Supply Chain Management System
End-to-end supply chain visibility platform with AI-driven demand forecasting and automated procurement, achieving 35% cost reduction across logistics operations.
Project Background & Objectives
Multinational Logistics Corporation manages freight and warehousing for 420 enterprise clients across 18 countries. When they engaged Dristi Technologies, their supply chain visibility was a patchwork of 12 ERP systems, 4 TMS platforms, and a small army of operations staff manually consolidating reports in Excel every morning. Procurement decisions were made 72 hours after demand signals arrived — too slow to avoid emergency airfreight costs when disruptions occurred. Our solution gave Multinational Logistics Corporation a real-time unified control tower with AI-driven disruption prediction and automated procurement triggers that reduced their clients' total logistics spend by a third.
Supply chain optimisation is fundamentally a data latency problem. When demand signals, inventory positions, and logistics capacity all live in the same real-time system, the decisions that previously required human committees happen automatically — and they happen in seconds, not days.
What Problem Were We Solving?
Multinational Logistics Corporation operated across 12 incompatible ERP systems — a result of 7 acquisitions over 9 years — with no unified data model or real-time visibility layer. Their largest client experienced 23 emergency airfreight events in 2023, each costing 6–8× the standard freight rate. Demand forecasting was manual, resulting in 34% average excess inventory and frequent stockouts on fast-moving SKUs simultaneously. A new competitor was pitching real-time visibility as a standard offering, threatening 30% of Multinational Logistics Corporation' revenue base if they couldn't match it within 18 months.
How We Delivered Results
We built a cloud-native supply chain control tower on Azure with a unified data ingestion layer connecting all 12 ERPs via a standardised API adapter framework. An AI forecasting engine trained on 5 years of client demand data predicts stockouts and demand spikes 21 days in advance with 91% accuracy. Automated procurement workflows trigger PO creation when inventory falls below dynamically calculated safety stock levels. A real-time disruption monitor aggregates port status, weather, geopolitical alerts, and carrier performance data to flag supply-chain risks before they become emergencies.
Mapped all 12 ERP systems, designed a canonical data model, and built an adapter framework that normalises data from each source into a unified real-time event stream without modifying source systems.
Trained vertical-specific demand forecasting models on 5 years of historical data, achieving 91% 21-day forecast accuracy across 14 product categories before production rollout.
Built the unified operations dashboard, automated PO generation workflows with approval gates, and integrated the disruption monitor pulling from 200+ real-time data feeds.
Ran a 12-week change management programme for 680 operations staff, transitioned 18 client accounts to the new platform, and established a Customer Success function to maximise adoption.
Built With Industry-Leading Tools
Every technology was selected for its production readiness, scalability potential, and fit with Multinational Logistics Corporation's long-term roadmap.
In Their Own Words
“Our operations team used to start every morning reconciling 12 different reports. Now they open one screen and see everything — in real time. When a port disruption hit the Red Sea last quarter, our system flagged it and rerouted four client shipments automatically before any human even saw the news.”
Results That Speak for Themselves
Quantifiable impact delivered for Multinational Logistics Corporation across every key performance dimension.
Full List of Outcomes
How We Deliver Enterprise-Grade Projects
A proven four-phase framework that consistently delivers on time, on budget, and above expectations.
Discovery & Scoping
Stakeholder workshops, existing system audit, user research, and definition of success metrics with all key decision-makers.
Architecture & Design
System architecture blueprint, UX/UI wireframes, API contracts, and technology stack validation against scalability requirements.
Agile Development
Two-week sprint cycles with CI/CD pipelines, automated test coverage, and weekly demos to ensure continuous alignment.
Launch & Optimise
Zero-downtime deployment, real-user monitoring, performance tuning, and a dedicated hypercare period with SLA guarantees.
