Retail | Supply Chain, Logistics & Transportation
Supply Chain Forecasting
Objective
The client faced significant challenges in accurately forecasting product demand, leading to overstocking or stockouts, increased holding costs, and lost sales opportunities. The goal was to enhance demand forecasting accuracy to optimize inventory levels, reduce costs, and improve customer satisfaction.
Challenges
- High variability in customer demand due to seasonal trends and promotions.
- Complexity in managing a large number of SKUs across multiple locations.
- Inadequate historical data and traditional forecasting methods were leading to inaccurate predictions.
- Integrating diverse data sources such as sales, weather, and social media trends.
Solution Proposed
- Implemented a deep learning model, specifically Long Short-Term Memory (LSTM) networks, to capture temporal dependencies and trends in historical sales data.
- Integrated weather pattern and seasonal data and utilized Natural Language Processing (NLP) for analysis.
- Leveraged PBI to visualize demand forecasts.
- Engineering efforts were utilized for seamless data integration while ensuring data quality.
Outcome
- Improved demand forecasting accuracy by 20%, reducing overstocking and stockouts.
- Reduced inventory holding costs, leading to better stock management.
- Decrease in stockouts, improving customer satisfaction and sales.
Design & Thinking Wins
- Successful integration of deep learning models with existing IT infrastructure.
- Scalable solution capable of handling large datasets and multiple data sources.
- Customizable BI dashboards tailored to different user roles within the organization.
- Proven ROI through measurable improvements in supply chain efficiency and cost savings.
Disclaimer: The outline showcases the typical challenges, solutions, designs, and outcomes for industries and functions, in general, based on Affine’s prowess in the Industry. The outcomes would be much higher for specific clients as they would be based on their data and specific problems to be solved.
