Recognised Leader in Supply Chain –
Specialty Analytics and AI Services
by ISG

This ranking reflects Tiger’s leadership in AI- powered Supply Chain analytics. Sustaining the top position in a year that ISG described as highly competitive, against strong challenges from peers, signals that Tiger’s solution portfolio, delivery excellence, and value impact are structurally strong while being agile to client needs.

Today’s supply chain problems need NextGen solutions that address two priorities simultaneously – preserving and evolving what already works, while transforming and modernizing for what comes next. Tiger’s unique approach blends both, overcoming cross-functional challenges in existing investments alongside building new AI-powered end-to-end capabilities for a resilient supply chain.

Silos in data, processes, and people stem from fragmented tech stacks, disconnected systems, and functions operating at different maturity levels. Tiger addresses this through a layered approach, unifying data via custom enterprise data foundations and supply chain data models, then building interoperable data products that create a shared intelligence layer across functions. The result is a coherent strategy where every building block supports the next.

Most pilot-to-production failures are design problems, not talent problems. Tiger embeds productionization from the start, with a Supply Chain Intelligent Data Platform that handles governance, data quality, and domain-context-aware ingestion, ensuring models have the reliable foundation they need to operate at enterprise scale. Intelligent Supply Chain Agents then extend this with structured autonomous execution across the value chain, making production-scale AI the baseline.

While analytical capabilities in supply chains are advancing rapidly, decision-making maturity is not evolving at the same pace. Research indicates that 75% of analytics work happens outside the model: defining the right business question, stress-testing assumptions, translating outputs into operational reality, and aligning cross-functional teams before recommendations reach leadership for change management. Tiger addresses this gap by embedding decision discipline throughout every engagement, ensuring analytics translate into business decisions and measurable outcomes, rather than simply producing reports.

Tiger’s Mission AI approach starts with a clearly defined business outcome, aka mission, and works backwards. Each mission is decomposed into focused sub-missions, assigned to cross-functional agent clusters that work concurrently across the value chain. At key steps, humans remain in the loop to validate critical choices and capture the rationale, turning a business goal into a coordinated, outcome-driven plan rather than a process map.