How Data-Driven Supply Chain Innovation Enabled a Global Sportswear Leader to Boost Full Price Realization and Operational Efficiency

Client Overview

A global leader in athletic apparel, footwear, and equipment, operates one of the most complex supply chains in retail, spanning factories, distribution centers, and retail stores across continents. The brand processes millions of transactions daily and must balance demand variability, logistics complexity, and customer experience at scale.

The Ask

The client was looking to redesign its supply chain to become more intelligent, adaptive, and real-time. The primary goals were to improve demand-supply matching, optimize freight and carrier usage, and eliminate inefficiencies in inventory and order tracking.

Key Challenges

• Inaccurate demand forecasting led to frequent stock imbalances, missed revenue opportunities, and over- or under-supply across regions.
• Limited visibility into distribution center performance hampered the client’s ability to assess efficiency, throughput, and sustainability efforts.
• Inefficient freight and carrier matching increased logistics costs and delayed shipments due to inaccurate shipment forecasts.
• Manual, decentralized inventory and store data made it difficult to quickly assess stock levels, performance metrics, and product flow.

Our Solution: Data-Powered Supply Chain Transformation

Tiger Analytics implemented a series of targeted, scalable analytics solutions designed to address the
client’s most pressing supply chain pain points. The engagement covered six key areas:

1. Dynamic Order Allocation to Match Supply with Demand

Built a real-time, data-driven allocation model to optimize inventory flow based on demand signals, account priority, and regional needs, reducing overstocking and improving fulfilment speed.

2. Distribution Center(DC) Reporting and Performance Visibility

Established a reporting infrastructure with 50+ data objects and 3 dashboards to track throughput, processing times, and sustainability metrics, enabling real-time DC performance monitoring

3.Freight Demand Prediction for Optimized Logistics

Developed a predictive model to assess lane-level shipment capacity, improving carrier selection and on-time delivery. Air freight forecast accuracy improved by +36 percentage points.

4. Real-Time Store Performance and Inventory Monitoring

Centralized fragmented data into a unified dashboard system to track store metrics like sales velocity and stock turnover, enhancing planning and forecast accuracy.

5. Supply Chain Simulation Platform for Risk Planning

Built a simulation platform to model 80+ operational scenarios across 10 million orders, supporting proactive risk planning and more precise policy decisions.

6. Improved Shipment and Carrier Analytics

Deployed 10+ Cognos packages and ad-hoc dashboards to improve visibility into shipments, missed capacity, and surcharge calculations, strengthening carrier performance oversight.

Impact Delivered

• 4.5% Increase in Full Price Realization (FPR) for top-selling SKUs due to improved stock placement and reduced markdowns
• ~1,500 sales orders/day processed in North America and ~4,000/day in EMEA with streamlined order allocation and fulfilment
• 50+ data objects and 3 DC dashboards deployed to improve inventory flow and enable sustainability monitoring
• +98 pp improvement in simulation accuracy for Stock Transfer Order (STO) breadth and +36 pp for air freight forecasting
• 10 million orders modelled through simulations to evaluate risks and refine logistics planning
• Predictive freight modelling reduced carrier mismatches and helped the client secure more favourable contract terms
• Centralized inventory pipeline eliminated manual tracking, enabling real-time decision-making and reducing time spent on reconciliation
• Carrier and delivery insights helped the client identify missed opportunities and optimize shipment costs