Post on 29-Mar-2015
Turn Service Supply Chain into Profits with Value Chain PlanningMoshin Lee, Sr. Director, Oracle Value Chain Planning Product Management
Graham Reid, Oracle Global Process Owner, Spares Planning
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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.
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Program Agenda
Evolving to best in class service parts and MRO planning with
Oracle VCP
Development Roadmap
Case Study: Oracle’s use of VCP for service parts planning
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Oracle Value Chain Planning Solution
Common foundation Single source of truth Centralized services Start anywhere, redo nothing
Planning and
Optimization
ScenarioPlanning & Analytics
EngineeredSystems &Solutions
Planning Data
Management
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ASSET INTENSIVE
Service and Maintenance Planning solutionThe Oracle difference: The right solution for the right problem
Maintain, repair, and overhaul complex equipment and installations
Repair work order hierarchies
Rotables and serialization
Long range and operational planning – Balance material, resources and budgets
Plan new buys, internal and external contractor repairs; plan maintenance repair schedules
CMRO and EAM based execution
ASCP/DM/IO/PS/GOP – CMRO/EAM integration: Korean Air
DISTRIBUTION CENTRIC
• Multi-echelon distribution with rebalancing and fair share allocation
• Standard catalog driven parts, no part condition; standard bills
• Standard work orders for assembly, new buy orders
• Forecasting and replenishment, with optionally inventory optimization
• ASCP/IO/DM: CARQUEST, Orbotech
REPAIR CENTRIC
• Use part condition (“usable”, “defective”)• Internal and external repair• Part criticality matrix linked to forecasting
rules• Optimize redistribution and replenishment• Account for supersession (repair to) in
forecasting and replenishment• Unified forecasting and replenishment UI• Release recommendations to Depot
Repair and Spares Management
• SPP/DM/IO: Oracle, Virgin Media, Virgin Mobile, Huawei, Teradata
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Support intermittent demand patterns
Leverage highly accurate Bayesian engine
Population and failure rate based forecasting
Forecasting based on supersession
Analyze and fix exceptions
Supersession-based planning
Plan reallocation and transfer of parts
Plan internal and external repair before new buy
Release planning recommendations to Execution
Single UI for forecasting and replenishment
Part and supersession chain centric analysis
Zone and enterprise views
Planner work lists
Personal and public queries
Auto-release rules
Parts Forecasting Replenishment Analysis
Improve spare parts planning
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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
Improve planner productivity through automation of release
Execute internal and external repairs
Execute to plan
Integrated planning and executionReduce cost via pre-built integration
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Work list driven actions
Supersession
Integrated demand and supply planning
Pegging view
Service planner workbench
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Forecast new service level agreements at customer and customer site level
Forecast new parts based on part characteristics
Centralized demand management for service and manufacturing
Enable simultaneous forecasting of end items and spare parts
Consider causal factors
Analyze impact of new service level agreements on safety stock policies
Simulate the impact of inventory budget reductions
Simulate trade offs between service levels and cost
Manage postponement decisions across all service facilities
Monitor service level agreement adherence
Monitor repair versus new buy trend patterns
Review service parts inventory performance
Compare plans and trends over time
Involve key managers
Advanced Forecasting Multi-echelon postponement Plan analytics
Evolve to best in class spare parts planning
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Account for detailed service level and fulfillment lead time targets
Deploy inventory to meet entire SLA portfolio
Account for repair, lead time, space, budget constraints
Simulate SLA scenarios
Evolve – optimize spares stocking
Minimize SLA portfolio cost
99%, 2 hours
97%, 4 hours
92%, 24 hours
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Monitor service level agreement adherence
Monitor effective use of repairable parts before buying new
Compare changes between plans and analyze trends
Analyze spare parts inventory performance
360 degree visibility
Evolve – Monitor parts planning performance
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Integrated maintenance scenario to support total cost of fleet operation – CMRO Unit Maintenance Plan, EAM Budget Forecast, Demantra non-Maintenance Forecast, ASCP Planned Repair Orders
Projection of resource utilization – Global, organization, department
Projection of total material requirements – Calculate retention levels and justify disposal actions
Projection of maintenance cost
Calculate planning factors
Scenario planning: select specific CMRO product classification (simulations) and EAM budget forecasts as basis for planning
Match defective demands with defective supplies
Plan repairs of complex subassemblies and components
Plan purchases, internal maintenance, and contractor maintenance
Consider repair capacity and material availability
Consider CMRO and EAM repair BOMs and routings
Consider resource (equipment) downtime due to preventive maintenance
Maintenance scenario planning and S&OP Balance supply and determine repair
Asset Intensive Planning with VCPPrebuilt integration with EBS CMRO and EAM
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What is the non-routine material and resources associated with a Maintenance Requirement (MR)?
