FY09 Commercial Planning - SCM

FY09 Commercial Planning - SCM
Keith Ip SCM Applications Solutions Consulting

Agenda Where we are Competition Where we should go Recommendations 2

? Product Solutions Management Team HCM SCM CRM FMS ACE / ARCH
Mike Hodgson (45) ?? (64) Shrav Malkani (60) Sally Li (59) David Barkess (54) ANZ Kristy Durston KP Loke Wayne Houghton Chris Downie Adam Krebet Industry Specialist ASEAN Jackie Goh Christo Sardjono Lisa tay TBH Alvin Leung INDIA Suryanaran. Iyer Sujit Sahu Samik Roy Aditya Bhattachar. Anurag Dubey G.CHINA (Yu Sicheng) Oliver Chen Keith Ip Binggin Huang Joyce Tan Charles Zhang Paul Peng KOREA HyeSoo Cho KangHyoug Lee Seong Hwan Young Hoon Kim JinYeun Park SCS Jeff Olson We often talk about the ‘value of the stack’ and it sounds very technical. I want to be sure to highlight that our applications also reap tremendous benefit from the technology. These are several areas where we have unique advantages – across all the applications. Prod Mgt John Hui (32) Matt Van Rensburg (7) 3

Headcount Status AIA & Lead SC skills key 4

FY09 GC SCM SC Organization Chart
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FY09 GC SCM SC Organization Chart
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Now (from IDC) 7

Assuming Oracle expects 30+% growth……
Now and Future 17% CAGR 20% CAGR 15% CAGR 20% CAGR Assuming Oracle expects 30+% growth…… Gen more demand, win more over SAP, in areas where they suck, Penetrate more in Growth Cities 8

What SAP did when entering China?
Enter China in 1991, SAP China established in 1995, Key wins of Lenovo and Haier in 1998 Lighthouse Accounts – Invest in working with leading companies by industries (Investing in Sinopec for 3-4 years without any rev before signing a 10M deal) Heavily invest in partners – Granting 30% margin to partners Create Strong Eco-system in key industries – Oil & Gas, Chemical, Tobacco, Traditional Mfg, Metal, Auto, etc… Strong Partner Eco-system Build up the Brand of Industry Solutions 9

SAP Today A large pool of install base of upsell add-on license
Enough funding for other smaller companies as well as dropping price when competing against us Leverage their brand to sell more ERP With our brand legacy, it takes time for learning curve in order to penetrate into SAP install base SAP is building their specialization teams (PLM, SRM, EPM) SAP is pushing their +1  Minimize Oracle’s Differntiators Time Window is closing 10

ERP Landscape in China – Winning ERP with EDGE/Industry Solutions
Opportunity for CMRL Emerging Industries Mid Size (local FIN) Government Mid Market Banks SASAC MNC SAP IB Hi Tech ERP + EDGE / Industry Solutions ERP Replacement EDGE / Industry Solutions Adoption Time 11

Oracle’s Strength The Oracle brand
Acquisition strategy / Best of breed solutions Leading “+1” solution differentiators (Agile, AutoVue, Stellent, Demantra, Projects portfolio, EPM, MDM, etc.) Talented People 12

Shift to Value Chain Orientation
Supply Chain Design Chain Demand Chain Design Chain Value Creating Activities Supply Chain Demand Chain INNOVATION SUPPLIER RELATIONSHIP MGT Key Points: 21st century – more complex, Integration of numerous sub-chains, into your organization Collaboration of the components The extended chain becomes a network of bilateral product information encompassing collaboration of suppliers, partners and customers with the factory and dealer. Information is not impeded but rather facilitated and orchestrated In the new and expanded roles including INNOVATION as well as the Supplier Relationship Mgmt. Eg: design and personalization, CTO and ETO preferences. In the twenty years since Porter published his Value Chain work, the world has undergone a remarkable transformation The economic environment has become global, requiring firms to manage far flung partners, suppliers, and supply chains Complexity has increased as more relationships and inter-relationships have been forged. Today’s firms must operate in an interdependent network of suppliers, and sub-contractors spanning multiple continents. In the world Porter described, the FAX was leading edge communications technology, but today everything is connected through the internet. There is an avalanche of information available, and firms have expectations of instant response from their suppliers. Customers now have greatly expanded choices which show up as increased competition to firms, but suppliers also now have the ability to interact with their customers to customize their products and delivery services This has led to innovation moving from a supporting function in yesterday’s value chain, to a critical component of today’s value chain. Smaller and more nimble firms can gain market leading positions by harnessing innovation, size is no longer a guarantor of success. To be competitive today’s firms must be able to: Collect, organize and extract insight from extraordinary amounts of volatile, fast moving data Create nimble extended enterprises that will compete as global networks of interconnected firms Use innovation to transform their products and processes Using Information is key to survival. Today, value creation is information-driven. HR Supporting Activities Administrative Infrastructure Convergence of Chains - Demand, Supply, Design Multi-enterprise – Collaboration, Orchestration, Flexible Information-Centric – Visibility, Predictive, Real-time 13 13 13 13 13

