that need to be implemented, such as results of a financial analysis or external market data and industry reports. Execute and assign demand plans to scenarios Execute and assign inventory plans to scenarios Execute and assign supply plans to scenarios Demand Planner Inventory Analyst Supply Planner

Compare Scenarios – Cut across Planning
360 degree visibility to demand, supply, capacity, finance, and exceptions Pre-built self-service dashboards for plan health and S&OP analysis When comparing scenarios to make decisions, it is imperative to have 360 degree access to demand, supply, capacity, finance, and exception information, as provided in the dashboards.

Enable holistic view of supply chain performance and drill down to details Demand from DM Supply from ASCP or SNO Inventory from IO You can look in a single report as consensus demand from Oracle Demantra Demand Management, supply from Advanced Supply Chain Planning, and inventory metrics from Oracle Inventory Optimization. Demantra Demand Management Advanced Supply Chain Planning Inventory Optimization

Enable holistic view of supply chain performance and drill down to details Demand from DM Supply from ASCP or SNO Inventory from IO Drilldown to details And from the high level, you can drill down to the next level and show the details without having to jump into the power user interfaces but with the ability to do so when working with the planners. Demantra Demand Management Demantra Demand Management Advanced Supply Chain Planning Inventory Optimization

Compare Scenarios to Make Decisions
Compare baseline to alternate Compare current to previous Once you have executed these scenarios you can compare them and make the decision by comparing baseline to alternates or current to previous scenarios and plans.

Business insight for supply chain executives Executive level business scenario planning Planning analytics for supply chain decision makers Planning process management automation After we talked about the scenario planning, let’s talk next about the type of analysis that supply chain decision makers can perform with Advanced Planning Command Center

Pre-seeded Rich Content – KPIs
Rich content out-of-the-box:100+ pre-seeded dimensions and perf. metrics As we mentioned earlier, it is key to have rich content when you want to start quickly. Oracle Advanced Planning Command Center ships with rich content out of the box – 100+ pre-seeded dimensions and performance metrics.

Pre-seeded Rich Content – Reports
Rich content out-of-the-box: 100+ pre-seeded reports Adv Planning Command Center also ships more than 100 reports that span Sales and Operations Planning and Supply Chain Planning Analysis across a wide set of important reports and metrics

Business insight for supply chain executives Executive level business scenario planning Planning analytics for supply chain decision makers Planning process management automation The last important part of the Adv Planning Command Center solution is the process management and orchestration layer, which we’ll talk about next.

Planning Process Management Automation
Web service enabled planning processes All key planning processes are web service enabled Collections Forecasting Plan runs Plan name creation Approval and review steps can be modeled and inserted into the process We web service enabled all key planning processes and linked these processes into comprehensive business flows that include approval and review steps.

Automate planning process execution via BPEL The system modeled tasks, along with manual activities that we talked about earlier in the presentation, can be assigned to planners for execution and planners can define the same parameters for running these tasks directly from the scenario management definition. When resubmitting a process, one can decide to skip processes if it is not required to change a particular starting point. Assign owners to top level process notes Optionally skip steps when resubmitting

Automatically archive scenarios plans for historical analysis Archive scenarios directly from Scenario Management, via concurrent program or web service Automatically archives KPIs and facts for plans that are linked to the scenario Archives Demantra Demand facts published to EBS Creates a new scenario version that can be used for comparison in the dashboards Purge scenarios as they become obsolete (will not purge plans shares across multiple scenarios) Archive plans directly from plan runs (optional) or Publish profile (SNO, Demantra) All facts, KPIs, and summaries for the plan are archived in a new plan version Compare plan versions in the dashboards Purge plan versions as they become obsolete ASCP/IO Purge plan: purges all plan versions Plans and Archived Plans Another important feature that is essential for trend analysis is the ability to archive plan performance information and scenarios in a single place. The archive of the plan can be performed automatically when running plans. Archive plans Archive scenarios

