Case Study — Supply ChainManufacturing

End-to-End Supply Chain Visibility for a Multi-Site Manufacturer

Supply ChainInventoryProcurementLogisticsRiskForecastingAI
Real-time
Demand & Supply Visibility
4 Variables
Scenario Simulation Engine
AI-driven
Risk Reduction Recommendations

The Challenge

The client sourced components from dozens of suppliers across multiple geographies with no unified view of demand, inventory, or supplier performance. Planners worked from weekly spreadsheet exports, meaning supply decisions were always based on stale data. Demand spikes from key customers went undetected until stockouts occurred. When a supplier was late or unreliable, the team had no pre-qualified alternates to fall back on — leading to expensive emergency freight and expedite orders. The cost of supply chain disruptions was growing but was never quantified, making it difficult to justify investment in better tooling.

The Solution

We built a supply chain management platform with a scenario simulation engine at its core. Planners can adjust demand spike, lead time buffer, supplier reliability, and logistics delay parameters in real time and immediately see the downstream impact on supply coverage, at-risk parts, and total cost exposure. A supplier risk matrix scores each supplier across reliability, lead time, and geographic risk. An inventory coverage module shows days-on-hand per part against a projected demand curve. The cost impact breakdown quantifies expedite, premium sourcing, stockout, and emergency freight exposure for any given scenario. An alternate sourcing module maintains a qualified supplier bench with status tracking so the team always has a fallback ready. AI-generated recommendations surface the highest-leverage actions to reduce risk score before a disruption materialises.

Core Capabilities

Demand vs Supply Forecasting

Rolling demand forecast plotted against available supply — with configurable demand spike modelling for scenario planning

Supplier Risk Matrix

Supplier scoring across reliability, lead time, and geographic risk with real-time risk score timeline

Inventory Coverage Analysis

Days-on-hand per part against projected demand, with at-risk part flagging and reorder point alerts

Cost Impact Modelling

Quantified breakdown of expedite costs, premium sourcing, stockout exposure, and emergency freight for any scenario

AI Recommendations

Automated prioritised action list to reduce supply risk score before a disruption occurs

Alternate Sourcing

Pre-qualified supplier bench with QA status tracking so fallback options are always ready to engage

Logistics Delay Modelling

Configurable logistics delay risk factor propagated through all forecasts and cost estimates

ERP Integration

Bi-directional sync with existing ERP for live order, inventory, and procurement data

See it in action

Explore the interactive mockup — live data, full navigation, all modules.

Open Demo