What is the total material and resources associated with a components item’s repair?
What is the difference between Engineering failure rates and actual failure rates?
What are the material and resources associated with flight operations?
Calculate planning factors based on non-routine resource and material requirements and incorporate into CMRO MR definition
Supports routine historical analysis contrasted to CMRO Engineering definition
Forecast non-UMP visit forecast and leverage to build flight schedules in CMRO (pre-flight, post-flight and transit visits are not contained in Unit Maintenance Plan)
Planning Factors – Business needs Solution
Asset Intensive Planning with VCPPrebuilt integration with EBS CMRO and EAM
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Which visits are early, on-time or late and why? What tasks are on the critical path? What is the total machine, crew, and tool utilization across visits,
or for a specific visit? How much of the utilization is associated with routine versus non-
routine work? What is the impact of taking down production equipment for
maintenance? What is impact of rescheduling the EAM maintenance?
What is the average visit duration by visit type (PDM, Engine Overhaul)?
How can Visit throughput be maximized?
Schedule CMRO Visits taking into account visit dates, milestones, task hierarchies, and prec. constraints
View CMRO work breakdown structure and critical path Schedule Visits while considering EAM preventative maintenance Override EAM preventative maintenance Model key constraints on the shop floor (crew, machine, tool –
capacity and calendars) Manually re-sequence visits Respect inventory reservations Constrain dates based on outside processing schedule Create multiple simulations and compare (on time, now late, KPIs)
Maintenance Scheduling – Business needs Solution
Asset Intensive Planning with VCPPrebuilt integration with EBS CMRO and EAM
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Asset Intensive Planning with VCPProcess flow
Complex Maintenance Repair and Overhaul
EnterpriseAsset
Management
VCP Demand Management and
S&OP
VCP Production Scheduling
VCP Advanced Supply Chain Planning
VCP Inventory Optimization
OrderManagement
Detailed maintenance schedule
Visits and Visit WBS
Adjusted WO dates
WorkOrders
Planned maintenance requirements & Planned UMP and Production Visit Work Orders
Planned repair orders
Rebuildable activities, WOs, and Forecasted WOs
Historical and projected fleet sizeHistorical and projected fleet utilization
Historical visits and usage
Planning factors
Historical EAM usage
Resource utilizationTotal costNon-UMP visit forecast
History for non-maintenance products
ASCP plan results (material and
resource requirements)
Total material requirements Demand variability
Service levelsBudgetsTarget SS
Time phased SS
Forecast for non-maintenance products
Planned orders
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Schedule around preventative maintenance
Analyze key performance indicators
Analyze maintenance schedule exceptions
Analyze critical path
Maintenance scheduler workbench
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Development Roadmap
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Recent Updates and Future PlansService and Maintenance Planning
2012 2013 2014
Asset Intensive Planning Material planning for complex maintenance Asset material planning for equip maintenance Maintenance detailed scheduling (critical path) Long term maint forecasting tied to fleet fcstInventory Optimization Warehouse capacity
Service Parts Planning Sourcing priorities for inventory
rebalancingService Planning Analytics (APCC) Performance enh (archive plan)Inventory Optimization Category level service level targets Unified planning and analytics Extreme intermittency enh
In-Memory applications R2Front port of 12.1.3.9Front port of Dem 7.3.1.5Technology upgrades
Asset Intensive Planning Aggregate work order support
Service Parts Planning Reserve safety stock
Service Parts Planning (candidates) Maximize repair vs. demand
lateness tradeoff Replenish before rebalancing… and more
12.1.3.7 and Demantra 7.3.1.3
