Topic: Nilofer

Shashank from Mumbai presents a challenge for AI in production planning for food outlets, specifically Nilofer at Hyderabad airport. Traditional planning based on historical data (year-on-year, day-to-day) is insufficient due to dynamic factors like flight schedules and events, leading to 30-40% errors. The problem is correlating airport traffic inflow with sales to predict demand, requiring real-time consumption data which is difficult to obtain.

Estimating airport footfalls for production planning is challenging due to the lack of direct data. A proposed AI solution involves using "Flight Price Watcher" via APIs to monitor real-time flight ticket prices. An increase in prices correlates with increased demand and passenger inflow, signaling a need for higher production. This dynamic approach can be further enhanced by incorporating weather data and sentiment analysis to find additional correlations.