Restaurant Order Preparation Time

Requirements Clarification & Assessment

• Objective:

  • Develop a predictive model to estimate the order preparation time in a restaurant, from order receipt to readiness for delivery.

• Key Questions:

  • Are we predicting preparation time for a specific type of cuisine or multiple cuisines?
  • Is the model intended for a single location or multiple restaurants?
  • How accurate does the prediction need to be? Is there a tolerance for error?
  • What is the priority between accuracy and interpretability of the model?
  • Are there any data privacy concerns or restrictions?

• Data Requirements:

  • Historical Order Data: Includes order details, preparation time, and timestamps.
  • Restaurant Operational Data: Number of staff, kitchen size, equipment, and layout.
  • External Factors: Day of the week, time of day, special occasions, holidays.
  • Customer Data: Order size, type, and complexity.

• Potential Challenges:

  • Variability in preparation times due to human factors (e.g., chef experience).
  • Missing or incomplete data for certain predictors.
  • Non-linear relationships between features and preparation time.