Clucking into the Future: A Data-Driven Strategy for Sustainable Growth at Chicken Coop
- Event: Trilytics '24 Analytics Case Competition, organized by the PGDBA Conclave (IIM Calcutta, IIT Kharagpur, and ISI Kolkata)
- Team Name: AnalySIS
- Team: Nithyashree M, Krupa P Nadgir, Lekhana A, Manaswini Simhadri Kavali, Ranjana Prabhudas
- Retail businesses struggle with unpredictable sales patterns, leading to inefficient inventory management and lost revenue.
- Traditional sales forecasting methods fail to account for seasonality, promotions, and external factors affecting demand.
- Lack of accurate demand prediction results in stockouts, overstocking, and suboptimal resource allocation.
- Businesses require an automated, data-driven forecasting system to improve sales planning and operational efficiency.
- Existing forecasting models lack integration with strategic decision-making for marketing, staffing, and pricing.
- Demand forecast: To develop predictive models that forecast sales in a dynamic environment
- Finding seasonal patterns: Identifying the periodic variations of the sales-driven economy with trend analysis.
- Location-based business outcome optimisation: Analysing the correlation between business outcomes/sales performance with the geographic location for personalised and strategic business expansion in optimal regions
- Suggesting market-based promotions and marketing: Inspecting the effect of marketing and promotional activities of the firm on the general public and suggesting improvement through data analytics.
Ensemble Model (SARIMAX + XGBoost): Predicts sales for the next 3 months using historical sales data and promotional information.
Evaluates the impact of location attributes (city, DMA, region) on sales performance. Identifies high-performing geographic areas for potential business expansion.
