EVERNILE

Predict Demand for Business Planning

“History doesn’t repeat itself, but sometimes it rhymes”

- Leverage Advanced Forecasting to Estimate Future Demand, learning from Past Trends and Market Dynamics

The Approach

Making it Happen

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To address the demand prediction challenge, the optimal strategy involves integrating time series forecasting and sophisticated machine learning models.

This approach entails a thorough examination of historical data, market dynamics, and customer behaviours to construct a resilient demand prediction model. This model takes into account a myriad of factors impacting demand, including seasonality, the effects of marketing campaigns, and the influence of external events.

Once crafted and verified for accuracy, the demand prediction model must seamlessly integrate into downstream planning processes. This encompasses aligning production schedules, optimizing supply chain logistics, and refining inventory management in accordance with the forecasted demand. In addition, real-time monitoring against predictions ensures adaptability to evolving market conditions, fostering agile decision-making.

For an ecommerce fashion retailer, we developed a sales demand forecasting model, with an accuracy of ~97%. Providing insights into drivers like discounting and marketing spends, it empowered the Growth Team to take intraday corrective actions based on real performance versus the plan. Additionally, it influenced downstream warehouse planning for a synchronized approach.