SCM · Oracle Fusion Inventory · Demand Management · Supply Planning · AI Forecasting
Overstock and Stockout at the Same Time.
Oracle Fusion AI Ends Both.
The paradox of most supply chains is simultaneous overstock and stockout — excess inventory in the wrong locations while the right product is unavailable. This is not a demand problem. It is a visibility and planning problem. Oracle Fusion gives you real-time inventory positions and AI-driven demand signals that eliminate both. Symhas implements Oracle Fusion Inventory Management and Oracle Demand Management — multi-warehouse real-time on-hand, on-order, and in-transit visibility, AI demand sensing that improves forecast accuracy by 30–40%, and supply planning that responds to exceptions in hours, not days.
+33%Forecast accuracy improvement — 500-location retail chain, Oracle AI demand sensing, 12 weeks
↓21%Inventory holding cost reduction — same retailer, overstock eliminated by accurate demand signal
Real-timeOn-hand, on-order, and in-transit inventory position — across all warehouses simultaneously
12wkOracle Fusion Inventory and Demand Management — production deployment, fixed price
Oracle Fusion SCM specialists available now Active
+33% Average improvement in demand forecast accuracy after Oracle AI demand sensing deployment
↓21% Average inventory holding cost reduction after Oracle Fusion Inventory optimisation
Real-time Inventory position across all warehouses — on-hand, on-order, in-transit, reserved
12wk Oracle Fusion Inventory and Demand Management — production in 12 weeks, fixed price
What We Deliver
Core Capabilities.
Live in Oracle Fusion in 12 Weeks.
Every capability deployed inside Oracle Fusion SCM — connected to your Finance, Manufacturing, and Order Management modules. Fixed price. Fixed timeline.
Multi-Warehouse Inventory ManagementReal-time on-hand · Lot/serial · Subinventory · Transfers · Cycle counting
Oracle Fusion Inventory Management gives you a single real-time view of inventory across every warehouse, distribution centre, and stocking location — on-hand, on-order, in-transit, and reserved — with lot and serial number traceability where required.
Organisation and subinventory structure design — warehouses, locations, and zones
Real-time on-hand balance by item, lot, serial, and location
Lot and serial number control — full traceability from receipt to shipment or consumption
Inter-organisation transfers — warehouse-to-warehouse and manufacturing-to-distribution
Cycle counting and physical inventory — automated count schedules and variance approval
One inventory position the entire organisation trusts — no more reconciling between warehouse systems
AI Demand Sensing & ForecastingML forecasting · Demand signals · Seasonality · Promotions · Consensus plan
Oracle Fusion Demand Management applies machine learning to your sales history, POS data, market signals, and external factors to produce a demand forecast significantly more accurate than a statistical model — with a consensus planning process that incorporates commercial intelligence.
ML demand sensing — algorithms trained on your specific product and market patterns
External signal integration — weather, economic indicators, and market data feeds
Promotion and event lift modelling — forecast adjusted for planned promotions automatically
Consensus demand plan — commercial, operations, and finance views reconciled in one plan
Forecast accuracy measurement — MAPE and bias tracked at SKU, category, and location level
Demand signal 30–40% more accurate than statistical baseline — reducing both overstock and stockout
Supply Planning & Exception ManagementMRP · Replenishment · Safety stock · Constraint-based · Exception alerts
Oracle Fusion Supply Planning generates replenishment recommendations based on the demand plan, current inventory position, supplier lead times, and stocking policies — with exception alerts that surface only the decisions that require human intervention.
Replenishment planning — min/max, reorder point, and MRP-driven replenishment methods
Safety stock optimisation — dynamically calculated based on demand variability and service level targets
Constraint-based planning — supplier capacity, warehouse capacity, and budget constraints respected
Exception management — only items requiring intervention surfaced to planners
What-if scenario analysis — impact of demand or supply shocks modelled before commitment
Planners manage exceptions, not calculations — Oracle does the arithmetic, humans make the decisions
Inventory Optimisation & Cost ControlABC analysis · Slow-movers · Obsolescence · Carrying cost · Turns
Oracle Fusion Inventory analytics and planning tools identify excess inventory, slow-moving items, and obsolescence risk — giving inventory managers the intelligence to reduce carrying cost without compromising service levels.
ABC/XYZ analysis — automated segmentation of inventory by value and variability
Slow-moving and excess inventory identification — aged stock reporting with disposition recommendations
Obsolescence risk scoring — items at risk of expiry, supersession, or end-of-life
Inventory carrying cost modelling — total cost of inventory including capital, storage, and handling
Inventory turns target tracking — performance vs target by warehouse and category
Inventory investment optimised — capital freed from excess stock without increasing stockout risk
Delivery Model
Assessment to Production.
Your Team Independent at Go-Live.
Four structured phases with go/no-go gates at every milestone. Fixed price agreed before week one. Your SCM team runs the system independently from go-live day.
01
Inventory & Data Assessment Weeks 1–3 Current inventory accuracy audit. Warehouse structure design. Item master data quality assessment and cleansing plan. Demand history extraction and quality review. Forecast accuracy baseline established.
02
Inventory Configuration & Data Load Weeks 4–8 Oracle Fusion Inventory configured — org structure, subinventories, and item master. Lot and serial controls configured. Item data migrated and validated. Cycle count schedules configured.
03
Demand Management & Planning Build Weeks 9–10 Oracle Demand Management configured — ML models trained on historical data. Consensus planning process built. Supply planning parameters set. Safety stock optimisation configured.