How the new R12.1 products compliment this strategy
Advanced Planning Command Center Elevates supply chain planning information to a business decision making level by combining cross-domain planning analytics within the context of business scenarios Manufacturing Operations Center Delivers an integrated view of manufacturing status and performance by combining ERP and real-time plant floor information, and using this for extensible analytics Demand Signal Repository Creates a shared and unified view of real-time demand information between parties in the value chain to drive closed-loop decision making Service Parts Planning Enables a responsive service supply chain and increases the profitability of after market service, helping OEM’s extend their value chain Deal Management Optimizes the effect of price-driven demand shaping 14

Service Supply Chain Must manage both forward and reversed material flows Customers Supplier (Repair) Repaired In repair Service technicians Regional DCs Central DC Supplier (New Buy) To set the stage, here is a graphical representation of a Service Supply Chain. But before we walk through this, what we are typically used to is the Manufacturing or Finished Goods Supply Chain where we see Manufacturing operations creating Finished Goods based on Sales Orders, Demand or a Forecast and pushing those goods forward into the supply chain to the customer. But with the Service Supply Chain, there are really two big differences: In Service Supply Chains, we see the presence reverse logistics material flows where returns and defectives make their way back to be repaired by Repair Depots and Repair Suppliers and we see Service Technicians fixing customer equipment in the supply chain, and in both cases, pushing that returned / and now repaired material forward into the supply chain into the distribution channels for the customer. So the two big differences between the Manufacturing Supply Chain and the Service Supply Chain are the Reverse Logistics Element and the Repair Element. On-hand Consigned Repair depot Material flow of good spares Material flow of defective spares 15

Service Industry Trends
Service is becoming a main profit driver even in manufacturing companies Desire to move from cost center to profit center Service parts have much higher margin than finished goods Service as a competitive differentiator - Better customer retention Finished goods have become commoditized Hi-Tech, Travel/Transportation & Aerospace & Defense (A&D) have unique requirements in terms of complex parts planning Repairs are being outsourced Rotables and serialization present planning complexities Interplay between parts planning and execution increasingly becoming important Logistics Service Provider (LSP) is a growing market especially with ‘End to End’ providers Significant amounts of money tied up in spares inventories Initiatives to reduce inventories while maintaining / improving service 16

Two Different Worlds Why Service requires different approaches and systems MANUFACTURING SERVICE Centralized Few locations Few products Planners manage few products 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 17

Service Industry Challenges in managing the service supply chain
Forecasting High SKU counts, low volume Intermittent demand Product life cycle events New product introductions End of part life / service life, supersession Inventory, replenishment, and distribution planning Dynamic redistribution of inventory as customer demand shifts Returns: part condition Part supersession and complex part chains Aggressive service level agreements and budgets Service level and response time key in balancing inventory Trade off service levels and budget 18

Oracle’s Service Parts Planning Solution
The better news: we’ll have an even better solution available soon ! Available with 12.FP: Demantra, SPP, GOP, CP, IO, SNO SPP – Service Parts Planning within Advanced Planning Suite Key features supported: Demand planning and replenishment / distribution from a single Workbench Returns / repairs / reverse logistics / dual sourcing of new buy & repair Part condition, supersession, failure rates, repair lead time, and criticality support Auto-release new buy and repair recommendations to Spares Management and Depot Repair Key environments: Works well for customers that are dealing more with complex reverse logistics and repair processes Solution modeling for “part conditions” not required: Use same part numbers to represent “good” and “bad” parts (part condition supported) Available with 12.FP: Demantra, SPP, GOP, CP, IO, SNO Key features supported: Demand planning and replenishment / distribution from a single Workbench Incremental and netchange planning and simulation Forecast on consumption and global forecasting Returns / repairs / reverse logistics Dual sourcing of new and repair, support for inventory rebalancing (circular sourcing) Part condition, supersession, failure rates, repair lead time, and criticality support, Productivity enhancing UI with personal queries, work lists, comments, and user preferences Auto-release new buy and repair recommendations to Spares Management and Depot Repair Safety stock calculations and stocking strategies Budget analysis Demantra can be used for more advanced forecasting needs (product life cycle based forecasting, causal factors, additional forecasting methods, promotions for parts sell-off strategies, collaborative demand planning, etc.) Replenish to forecast Forecasting, planning, and execution tied together via integration Design most profitable distribution network and analyze risk scenarios for distribution and supply strategies Solution modeling: Use same part numbers to represent “good” and “bad” parts (part condition supported) Works well for customers who’s main problem is solving a spare parts distribution problem (where do I hold how many cataloged parts in my service distribution network) Works well for customers that are dealing more with complex repair processes (returns and reverse logistics streams, part supersession chains supported)

