Business Domain: Retail
Problem Statement: The retail company is experiencing a decline in sales and wants to analyze sales data to identify trends, optimize product offerings, and improve overall revenue.
Domain-Specific Requirements:
- Analyze historical sales data by product category, location, and time period.
- Identify seasonality and trends in sales.
- Optimize inventory management to reduce stockouts and overstocking.
- Improve sales forecasting accuracy.
- Incorporate data from customer loyalty programs and social media sentiment analysis.
- Implement a recommendation engine based on customer purchase history.
- Utilize IBM Cognos Analytics’ AI-driven features for automated insights generation.
Solution Provided:
- Utilized IBM Cognos Analytics for comprehensive data visualization and analysis.
- Integrated data from POS systems, inventory databases, and external market data sources.
- Developed interactive dashboards and reports for real-time sales tracking.
- Implemented advanced analytics algorithms to predict future sales trends.
Technical Tools Used:
- IBM Cognos Analytics
- SQL for data extraction
- Python for predictive analytics
Achievements:
- Increased sales by 12% within the first year.
- Reduced inventory holding costs by 15%.
- Improved sales forecasting accuracy by 20%.