Service Parts Planning

Two Different Worlds Centralized Few locations Few products
Why Service requires different approaches and systems MANUFACTURING SERVICE Centralized Few locations Few products Planners manage few parts Shorter lead times Few suppliers Sales forecast Deterministic Build or buy supply Decentralized Many locations Many service parts Planners manage many parts Longer lead times Many suppliers Myriad of demands Probabilistic Move, repair, or new buy Manufacturing and Service Operations operate very differently. Service Parts Planners are typically responsible for a particular group of spare parts or customer region. Often they manage many spare parts as the number of spare parts accumulate over long periods of time when you still provide service even though you’re not selling the products anymore. Service Parts Planners need to figure out replenishment strategies when there’s no demand history and part failure rates. They typically work with specialized parts and repair suppliers and rather than building or buying, they focus on transfers, repair and new buy. Let’s first talk about the current trends in the Service Industry: Service Operations need to be transformed from cost to profit centers Good service translates into proven customer retention, key when new competitive products are being introduced globally more faster than ever before In working with your supply base, it is of essence to have visibility Since you cannot keep every part at 100% service level at every location from a cost perspective, it is also key to determine where to hold which spare parts inventory for example based on a set service level or budget

Service Supply Chain Must manage both forward and reverse material flows Customers Supplier (Repair) Repaired In repair Service technicians Regional DCs Central DC Supplier (New Buy) The service supply chain is all about the reverse material flow. Service technicians and customers return parts. You send parts for repair to suppliers. Suppliers send repaired parts and new buy parts back to you. You send repaired products or spare parts to your customers. On-hand Consigned Repair depot Material flow of good spares Material flow of defective spares

Oracle’s Service Management Solution
Complete and integrated solution Customers Service Execution Service Providers and Suppliers External Contracts Call center CMRO & Depot repair Install base & Engineering Spares Mgt Field scheduling Self-Service Contracts & renewals Parts life cycle & failure rates Repair orders Parts usage Self-Service In-house Oracle provides a comprehensive Service Management solution that covers all aspects of the service chain. From call center management with Siebel service, to service contract management and field service, it is completely covered. Service Parts Planning complements this solution with parts planning that is seamlessly integrated to the Field Service applications. Service supply chain design Spare parts and returns forecast Inventory postponement plan Spare parts replenishment plan Deployment plan Phone Spare parts order promising Messaging (XML/EDI) Replenishment orders Workflow based exceptions Power user Self-Service Service Parts Planning Solution

Oracle Service Parts Planning
Key capabilities Simultaneously forecast, replenish and redistribute your service parts across your service supply chain More accurately forecast your service parts Demantra statistical forecasting engine inside for highest accuracy Account for intermittent, seasonal, and fast moving demand patterns Leverage composite forecasting (shipments, usages, returns) Use service failure rates Optimize the replenishment and redistribution of parts across the extended service network, integrated with Service Execution Integrate with other Advanced Planning products for additional business processes Manage spare parts at customer locations (via CP) Manage service contract customer demand (via Dem DM) Manage targeted service levels and budgets (via IO) Produce parts in manufacturing facilities (via ASCP) Oracle Service Parts Planning offers the following key capabilities …

Oracle Service Parts Planning
Customers Supplier (Repair) Repaired In repair Service technicians Regional DCs Central DC Supplier (New Buy) On-hand Consigned Key to mention is that Service Parts Planning plans everything up and to the field stocking locations/ESLs and that Spares Management complements this by planning the replenishment to the stock trunk of field technicians. Repair depot Spares Management Service Parts Planning Spares Management plans field service engineer trunk stock replenishment Service Parts Planning plans supply network (up-to trunk stock locations) Recognizes usages from field service