Coming in 12.FP – Service Parts Planning
Integrated forecasting and replenishment Minimize inventory and purchasing cost, and out-of-stock impacts Dynamically reallocate and reposition parts across your entire network (customer locations, dealer locations, ESLs, and suppliers) Use up superseded parts, repair before new buy Consider key service planning constraints Part supersession, condition, and criticality Sourcing of repair-at and buy-from Repair resources (internal) Out-of-the-box integration with Execution Release recommendations for new buy, repair, and transfers

Coming in 12.FP – Service Parts Planning
Out-of-the-box integration with Spares Management and Depot Repair Global parts inventory visibility across all service organizations Out-of-the-box integration with Oracle Spares Management and Oracle Depot Repair Release depot repair orders, reschedules, and transfers Release spares management new buy purchase orders, repair orders, and transfers 21

Service Parts Planning Solution Selling into various Industries
<Insert Picture Here> Service Parts Planning Solution Selling into various Industries 22

Service Industry Challenges
Automotive / Distribution-only Distribution Only / High Volumes Requires forecasting and distribution / replenishment Support dealer network Challenges Forecasting High SKU counts, low volume, intermittent / seasonal Forecasting at the Dealer level Inventory, replenishment, and distribution planning Distribution to dealer network to address sporadic / erratic ordering patterns Part supersession Position TODAY: Demantra, ASCP-DRP, GOP No reverse logistics / repair element; Dealers modeled as Orgs Where we’ve won: General Parts Distribution Only / High Volumes Requires forecasting and distribution / replenishment Support dealer network Challenges Forecasting High SKU counts, low volume, intermittent / seasonal Product life cycle events: new product introductions, end of part life /= service life, supersession Forecasting at the Dealer level Inventory, replenishment, and distribution planning Distribution to dealer network to address sporadic / erratic ordering patterns Part supersession Position TODAY: Demantra, ASCP-DRP, GOP No reverse logistics / repair element; Dealers modeled as Orgs Position IN NEAR FUTURE: SPP, GOP, Demantra (for adv. Fcsting) Usage, returns, and population based forecasting; use failure rates Part supersession, criticality matrix, and condition Dealers modeled as Orgs Optionally position: IO and SNO Target service levels, budget analysis, design of service supply chain General Parts Win Manhattan and i2 lose spark—and $2M—at General Parts Automotive parts supplier (CARQUEST) selects Oracle APS over i2 and Manhattan About General Parts General Parts (GP) is a premier supplier of replacement parts, accessories, supplies and equipment for most makes of automobiles, as well as light and heavy-duty trucks, off-road equipment, buses, recreational vehicles, and agricultural equipment. Main Business Challenges & Expected Benefits Despite a large presence with 3,400 auto parts stores and 40 distribution centers across the US, GP has strong competitors. If a consumer needs a part for their ’97 Impala and GP doesn’t have it, they’ll walk down the street to a competitor. For GP, it’s all about having the right part at the right place at the right time. To meet these demand challenges, the average store stocks about 10,000 parts. Retail outlets are replenished by super stores or distribution centers, which stock over 100,000 SKUs. Determining which parts to stock at the store level is a make or break proposition. Under stock the right ones and watch the customer go to Auto Zone or Pep Boys. Overstock the wrong ones and watch inventory carrying costs crunch the bottom line. GP needed a technology platform that would: . Reduce inventory cost . Increase revenue (avoid lost sales) . Improve customer service Competitors GP started with a long list of 12 vendors. i2, Manhattan (Evant) and Oracle were asked to demo resulting in. Manhattan and Oracle being selected as the two finalists. Products Purchased - $2.08 Million in license . Demantra Demand Management (DM), Advance Forecast Demand Modeling (AFDM), Real Time Sales and Operations Planning (RT-SOP) . Advanced Supply Chain Planning (ASCP) . Constraint Based Optimization (CBO) . Inventory Optimization (IO) . Strategic Network Optimization (SNO) Why Oracle Won the Deal Oracle’s Advanced Planning proven integration with legacy manufacturing systems showed GP a quick path to ROI. Inventory Optimization (IO) will handle the “right place, right quantity” and Advanced Supply Chain Planning with Constraint Based Optimization (ASCP/CBO) will drive the store replenishment (right time). Although Strategic Network Optimization (SNO) was originally out of scope, analysis of GP’s global supply chain enabled us to re-introduce SNO as a key differentiator over Manhattan. GP’s overseas suppliers often offer discounts for “full containers.” GP will use SNO to help determine whether the discounts offset the additional inventory carrying costs. Demantra’s proven track record and ability to accurately forecast intermittent demand were big plusses. With Real Time Sales and Operations Planning (RT-SOP), GP will sense, shape, and respond to demand quickly through embedded analytics and alerts. Demantra’s multiple causal capabilities were another clear differentiator over Manhattan’s Evant. Mike Peterson led a masterful sales campaign. Along with Linda Marley, they captained the resources needed to convince the customer Oracle understood their business and could deliver competitive advantage. The SC team immersed themselves in the customer’s business and a demo “walk through” allowed our internal champions to provide essential guidance. The Oracle message was reinforced by Kanbay (Cap Gemini), who stressed the value of a single source solution including lower TCO, greater accountability, out-of-the-box integration et al).