12.1.3.8 and Demantra 7.3.1.4 VCP 12.2.4
12.1.3.9 and Demantra 7.3.1.5 VCP 12.2.2.3.1
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Case Study
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Oracle Internal Implementation
Oracle Hardware Support Overview Implementation footprint Service Supply Planning Process Benefits Achieved Lessons Learned Looking Forward
Deploying Value Chain Planning for Hardware Spares
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Oracle Systems Support Overview
167 product lines– 17K unique spares
– 376 spares Inventory Organizations
– 2.6M item-org combinations
285 physical warehouses 4600 employees in Systems Support $2.4B systems Support Revenue
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LockbourneLeipzig
Singapore
Miami
Oracle Spares Warehouse Distribution
T2 - 7T3 - 76
T1
T1
T1
T1
T2 - 11T3 - 15
T2 - 83T3 - 58
T2 - 17T3 - 54
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Inventory Organization Structure
Tier Description Planned
Tier 1 Distribution Center SPP in VCP
Tier 2 Country Warehouse SPP in VCP
Tier 3 Local Warehouse SPP in VCP
Tier 4 Unmanned Warehouse Min-Max
Tier 5 Managed On -Sites Min-Max
Tier 6 Field Technicians Spares Management
Tier 7 Repair Vendors
Tier 8 Scrap Agents
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Disparate, local planning, procurement, stocking and repair processes
Disjointed view of inventory levels, purchasing activity and delivered level of service
Focus on Service as a profit center
Implement a single, global VCP solutionSingle source of truthUtilize intelligent forecasting, optimized
stocking strategies to drive lowest cost of operations while increasing level of service
Business Challenges Solution
Oracle Spares Planning with VCPRight Part, Right Place, Right Time at the Right Cost
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Value Chain Planning
Oracle Hardware Spares Supply ChainVCP Footprint
Advanced Planning
Command Center
CollectionsItems/BOMs
Sourcing RulesPurchase Orders
Repair OrdersShipmentsSuppliers
CustomersOrder Types
Demand ClassOrganizations
InventoryLocationsContracts
Supersessions
E-Business Suite - Global Single Instance
Service Parts Planning
OrdersBuy
RepairTransfer
DemantraDemand
Management
Inventory Optimization
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Planning Calendar
Monthly
• Statistical Forecast
• Leading Indicator Forecast
Weekly
• Rebalancing• Inventory
Optimization• Weekly Sub-Set
Daily• Collections• Regional Plans• APCC Refresh
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Key Success Factors
Shared vision and cross-functional executive sponsorship Invest in process governance Define global, standard process Align business process with application technology Data validation & migration Change management
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Reverse Supply Chain Transformation
Spare parts inventory $800 million to $400 million MAPE improved by 20% , BIAS down to single digits Backorders reduced by 50% , Service level @ 90+% Risk pooling used in Inventory Optimization
– $20M reduction in spare parts safety stock
Improved collaboration across Support organization Better decisions based on a single source of truth
Results
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Looking Forward
Differentiated Stocking Strategies– Rationalize placement of non-critical spares to maximize risk pooling
– Focus on high value, critical spares close to point of use
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Oracle Value Chain Summit
February 3-5, 2014 – San Jose McEnery Convention Center Hands-on workshops, solutions demonstrations & more than 200
sessions on topics in 6 complementary solution areas: Product Value Chain, Manufacturing, Enterprise Asset Management, Logistics, Planning & Procurement
Early bird registration opens soon – www.oracle.com/goto/VCS14
Empowering the Modern Value Chain
Explore How New Solutions Within Social, Mobile, Analytics & the Cloud are Helping Companies Transform Supply Chains into Modern Value Chains
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