Oracle’s Service Parts Planning Solution
Enabling profitable reverse logistics at higher service levels Simultaneously forecast, replenish and redistribute your service parts across your service supply chain More accurately forecast your service parts Optimize the replenishment and redistribution of parts across the extended service network, integrated with Service Execution Integrate with other Advanced Planning products for additional business processes So let’s look at the details next, starting with the simultaneous forecasting, replenishment and redistribution

Simultaneously Forecast, Replenish and Distribute
Single planning process and UI for highest productivity and fastest analysis Items, Failure Rates, Supersession Chain Worksheet Preferences Supply-Demand Forecast Graphs Here’s a screenshot. As you can see, it show both forecast and replenishment info, exceptions, you can add comments, view the supersession chain, and analyze your service chain for a particular or set of organizations, locations, and parts. Comments Exceptions

Enabling profitable reverse logistics at higher service levels Simultaneously forecast, replenish and redistribute your service parts across your service supply chain More accurately forecast your service parts Optimize the replenishment and redistribution of parts across the extended service network, integrated with Service Execution Integrate with other Advanced Planning products for additional business processes Let’s next talk about the powerful forecasting capabilities that Service Parts Planning support…

More Accurately Forecast Service Parts
Demantra Bayesian statistical engine “inside” for highest forecast accuracy Accurately statistically forecast the complex demand patterns found in service parts Key forecast methods specific to service part demand patterns Data transformations for intermittent or sporadic patterns Expert mode: automatically select best blended statistical method for every service part Forecast for service parts without adequate shipment history Forecast based on composite of shipments, usages, returns, failure rates, and product population Forecast for changing replacement parts and revisions Forecast entire supersession chain and chain history of multiple revisions Scale to handle large volumes of parts Selectively re-forecast: use specific forecast methods, parameters, and forecasting frequency as needed based on criticality We embedded Oracle’s Bayesian forecasting engine, similar to how we embedded this in Demantra Demand Management, for Service Parts Forecasting. It is basically a “PHD in Statistics” out-of-the-box that solves the key forecasting problems that service parts planners face … (talk through bullets). Speaker note: customers do not have to buy Demantra Demand Management to get Service Parts Forecasting. They can add Demantra DM for additional forecasting capabilities that are not supported in Service Parts Planning. This also means that you do not get Demantra DM included when buying SPP – you only get the SPP specific statistical engine component.

Intermittent, Seasonal and Fast Moving Demand
Demantra Bayesian statistical engine “inside” for highest forecast accuracy J F M A M J J A S O N D J F M A M J Intermittent demand – Printer Heads Support for key forecasting methods Moving average Single exponential smoothing Holt Integrated causal exponential model (Winters enhanced) Regression with seasonal causal Croston’s for intermittent Regression with seasonal causal for intermittent Multiplicative Monte Carlo regression with seasonal causal for intermittent Optionally, use 100+ advanced parameters for fine tuning Baysian weighted forecasting - blend multiple forecast methods instead of picking one method M A M J J A S O N D J F M A M J J A Seasonal Demand – Air Conditioning Parts The SPP Forecasting engine supports the key forecasting methods that service parts planners use as well as enables planners to use a blended method when they are unable to decide which forecast method to use. The statistical engine hides the complexity from the planners but for those that need tweaking and control, all the parameters can be changed. Forecasting items is basically driven by forecasting rules that can be modeled based on usages, shipments, and returns forecast, as well as product population. Another important problem for parts forecasting that is addressed in Service Parts Planning is the ability to perform composite forecasting especially when no history is available for new service parts or when there is a need to drive the forecast Another important capability that we provide in SPP Forecasting is the ability to calculate forecast based on item supersession chains

Enabling profitable reverse logistics at higher service levels Simultaneously forecast, replenish and redistribute your service parts across your service supply chain More accurately forecast your service parts Optimize the replenishment and redistribution of parts across the extended service network, integrated with Service Execution Integrate with other Advanced Planning products for additional business processes The essence about using all the forecasting capabilities that we just talked about it to have it result in a more accurate forecast that drives you replenishment and redistribution decisions, which we’ll talk about next.