Heavy Equipment / Industrial Manufacturing Aftermarket spares support for customer equipment Returns / Repairs / Reverse Logistics Dual sourcing of new and repair Challenges Forecasting High SKU counts, low volume, failure rates – install base Inventory, replenishment, and distribution planning Dynamic redistribution of inventory as customer demand shifts Returns: part condition, part supersession and complex part chains Aggressive service level agreements and budgets / trade offs Position TODAY: Demantra, ASCP-DRP, GOP Model good and bad parts as different items. Where we’ve won: Aftermarket spares support for customer equipment Returns / Repairs / Reverse Logistics Dual sourcing of new and repair Challenges Forecasting High SKU counts, low volume, intermittent / seasonal demand, failure rates – install base Product life cycle events: New product introductions, End of part life /= service life, supersession Inventory, replenishment, and distribution planning Dynamic redistribution of inventory as customer demand shifts Returns: part condition, part supersession and complex part chains Aggressive service level agreements and budgets Service level and response time key in balancing inventory Trade off service levels and budget Position TODAY: Demantra, ASCP-DRP, GOP Model good and bad parts as different items. Position IN NEAR FUTURE: SPP, GOP, Demantra (for adv. Fcsting) Usage, returns, and population based forecasting; use failure rates Part supersession, criticality matrix, and condition Optionally position: IO and SNO Target service levels, budget analysis, design of service supply chain GE Aircraft Engines Integrate with 12 legacy systems via Oracle ERP 11.0 shell APS 33 organizations 100K items 2 years horizon GE Oil & Gas 12 organizations with heavy use of inter organization sourcing rules Mostly a hard pegged planning environment ~2.5M planned items Plan for safety stock Shop Floor scheduling using Oracle manufacturing scheduling

High Technology Aftermarket spares support for customer equipment Returns / Repairs / Reverse Logistics Dual sourcing of new and repair Challenges Forecasting Very short product life cycles Inventory, replenishment, and distribution planning Part supersession, returns, part conditions, complex part chains Aggressive service level agreements and budgets / trade offs Position TODAY: Demantra, ASCP-DRP, GOP Model good and bad parts as different items Where we’ve won: Aftermarket spares support for customer equipment Returns / Repairs / Reverse Logistics Dual sourcing of new and repair Challenges Forecasting High SKU counts, low volume, intermittent / seasonal demand, failure rates – install base Product life cycle events: New product introductions, End of part life /= service life, supersession Very short product life cycles Inventory, replenishment, and distribution planning Dynamic redistribution of inventory as customer demand shifts Returns: part condition Part supersession and complex part chains Aggressive service level agreements and budgets Service level and response time key in balancing inventory Trade off service levels and budget Position TODAY: Demantra, ASCP-DRP, GOP Model different part numbers for good and bad Position IN NEAR FUTURE: SPP, GOP, Demantra (for adv. Fcsting) Usage, returns, and population based forecasting; use failure rates Part supersession, criticality matrix, and condition Optionally position: IO and SNO Target service levels, budget analysis, design of service supply chain Fuji Xerox Forecasting using Demand Planning 18 Month history to generate 9 month plan Generate forecast by part/country/month level Distribution Planning using Advanced Supply Chain Planning 9 month supply plan Plans for Asia Pac 6 country organizations and 2 distribution hubs Improved forecast accuracy by 35% Reduced Inventory by $40m Improved supplier collaboration

