Presentation Transcript

1. Beyond Order Orchestration: Plan and Execute with Allocation and Backlog Management Rajat Bhargav, Director, Product StrategyDanny Smith, Executive Director, SCM Solutions
2. Safe Harbor Disclaimer 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 Corporation.
3. Agenda The Business Problem The Desired Process Oracle’s Solution Q&A
4. 53% of high-tech companies collaborate with partners on demand forecasting High-tech companies do not meet their allocations commitments 50%of the time Inaccuracy of data and the inability to stick to the committed forecast impede the success of collaborative forecast compliance programs. Supply Chain Management Review 2013 Order Fulfillment Survey
5. Allocation Process 4 Collaborative Allocation Budget Supply Statistical Forecast Supply Planning Promising Demand Allocation Rules Constrained Supply 1 2 7 8 5 3 6 Run Statistical Forecast Import forecast to collaborative environment Create allocation plan (consensus) Import allocation plan as forecast to supply plan Run supply plan (constrain demand) Import constrained supply plan into collaboration environment Create final allocation plan and export for enforcement Collect supply plan (stock and production) Orders quantities are kept consistent with final allocation planExcess order quantity is split and queued 9 Customer Orders
6. Align Planning & Execution with Order Promising Planning Execution Forecast Plan Source Order Capture Orchestrate Ship Multi-channel, Multi-division, Multi-partner Allocated ATP/CTP/PTP Order Promising Feasible Optimal
7. Align Planning & Execution with Order Promising Planning Execution Forecast Plan Source Order Capture Orchestrate Ship Only 1 in 3 companies feel good about their order promising Source: Oracle / Capgemini Multi-channel, Multi-division, Multi-partner Allocated ATP/CTP/PTP Order Promising Feasible Optimal
8. Align Planning & Execution with Order Promising Planning Execution Forecast Plan Source Order Capture Orchestrate Ship …. think that their exception handling needs improvement Delivery delays and resultant expediting are the largest drivers of fulfillment costs Source: Oracle / Capgemini Multi-channel, Multi-division, Multi-partner Allocated ATP/CTP/PTP Order Promising Feasible Optimal
9. Promising Promise Date Promising Engine Demand (Commitment) Supply (Inventory and Production) Allocation Availability Rules lead times shipping constraints service levels sourcing costs calendars
10. Distributed Order Orchestration Components Business Rules PROACTIVE EXCEPTION MANAGEMENT Business Process Order Promising CHANGE MANAGEMENT
11. Configurable Business Rules Enrich orders for fulfillment Select optimal fulfillment process Assign fulfillment process to lines Route requests to appropriate fulfillment system Enable business users to configure rules without IT coding Warehouse In Store Commerce
12. Business Process Mapping Define unlimited global fulfillment processes Add wait times & prevent premature actions Support change order processing, process restart, and multiple processes per order Improve insights & decisions with in-context embedded analytics
13. Order Promising Create/Assign Sourcing & Promise Rules Profitable to Promise, Capable to Promise, Available to Promise Allocation by Demand Class (e.g. channel) Manage jeopardy conditions Perform what-if analysis for cost & delivery times with embedded analytics
14. Order Change Management Rules-driven decision making based on order attributes, user role or business process Processing Constraints Reset Process to Re-execute Cost of Change? Update Allowed? Order Change Request Provides cost to change visibility for smarter updates
15. Proactive Exception Management Jeopardy Management Which customer is impacted? Which step is late? What is the order’s priority? Is this a problem yet? Who needs to be alerted? What is the cost to rectify? How late is the step?
16. 100% Open Standards Role-Based User Experience What You Need to KNOW WHO Can Help What You Need to DO HOW to Get it Done 100% Open Standards Intelligent Business Processes Java, BPEL, XML,HTML, AJAX, Portlet, RSS, Mobile, etc. Services Unified Information Employee Ledger Date Effectivity Customer Organization Territory … Product Business Unit Trees
17. Current Situation without GOPSub-optimal service, revenue, and margin CUSTOMER Standard lead times Isolated stock visibility Availability limited to stock on hand Plants Ware house Partners Store
18. The Solution: Fusion GOPOptimized delivery across all sources of supply CUSTOMER Available to Promise (ATP) Capable to Promise (CTP) Profitable to Promise (PTP) Fusion Global Order Promising Visibility What-if Simulation Embedded Analytics Plants Ware house Partners Store
19. Fusion Global Order Promising Highlights Architected for flexibility Supply chain definition Promising rules Capabilities new to Fusion Profitable to Promise Alternate availability options What-if simulation Embedded analytics In-memory performance
20. Create and Assign Sourcing Rules Key Features Define sources and their priorities Specify internal orgs and suppliers / supplier sites Assign sourcing by item, category, item-org, customer, or geography/zone
21. Create and Assign ATP Rules Key Features Choose among 3 modes For supply chain availability mode, specify ATP, CTP, or PTP, and multiple attributes Assign rules by category, org, item, or item-org
22. Specify and Assign Allocation by Demand Class Key Features Preserve scarce supply for most important orders Allocate by Demand Class Assign allocation rules by category, org, item, or item-org
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