Optimize Replenishment and Redistribution
Operate more profitable Service chain by saving inventory and purchasing costs Consider key service planning constraints Part supersession, condition, and criticality Sourcing of repair-at and buy-from Repair resources (internal) Purchasing, repair, transportation lead times Supplier capacity (for new buy) Minimize inventory and purchasing cost, and out-of-stock impacts Dynamically reallocate and reposition parts Replenish to optimized safety stock levels Use up superseded parts; repair before new buy Out-of-the-box integration with Execution Release recommendations for new buy, repair, and transfers Service Parts Planning calculates the optimal replenishment and redistribution decisions while considering all the key constraints in sourcing, supersession, part criticality and condition, and repair capacity. By dynamically reallocating inventory it enables you to minimize inventory and purchasing cost and out-of-stock impacts. Recommendations can be directly released to Field Service for execution.

Model Key Service Constraints
Accurately model your service supply chain Model how your supply chain changes over time Time phased sourcing rules Include sources such as Transfer From, Repair At, Return To, Make At, and Buy From Use unlimited assignment sets for what-if sourcing scenarios Rebalancing between organizations (circular sourcing) Use different ship methods w/ diff lead times attached to sourcing rule Flexible assignment of sourcing rules minimizes setup maintenance The underlying sourcing model is very flexible and models key sources such as “repair at”, “return to”, ”transfer from”, and so on. In addition, you can define that one warehouses can supply each other, use different ship methods with different lead times. Sourcing rules are date effective, so if they need to change over time, you can model this and the planning engine will take this into account.

Model Key Service Constraints
Part Supersession and Part Condition A key constraint that SPP supports is part supersession and part condition. The planning system will recommend to repair a “bad” part to a “usable” part before recommending new buy as it is less costly.

Minimize Inventory and Purchasing Cost, and Out-of-Stock Impacts
Service-specific business logic Repair before new buy Consider returns supply Use up superseded parts Dynamically reallocate and reposition parts Replenish to optimized safety stock levels This screen illustrates how the planner can analyze the detailed decisions from the engine.

Enabling profitable reverse logistics at higher service levels Simultaneously forecast, replenish and redistribute your service parts across your service supply chain More accurately forecast your service parts Optimize the replenishment and redistribution of parts across the extended service network, integrated with Service Execution Integrate with other Advanced Planning products for additional business processes In the beginning we talked about Service Parts Planning being part of a broader Advanced Planning solution. We’ll cover next what problems the other planning applications help you solve in the Service Management area. These additional capabilities can be deployed at a later point in time or simultaneously with Service Parts Planning.

Enable Additional Business Processes
Leverage additional key capabilities provided by Oracle Advanced Planning Spare Parts Forecast (Highest Rev) COLLABORATIVE PLANNING Manage spare parts at cust. locations Get visibility to new buy supplier capacity DEMANTRA DEMAND MANAGEMENT Advanced forecasting methods Forecast at additional levels (customer, …) Forecast leveraging causal factors Forecast new product introductions New buy supplier capacity SERVICE PARTS PLANNING Spare Parts Forecast (Highest Rev) and Demand Variability (optional) Replenishment and Redistribution Forecasting INVENTORY OPTIMIZATION Verify ability to uptake new SLAs Determine inventory budget required for SLAs Optimally deploy inventory to meet SLAs Analyze inventory policy recommendations Forecast and Demand Variability This diagram shows the integration points between SPP and the other products. Time-phased Safety Stock Levels