04
Go-Live & First Planning Cycle Weeks 11–12 Production go-live. First live demand plan generated and reviewed. First replenishment recommendations processed. Forecast accuracy baseline measured. Supply chain team certified. Symhas moves to advisory.
Retail · Inventory & Demand Planning 500+ Location Retailer.
+33% Forecast Accuracy. ↓21% Holding Cost. 12 Weeks.
A national retailer with 500+ locations and 3 distribution centres was forecasting demand through a combination of spreadsheet models and buyer intuition, with a 5-day data lag from store POS to planning system. Forecast error averaged 41% across their top 200 SKUs. Inventory positions were reconciled manually from 3 systems. Symhas implemented Oracle Fusion Inventory Management and Demand Management — real-time POS data feeding ML demand sensing, replenishment recommendations generated automatically, and inventory positions unified across all 3 DCs and 500+ stores. Discuss Your Programme
+33%Forecast accuracy
↓21%Inventory holding cost
1 systemInventory position
12wkTo production
What was delivered Oracle Fusion Inventory & Demand Management — Retail Deployment
Oracle Fusion Inventory — 3 DCs and 500+ store locations on single real-time inventory platform
Item master migration — 48,000 active SKUs migrated with lot control and unit of measure conversion
Oracle Demand Management — ML models trained on 3 years of POS and store replenishment history
Promotion lift model — seasonal and planned promotional uplifts applied automatically to base forecast
Consensus plan — commercial, buying, and operations views reconciled weekly in Oracle
Replenishment automation — 85% of replenishment orders generated and approved without planner intervention
“Our buyers stopped fighting the forecast and started trusting it. When 85% of replenishment runs automatically and you only manage exceptions, you have time to actually think about the supply chain instead of just running it.” — VP Supply Chain, National Retail Group
Oracle Fusion Modules
The Oracle Fusion SCM Modules
We Configure for This Capability.
Every module configured to your industry, your product structure, and your supply chain complexity. Not a generic out-of-box deployment.
Oracle Fusion
Oracle Fusion Inventory Management Core inventory — real-time on-hand balances, lot and serial control, subinventory management, and inter-org transfers.
Organisation and subinventory structure
Real-time on-hand by item and location
Lot and serial number traceability
Cycle counting and physical inventory
Oracle Fusion
Oracle Fusion Demand Management AI demand forecasting — ML demand sensing, external signal integration, promotion modelling, and consensus planning.
ML demand sensing configuration
External signal integration
Promotion lift modelling
Consensus planning process
Oracle Fusion
Oracle Fusion Supply Planning Replenishment and supply planning — MRP, min/max, safety stock optimisation, constraint-based planning, and exception management.
Replenishment planning methods
Safety stock optimisation
Constraint-based planning
Exception management workbench
Oracle Fusion
Oracle Fusion Inventory Optimisation Inventory analytics and optimisation — ABC analysis, excess inventory, obsolescence risk, and inventory cost modelling.
ABC/XYZ segmentation
Excess and slow-mover identification
Obsolescence risk scoring
Inventory carrying cost modelling
Oracle Fusion
Oracle Fusion Item Master Central item repository — item definitions, unit of measure conversions, lead times, and sourcing rules.
Item definition and classification
Unit of measure and conversion
Lead time and sourcing rules
Item category and catalogue management
Oracle Fusion
Oracle Fusion SCM Analytics Supply chain dashboards — inventory turns, forecast accuracy, service level, and fill rate analytics.
Inventory turns and coverage
Forecast accuracy (MAPE, bias)
Service level and fill rate
Supplier lead time performance
Why Symhas
Oracle SCM Expertise From
45+ Enterprise Deployments.
ML Models Trained on Your Data, Not a Demo Dataset Oracle Demand Management ML models need to be trained and validated on your specific sales history, product structure, and market patterns. Symhas includes ML model training, validation, and accuracy baseline as part of the 12-week engagement — not a post-go-live activity.
Item Master Cleansed Before Go-Live Inventory accuracy depends on a clean item master. Symhas conducts item master data cleansing as part of every inventory engagement — duplicate items resolved, units of measure standardised, and lead times validated before the first replenishment run.
Forecast Accuracy Target Committed in Writing We agree a minimum forecast accuracy improvement target before the engagement starts. If the ML model does not meet the agreed accuracy improvement at the Week 10 checkpoint, we continue training and tuning within the fixed price.
Real-Time Inventory From Go-Live Day Inventory visibility means nothing if it takes 24 hours to update. Symhas configures Oracle Fusion Inventory for real-time transaction processing — on-hand positions update on every receipt, issue, transfer, and shipment, not on a nightly batch.
Connected to Procurement and Manufacturing Demand planning isolated from procurement lead times and manufacturing capacity produces plans that cannot be executed. Symhas connects Oracle Demand and Supply Planning to Oracle Procurement and Manufacturing — so every plan is constrained by what can actually be sourced and made.
Planners Managing Exceptions, Not Running Calculations By go-live your planning team is spending time on the exceptions Oracle flags — not on running models. Symhas targets 80%+ automated replenishment from go-live — human judgment applied to the 20% that genuinely needs it.
Next Step
Tell Us What Your Forecast Accuracy and Inventory Cost Look Like.
We Will Tell You What Oracle AI Can Do to Both.
A 30-minute Oracle SCM assessment with a Symhas supply chain specialist. We will review your current inventory position, forecast process, and demand data quality — and tell you what a 12-week Oracle Fusion Inventory and Demand Management engagement would deliver. No pitch deck. No sales process. An honest conversation about your Oracle SCM environment.