AI-poweredSupplyChainControlTower
One view across suppliers, plants, warehouses and demand, built on the systems you already run.
Manufacturers usually hold the data they need to see supply risk early. It sits in ERP, MES, WMS, TMS and supplier files, each with its own identifiers and refresh cycle. The Control Tower connects those sources, shows how a delay travels through your network, and lays out the options before anyone has to choose.
Trusted by
Supply chain and data engineering expertise, applied to your network
N-iX Control Tower reads data from the systems you run today, maps products, BOM components, suppliers, sites, orders and shipments to one another, and shows delays, shortages and bottlenecks next to the demand and inventory they affect.
The work draws on N-iX experience in data engineering, cloud architecture and enterprise analytics. The proposed data platform is Snowflake on AWS, subject to an architecture review with your team.
The Control Tower observes, simulates and recommends. When a user selects an option, it can send a structured action request to your ERP, procurement or workflow system. Orders, approvals and corrective actions stay in your ERP, MES, WMS, TMS and procurement systems, and your people make the decisions. You can start with one module and add others when the data and the business case are there. N-iX builds it on a proven accelerator base and hands it over as your own system: no licence fees, and the source code stays with you.
Tower
Control tower use cases for different teams
Supply chain and operations leaders
- See where the biggest risks and bottlenecks are.
- Find which products, sites or customers may be affected.
- Follow a delay to its downstream impact.
What the Control Tower includes
Network visibility.
A multi-level view of suppliers, shipments, plants, warehouses and markets, with network health, delays, bottlenecks and the affected nodes or flows.
Supplier intelligence.
A dedicated subpage with supplier tiers, supplied materials and components, performance, lead times, shortage exposure, carbon indicators and data completeness. Requests, corrections and approvals stay in procurement systems.
Shortage prediction.
Current and predicted material shortages from demand, inventory, supply, BOM and lead-time data, with the downstream products each one affects.
Lead time and MOQ analytics.
Contracted, declared and observed lead times and minimum order quantities side by side, showing where planning assumptions do not hold.
What-if simulation.
Response options such as stock transfer, expedited transport or changed production timing, tested across demand, inventory, suppliers, logistics and emissions, each shown with its assumptions, data used, effect on lead time and inventory, and confidence. Cost and estimated emissions appear where the data exists.
Action handoff.
The selected option is passed as structured data to the relevant execution system. Validation, approval and execution stay there.
Cross-module context.
With Demand Planning, Inventory and Warehouse Intelligence and Carbon Emission Monitoring enabled, one issue is seen with its demand, stock and carbon context.
Control Center
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Four principles shape the platform. It integrates with your systems instead of replacing them. It watches and explains before anything is executed. It shows which data a result rests on and how complete that data is. It grows from one module to several without a redesign.
layers from source data to the user: integration, common data foundation, intelligence, business experience
steps from signal to action: detect, contextualise, assess impact, simulate and compare, decide and hand off
sites the platform is designed to handle
Addressing key supply chain challenges with a connected control tower
Fragmented data landscape
Supply chain data sits in ERP, MES, WMS, TMS, supplier systems, local applications and documents. Teams spend significant time collecting and reconciling it, and different functions work from conflicting views. The Control Tower gives them one analytical view without replacing the systems the data comes from.
Limited visibility across the whole chain
Teams can watch their own process but not how demand, inventory, production, suppliers and logistics affect one another. The Control Tower links products, BOM components, sites, suppliers and supply chain stages, so a delay can be followed to what it touches.
Risks that surface late
Delays, shortages and capacity constraints often show up only after they have hit production or customer demand. Trends, thresholds, forecasts and anomaly detection flag them earlier and rank them.
Little visibility beyond direct suppliers
Many organisations see only part of the supplier network and struggle to connect performance, quality, lead time and component dependencies. The supplier subpage combines tiers, performance indicators, BOM dependencies and data completeness, and says where supplier data is missing.
Benefits of a supply chain control tower
For the business:
- Faster identification and prioritisation of supply chain risks
- Clearer view of dependencies and downstream impact
- Less manual work collecting and reconciling data
- Earlier visibility of supply gaps and constraints
- KPIs that mean the same thing across functions
- Scenarios and trade-offs compared before a decision
- The chosen action passed to the execution system without re-keying
For planners, buyers and warehouse teams:
- A dashboard prioritised for their role, with items that need attention listed first
- Drill-down from an alert to the product, supplier, site or shipment behind it, with context kept
- Each result labelled confirmed, calculated or predicted
- Data freshness and missing data shown
- Decisions that stay with them
FAQ
A supply chain control tower is one analytical view of your supply chain. It pulls data from the systems that run it, such as ERP, MES, WMS and TMS, and shows how suppliers, shipments, plants, warehouses and demand depend on one another. When something goes wrong, for example a shipment is likely to arrive late, it shows which products and orders are affected and what the options are. It can simulate those options and pass the one you choose to the execution system. Each result is marked confirmed, calculated or predicted.
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