Demand Signal Repository

Demand Signal Repository Overview
Business Problem Limited visibility to store/SKU level inventory location and performance data contributes to suboptimal forecasting, allocation and replenishment capabilities Retailers are starting to rely more on category captains and have begun to share daily store level POS and inventory data directly with their CG suppliers Unlocking the value of downstream data is a challenge due to high complexity, variability and volume Solution Overview Oracle Demand Signal Repository (DSR) helps CG manufacturers capture, manage, analyze and ultimately drive value from downstream demand data Oracle DSR leverages OBIEE to provide a powerful BI/reporting platform to analyze the external data, including a set of pre-built dashboards and reports Oracle DSR integrates aggregated demand data with Demantra and offers standards-based integration to other applications via AIA/Oracle SOA Suite Average OOS rate = ~8% (promotions and NPI = ~2x average) ~72% of OOS are caused by store-related issues Average CPG company lost sales due to out of stocks = 2.5% A recent survey of 109 global retailers indicates that suppliers are performing “less than adequately” in key areas: Merchandising & category management Promotional design & execution Customer insight development

Convergence of Retail and Consumer Goods
Mfg. Retailer Traditional View of Relationship CG Mfg Retailer Shared Emerging Relationship Aligned Priorities Jointly managed store/SKU-level merchandise plans Optimized promotion & merchandising decisions Total supply chain logistics & transportation cost reduction Item & price data synchronized to reduce deductions Transportation & Logistics Retail Execution Vendor Managed Inventory Retailer Facing Applications Category & Space Planning Demand Management Trade Promotion Management

DSR Solution Capabilities
Capture Adaptors to capture a variety of data types and sources Data cleansing tools to address data quality issues Extensible, retailer-based data model to maintain external data at the store/SKU level Routines to to harmonize data across multiple data aggregation levels and hierarchies Manage Pre-built category management, key account management and scorecarding dashboards and reports Flexible, robust business intelligence and reporting capabilities Analyze Rules-based exception management dashboard Automated workflow to facilitate resolution of exceptions User-defined, event-based triggers to initiate transactions in external applications and enable “sense & respond” capabilities Respond Pre-built integration with key Oracle applications such as Demantra, Siebel, Agile and G-Log Pre-built SOA integration with other external applications via Oracle Application Integration Architecture Integrate

Data Integration Today
Downstream Demand Data TPM Retailer 1 POS Capture + Cleanse TPO Retailer 2 POS Capture + Cleanse High latency of demand data Significant manual effort and cost Increased probability of inconsistencies across applications APS IRI Capture + Cleanse S&OP Capture + Cleanse ACN DRP Capture + Cleanse Distrib. 1 SNO Distrib. 2 Capture + Cleanse PLM Other Capture + Cleanse Data sources cleansed and managed independently

Data Integration With Oracle DSR
Retail Store Data POS sales Price Store inventory Promotional plans Store replen. rules Store forecasts Capture Manage Analyze Respond Oracle Demand Signal Repository Integrate TPM More timely data to better sense, shape and respond to demand Reduced manual effort and cost Consistent data more easily leveraged across teams and applications TPO APS Retail DC/ Distributor Data DC shipments DC inventory DC replen. rules Aggregated Demand Signals – SOA Messages – S&OP Other External Data DRP Retail loyalty IRI/AC Nielsen 3rd party demographic Causal (weather,etc.) RFID/EPC IMS, NDC, EDI (867, 852), Scripts, Pedigree Unstructured text SNO PLM Data sources centrally cleansed, harmonized and aggregated Pre-built dashboards and reports Powerful BI capabilities “Sense & Respond” event management

DSR Data Integration Scenarios
“Consumer products companies that take responsibility for the supply chain all the way to the retail shelf can see a 2% to 15% improvement in sales” AMR Research, “Shouldn’t You Be Minding the Store?” (May 2007)

DSR Integration Scenario: Demand Management & S&OP
More timely and accurate visibility to downstream demand signals Forecast based on store level visibility Accurately predict demand based on store level visibility Forecast based on attribute-level granularity

