Food Distributor Saves $100M+ with AI Demand Forecasting

Due to the pandemic, a leading food distributor struggled with inaccurate demand forecasting, supply chain disruptions, and inefficient inventory management. They implemented an AI solution that combined internal sales and inventory data with external factors like weather and restaurant reservations.This allowed for more accurate forecasts, real-time insights, and improved planner efficiency.

Problem Statement:

A leading food distributor grappled with:
● Inaccurate Demand Forecasting: Traditional methods failed to adapt to pandemic disruptions.
● Supply Chain Disruptions: Stockouts, lost sales, and increased costs due to unpredictable demand.
● Limited Visibility and Flexibility: Inability to pivot and adapt to changing demand patterns.
● Inefficient Inventory Management: Excessive or insufficient inventory levels leading to costs and lost sales.
● Overwhelmed Planners: Manual data analysis hindering focus on critical tasks.

Results:

☑️ $100-$130 million in savings through inventory cost reduction and lost sales recovery
☑️ 6-8 point reduction in forecast errors.
☑️ Improved supply chain resilience through real-time insights and adaptation to changing demand patterns.
☑️ Enhanced planner efficiency by automating time-consuming data analysis.

AI Solution:

Driven by the need to navigate COVID-19 disruptions, a leading food distributor sought a more innovative approach to demand forecasting. The company implemented an Accenture solution called Unified Demand Sensing. This AI-powered system went beyond traditional methods that relied solely on historical data.

How the AI solution worked:

● Combined Data Sources: Unified Demand Sensing integrated the company’s internal data (sales, inventory) with new external data sources (weather, restaurant reservations). This broader data pool allowed for a more comprehensive understanding of demand drivers.
● AI-driven Analysis: By analyzing the comprehensive dataset, the AI engine identifies key patterns and trends, empowering highly accurate demand predictions.
● Real-time Insights: The solution provided near real-time insights, giving the distributor the agility to adapt their supply chain to changing market conditions.

By implementing this AI-powered approach to demand forecasting, the food distributor overcame the limitations of traditional methods and gained a competitive advantage in a disrupted market.

References:

1. A forward-looking supply chain using demand forecasting

Industry: Wholesale Food Distribution
Vendor: Accenture
Client: Wholesale Food Distributor