Client Background: A leading consumer packaged goods manufacturer with operations across 15 US states struggled with demand forecasting accuracy, resulting in frequent stockouts and excess inventory. Their traditional forecasting methods failed to capture rapid market changes and seasonal fluctuations effectively.

Challenge: The client faced 60% forecast accuracy rates, leading to $3.2 million in annual inventory carrying costs and 15% stockout rates during peak demand periods. Manual data collection from multiple retail partners consumed excessive resources while providing outdated insights.

Solution: We implemented comprehensive data extraction from major quick commerce platforms including Instacart, Amazon Fresh, and regional grocery chains. Our AI-powered analytics platform integrated real-time sales data, inventory levels, promotional activities, and external factors like weather patterns and local events.

Results: Achieved 85% forecast accuracy improvement, reducing inventory carrying costs by 30.6% while improving product availability to 99.1%. The client eliminated $1.4 million in lost sales quarterly and increased customer satisfaction scores by 18% within six months.

Client Testimonial: “Hir Infotech’s data intelligence platform transformed our entire supply chain strategy. We now predict demand spikes weeks in advance, enabling proactive inventory management that our competitors simply cannot match.”