DSR Integration Scenario: PLM and Innovation
Improve both NPD and NPI capabilities Improved NPD by matching shopper and consumer insight to product attributes to enable attribute-based NPD and demand forecasting Improved NPI by providing more accurate visibility to channel inventory and event execution Improved PLM by providing more timely store/SKU level performance data Faster Cheaper Better ~10,700 new CPG products introduced ~3% of food and beverage introductions and 1% of non-food introductions achieved $50M sales Source: IRI, “2006 New Product Pacesetters, New CPG Brand Leaders” (March 2007); McKinsey Quarterly, “Reinventing Innovation at Consumer Goods Companies” (November 2006)

Scorecard Dashboard Leverages New Ways of Working Together Pilot
Monitor results vs. goals over time Drill-down to view supporting data View score by retailer and overall

Category Management Dashboard
Illustrative Multiple KPIs in a single dashboard Track performance relative to pre-defined thresholds Drill-down to view supporting data All reports viewable in retailer hierarchy or manufacturer hierarchy Reports can be automatically delivered via MS Office tools

Example Category Management Reports
Top Performers by Sales Category Sales Value by Type

Manufacturing Operations Center

What is MOC..? Mfg Ops Center is the same as… Mfg Ops Center is not…
Manufacturing Hub Manufacturing Data Hub Manufacturing Transaction Hub Enterprise Manufacturing Intelligence (EMI) Operational Intelligence Shop Floor Integration Solution Real-time Intelligence Mfg Ops Center is not… MES A Substitute for Corporate Business Intelligence (BI) solution Data Historian (OSI Pi, Wonderware….) Middleware 55

Supply Chain Management
Operational Challenges Zero Manufacturing Agility to Respond to Changing Demand Real-Time, Exception Prone Environment Dominated by Older Legacy Systems Multiple Plants w/ Different Systems Factory Automation Homegrown / 3rd Party MES Quality / SPC Maintenance / Service Multiple Contract Mfgrs Corporate Customer Relationship Mgmt Supply Chain Management Business Intelligence Enterprise Resource Planning Relatively Stable Environment Planning and Schedule-Driven Standard Systems Disconnected Multiple sources of truth Poor production performance visibility Knowledge not shared across resources Rigid, disconnected & disparate systems

A Need for Change Leading Business Trends
Shift from Periodic Reporting to Real-Time Performance Management Leverage Consistent Performance Metrics Across the Enterprise Plan and Schedule to Realistic Equipment Capacity and Adjust Operations in Real-Time Utilize an Enterprise Approach to Managing Manufacturing Operations Systems

Oracle Manufacturing Operations Center
Automation & Process Control Systems ERP Systems Users PLC CNC Machines DCS SCADA Systems Advanced Process Control Human Machine Interface MES Quality Cost Mgmt … Manufacturing Operations Data Model Role-Based Dashboards Contextual- ization Engine Corporate BI Cross-Plant KPIs Historical Trends Plant-Specific KPIs Real-Time Updates Device-Generated Data Production Actuals Schedules Item Master Data Production Manager Plant Mgr / VP of Mfg Shop Floor Communication Drivers The Foundation for Continuous Improvement in Manufacturing Operations Bridges the Gap Between Shop Floor & EnterpriseThe Hub is designed to aggregate real-time data directly from control systems such as PLCs, SCADA and DCS on the plant floor. The Hub would primarily utilize an OPC based connection to communicate with devices. To ensure coverage for different types of devices, we have partnered with Kepware Technologies. Kepware has built a large library of device drivers for various types of hardware found on the shop floor. In addition to their standard OPC Servers and Clients, Kepware would build additional capabilities such as Complex tags and would deliver tighter integration to Manufacturing Hub. However to really keep it open and flexible for customers, we would also deliver an API and interface table for customers that may want to build or utilize their own connectivity infrastructure on the shop floor. Error Handling Hub provides infrastructure to capture and process errors at every stage of data collection. In addition the OWB tool set provides customer to define their custom business rules to filter the data that gets into the Hub.

