A Global Consumer Goods Leader Reduced Operating Costs by 55% Using Cloud-Native Data Platform
Overview
A global consumer goods leader operating in 180+ markets needed to unify fragmented warehouses, control rising costs, and deliver real-time insights for compliance, sales, and customer behaviour. Local ecosystems had created silos, duplication, and inconsistent governance - slowing decision-making and exposing regulatory risks.
The client faced significant challenges in achieving unified, compliant, and timely insights across its global operations due to fragmented data ecosystems and disconnected governance practices. Expanding on the same below:
Fragmented data products and ingestion pipelines across regions created siloed, inconsistent insights.
Disparate teams and disconnected systems led to conflicting views of performance, compliance, and market data.
Absence of a centralized, trusted data foundation caused delays in decision-making and innovation.
Teams spent weeks reconciling data, slowing product launches and compliance reporting.
Duplicate data products across markets inflated operational costs and reduced efficiency.
Rigid, one-size-fits-all processes limited scalability and adaptability for high-value initiatives.
Data quality monitoring and regulatory adherence were complex and error-prone at a global scale.
Risk of higher costs, slower speed-to-market, and lost innovation opportunities compared to data-mature competitors.
Solution
To address these challenges, Coforge implemented a unified, cloud-native data platform that modernized the client’s data ecosystem, automated critical workflows, and enabled faster, more trusted insights across global operations.
Solution Highlights
Built a unified, cloud-native data platform on Snowflake and AWS, consolidating global data products into a single, trusted ecosystem.
Enabled federated governance and real-time integration for consistent, compliant insights across 180+ countries.
Deployed AWS Glue, Kafka, and Lambda to automate ingestion, streaming, and processing.
Introduced domain-driven workflows and AI-powered quality checks to enhance autonomy and accuracy.
Delivered Power BI dashboards for real-time visibility into cost, usage, and SLA performance.
Adopted an agile, iterative rollout supported by structured change management and a global data champions network.
To tackle the mammoth task of data classification and governance, we deployed an AutoClassifier powered by AI/ML models. It automated metadata tagging, PII identification, and classification across C1–C4 levels and reduced manual effort dramatically while introducing Human-in-the-Loop (HITL) validation for accuracy.
The Impact
The solution delivered a measurable business impact:
360° Customer View: Unified data across markets enabled hyper-personalized insights and stronger customer engagement.
35% Faster Turnaround: Automation and deduplication improved efficiency, allowing more data products to be managed with existing resources.
Real-Time KPI Visibility: Leadership gained instant access to performance, cost, and compliance metrics for proactive decision-making.
55% Lower Operating Costs: Optimized Snowflake usage and automated governance reduced costs by over half, unlocking substantial annual savings.
Enhanced Data Confidence: Reliable, real-time insights boosted adoption and decision accuracy across global teams.
Future-Ready Platform: Cloud-native, federated architecture positioned the client for AI, predictive analytics, and scalable innovation.
