CASE STUDY

AI/ML for Inventory and Sales Optimization

Data-Driven Inventory Management & Sales Forecasting

Client: Flemiongo International
Industry: Retail (FMCG Products)
Project: Inventory & Sales Optimization

Project Overview

Flemiongo International, a leading retail business specializing in FMCG products, faced significant challenges in managing their inventory efficiently. Their manual processes led to issues such as stockouts, overstocking, and product wastage due to expiration. To address these challenges, Intium Solutions implemented a comprehensive AI and Machine Learning solution to optimize stock levels, predict demand patterns, and automate inventory reporting processes.

Objectives

  • Implement interactive visualizations for gaining insights into SKU performance and stock levels.

  • Develop AI-powered forecasting systems to predict future sales trends and optimal reorder quantities.

  • Automate inventory updates and reporting to reduce manual effort and human error.

  • Track product shelf life to minimize wastage of perishable items.

  • Provide actionable insights for procurement decisions and sales strategies.

Implementation

Visualization

  • Power BI dashboard with interactive SKU performance visualizations.

  • Fast vs. slow-moving product identification for inventory optimization.

  • Seasonal SKU trend analysis for demand fluctuations.

  • Shelf life calculations and expiry tracking for perishable items.

  • Historical sales trends and profit margin analysis.

Forecasting Model

  • Custom AI/ML model for sales trend prediction using historical data.

  • Optimized reorder points and quantities to reduce stockouts.

  • Demand forecasting with consideration for seasonal factors.

  • Inventory recommendations with automated procurement alerts.

Automation

  • Power Automate integration for automated data updates.

  • Daily email reports with order insights and sales projections.

  • Automated alerts for stock threshold levels.

Documentation & Training

  • Comprehensive user guide for Power BI dashboard navigation.

  • Technical documentation for maintaining the forecasting model.

  • Instructions for managing automation flows and alerts.

  • Staff training sessions for optimal system utilization.

Development Approach

Technology Stack

Power BI Power Automate Python TensorFlow Azure ML

User Roles & Access Control

Executives, Store Managers, Inventory Team, Procurement, and Sales Staff.

Data Integration

Connected with existing POS systems, inventory databases, and external market trend data.

Deployment Approach

Phased roll-out with continuous feedback loops for model refinement and dashboard optimization.

Results & Impact

Reduced Wastage

20%

Decrease in stock wastage through better shelf-life tracking

Inventory Optimization

15%

Reduction in overall inventory holding costs

Forecasting Accuracy

92%

Prediction accuracy for demand forecasting

Time Savings

25+

Hours saved weekly through automated reporting

Conclusion

The implementation of AI and ML-powered solutions transformed Flemiongo International's inventory and sales management processes. By leveraging data-driven insights, the company achieved significant improvements in operational efficiency, cost reduction, and decision-making capabilities. The system continues to learn and improve over time, adapting to changing market conditions and consumer preferences.

Future Enhancements

Customer purchase behavior analysis for personalized marketing

Store-level optimization with geospatial analysis

Mobile app for real-time inventory management on-the-go