Enables you to… Contextualize Plant Floor Data and Synchronize with ERP Provide Real-Time Intelligence for Plant Operations Leverage Next Generation Manufacturing Operations Architecture CONFIDENTIAL: All capabilities and dates are for planning purposes only and may not be used in any contract

Manufacturing Operations
Single Repository for Mfg Operations Data Provide Consistent Information for All Manufacturing Users Manufacturing Operations Data Model Granularity Enterprise Level Products Orders Plans / Schedules Plant Level Work Orders Batches Mfg Routing Equipment Level Availability Status Output Quality Parameters Device Level I/O Tags Sensor ID Generic data model supports hierarchical structure for reporting or building KPIs and metrics Support for industry standards such as S-95 Out-of-the-box hierarchical dimensions: time, product, and equipment Flexible and configurable Open and extensible to meet the requirements of different industries Capture process variables Capture additional parameters for Item, Equipment, and Work Orders 3 key hierarchical dimensions Time (Calendar), Product and Equipment are delivered by the Manufacturing Operations Center out-of the box. For each of the dimension customer can build more than 1 hierarchy to analyze data. These hierarchies are flexible and multi-level with options to build custom defined hierarchies.

Shop Floor Communication Drivers
Integration with Manufacturing Equipment and Distributed Plant Systems Gather High Resolution Data Directly from Source PLC CNC Machines DCS SCADA Systems Advanced Process Control Human Machine Interface Mfg Operations Ctr Error Handling OPC Servers MES Shop Floor Communication Drivers Adapters Other Connectors 3rd Party OPC Client Support adapters for 3rd party systems, like data historians Build additional adapters using Fusion Middleware Tag data mapping Data filtering rules engine Capture and process errors at every stage of data collection Support broad range of devices Device Connectivity Manufacturing Operations Center is designed to aggregate real-time data directly from control systems such as PLCs, SCADA and DCS on the plant floor. It would primarily utilize an OPC based connection to communicate with devices. To ensure coverage for different types of devices, we have partnered with Kepware Technologies. Kepware has built a large library of device drivers for various types of hardware found on the shop floor. In addition to their standard OPC Servers and Clients, Kepware would build additional capabilities such as Complex tags and would deliver tighter integration to Manufacturing Operations Center. However to really keep it open and flexible for customers, we would also deliver an API and interface table for customers that may want to build or utilize their own connectivity infrastructure on the shop floor. Error Handling Manufacturing Operations Center provides infrastructure to capture and process errors at every stage of data collection. In addition the OWB tool set provides customer to define their custom business rules to filter the data that gets into Manufacturing Operations Center .

Integration with ERP Enable Seamless Information Flow
Leverage… Metadata-driven integration to Oracle EBS Fusion Middleware for SOA-based integration with other ERP Oracle EBS Discrete Mfg or Other ERP Shop floor transactions ERP Adaptor Master data, plans, and schedules Mfg Operations Center Simplify integration to ERP -- rely on Manufacturing Operations Center for data cleansing, error handing, etc. Reduce the cost of ERP integration -- eliminate one-to-one integrations

Automation & Process Control Systems
Shop Floor Data Contextualization Convert Raw Data into Useful Business Information Automation & Process Control Systems Transform Business Events Build Context Analyzable Business Data PLC DCS SCADA … Intelligence Systems Corporate BI Ops Center Dashboards Business Context Data ERP Systems CRM SCM ERP High Resolution Tag Data Define data transformation rules Rules by tag type Business-oriented aliases for tags Additional tag attributes like rollover values Use pre-built rules or create new rules Apply context to time series data Work Order WO Segment Apply out-of-the-box rules or define new rules Product Shift

Role-Based Dashboards and KPIs Deliver Performance Measures by Responsibility
VP of Operations Plant Manager Pre-built role-specific dashboards, reports, and alerts Graphical views Trend charts Graphs Tables Embedded best-practice calculations and KPIs Analytic workflows to drive actions Drill-downs into details for root-cause analysis Leverages OBIEE+ Configurable and customizable Are we achieving our cost and productivity targets? Red-yellow-green indicators Production Manager Production Supervisor What is happening now? What happened last shift? Operator QA Engineer How is the machine performing?