Travel & Transportation (Aircraft, locomotives, public transit, etc.) Aftermarket spares support for repairing and maintaining aircraft Returns / Repairs / Reverse Logistics Dual sourcing of new and repair Maintenance / Overhaul operations Rotable planning / serialization / tail number planning Challenges Forecasting Part conditions / probabilistic forecasting / reverse BOM for cannibalization Very deep BOMs for repair, fly away kits, initial provisioning Inventory, replenishment, and distribution planning Strategic placement / pooling for very expensive / low volume items Position TODAY cMRO ODP for out-of-the-box integration Demantra will require custom integration We have team members who specialize in cMRO to help you. Aftermarket spares support for repairing and maintaining aircraft Returns / Repairs / Reverse Logistics Dual sourcing of new and repair Maintenance / Overhaul operations Rotable planning / serialization / tail number planning Challenges Forecasting Part conditions / probabilistic forecasting / reverse BOM for cannibalization High SKU counts, low volume, Intermittent / seasonal demand, causal factors Very deep BOMs for repair Fly away kits, initial provisioning Inventory, replenishment, and distribution planning Strategic placement / pooling for very expensive / low volume items Part supersession and complex part chains Aggressive service level agreements and budgets Service level and response time key in balancing inventory Trade off service levels and budget Position TODAY and in FUTURE cMRO ODP for out-of-the-box integration Demantra will require custom integration EAM, Advanced Supply Chain Planning, Global Order Promising 26

Aerospace and Defense Aftermarket spares support for repairing aircraft & defense equipment / weapon systems Returns / Repairs / Reverse Logistics Dual sourcing of new and repair Maintenance / Overhaul operations Rotable planning / serialization / tail number planning Challenges Forecasting Part conditions / probabilistic forecasting / reverse BOM for cannibalization Very deep BOMs for repair, fly away kits, initial provisioning Inventory, replenishment, and distribution planning Strategic placement / pooling for very expensive / low volume items PBLCs (Performance Based Logistics Contracts) drive high service levels Position TODAY cMRO ODP for out-of-the-box integration Demantra will require custom integration We have team members who specialize in cMRO to help you. Aftermarket spares support for repairing and maintaining aircraft and defense equipment / weapon systems Returns / Repairs / Reverse Logistics Dual sourcing of new and repair Maintenance / Overhaul operations Rotable planning / serialization / tail number planning Challenges Forecasting Part conditions / probabilistic forecasting / reverse BOM for cannibalization High SKU counts, low volume, Intermittent / seasonal demand, causal factors Very deep BOMs for repair Fly away kits, initial provisioning Inventory, replenishment, and distribution planning Strategic placement / pooling for very expensive / low volume items Part supersession and complex part chains Aggressive service level agreements and budgets Service level and response time key in balancing inventory Trade off service levels and budget Position TODAY and in FUTURE cMRO ODP for out-of-the-box integration Demantra will require custom integration EAM, Advanced Supply Chain Planning, Global Order Promising Aircraft Engines 27

Current Competitors SAP Servigistics MCA (Morris Cohen Associates)
APO Recently released a service parts specific solution - unproven Partnership with MCA Servigistics Good presence and slick product Good marketing Strong in distribution, reverse logistics, repair forecasting MCA (Morris Cohen Associates) Strong in Aerospace and Defense Good algorithms and approach Baxter Planning Systems Outsourcing / hosted model for SPP and SCP Not aggressive in marketplace / weak presence Conference room pilot / consulting approach Xelus / Click Commerce Acquired twice in past few years, uncertain future Current customers being replaced by Servigistics and others 28

Market Review 29

Market Review SAP = Caution 30

Sample Service Parts Planning Customers
Hi tech United Space Alliance A&D Aircraft Engines Siberian Airlines Travel & Transportation Industrial Manufacturing 31

A Few Service Management Customers …
Hi Tech Office Equipment Manufacturing Aerospace & Defense Automotive Comms & Utilities 32

Oracle Service Parts Planning Additional Information
Deployment and Integrations Part of Oracle APS and can be deployed as follows: Separate APS 12.1 instance - fully integrated with EBS R12 and EBS R11i10* Standalone - integrated with other ERPs through legacy integration* Single instance - combined EBS+APS instance, when EBS 12.1 is available later this year Availability: GA now as a part of R12.1 APS Feature Pack – deployable on a separate APS 12.1 instance Controlled Availability process in effect to help track initial sales Pricing: $1750/$M of Cost of Goods Sold (COGS) More Information: apps.oraclecorp.com www-apps.us.oracle.com/aps * - Available soon 33

FY09 Commercial Planning - SCM

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