Extensible Analytical Engine and Dashboarding Tool
Build a Decision Support System Unique to Your Environment Accelerate deployment and adoption Easily adapt dashboards and metrics Provides a comprehensive Operational Intelligence framework Most standard KPIs available out-of-the-box Easily identify, select, modify, and format relevant KPIs

Production Manager Dashboard Line-Level Status
Click to view alert details Delivered Via BAM Active Viewer

Production Throughput Analysis Track Production and Identify Potential Bottlenecks
Supervisors, Line Managers Track against targets for shift, day, week, or month Monitor backlogs by individual equipment Determine equipment status Visual cues quickly indicate production status Plant Managers, VP of Manufacturing Click to view alert details View throughput by product, plant, line, and equipment Analyze monthly trends to ensure aggregate performance Monitor production volumes & throughput from anywhere in the enterprise

What is Next-Generation Manufacturing Operations Architecture?
Next-Generation Architecture Abstraction Layer ERP Distributed Plant Systems Automation & Control Mfg Operations Ctr Built on a common abstraction layer of production / equipment data Leverage existing investments in plant IT infrastructure – no rip & replace Allows for gradual upgrade of plant systems “It is often more expedient to install an abstraction layer built on a plant-level data store than to reengineer the plethora of existing applications to achieve normalization. We see this approach rapidly emerging as a best practice.” Alison Smith, February 2008

Contextualize Plant Floor Data and Synchronize with ERP Consistent mfg information for all users Convert equipment data into useful business info Ensure rapid response to manufacturing issues Provide Real-Time Intelligence for Plant Operations Deliver performance metrics & trends by role Easily build dashboards to your unique needs Identify performance improvement opportunities Leverage Next Generation Manufacturing Operations Architecture Leverage existing plant IT infrastructure Enable gradual upgrade of plant systems Simplify IT support for your core mfg strategy The Foundation for Continuous Improvement in Manufacturing Operations

Bring up on stage two customers to tell the audience about their experiences.
Manpower Associates is a $14.9B global company with 27,000 employees in the temporary staffing business. Manpower runs a combined PeopleSoft Enterprise and JD Edwards EnterpriseOne shop. These experts in human resources use Enterprise HCM for their own staffing and EnterpriseOne Payroll and Service Billing for handling the large volumes of US-based temporary staff. Manpower is very happy with Oracle’s support since purchasing PeopleSoft and is looking forward to a long relationship with Oracle. Spokesperson will be Jay Schaudies, Vice President, Global eCommerce. Welch Foods is the food processing and marketing arm of National Grape Cooperative Association. Organized in 1945, National Grape is a grower-owned agricultural cooperative with 1,461 members. The company, headquartered in Concord, Massachusetts, operates six plants located in Michigan, New York, Pennsylvania and Washington. The company was running a mix of legacy, home grown, and manual systems that failed to provide senior management with accurate and timely cost and production information. Welch’s required a centralized manufacturing and financial information system to improve management decision making. The solution had to be hot-pluggable with existing technologies, for example, Welch’s Plumtree portal. Welch Foods chose Oracle over SAP for this business-critical application. The key to the customer’s business problem was their ability to manage costs. The company’s costs are driven by fruit solid content in each of their products, and they use a specialized technique called BRIX for measuring and calculating the cost of materials. Welch’s compared SAP and Oracle SAP’s software was too rigid and, therefore, unable to include the BRIX calculation in their manufacturing solution. Only Oracle’s OPM could bind this custom cost method into the Quality Management Process. Technology customer yet to be determined. Current possibilities include eBay and FTD Florists.

Nicki Sommer Principal Sales Consultant NCOAUG, August 15, 2008

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Nicki Sommer Principal Sales Consultant NCOAUG, August 15, 2008

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