Iteration 1 Summary
Business Context: A movie streaming service aims to optimize the allocation of its promotional budget across various movies to maximize the expected improvement in their average ratings, considering budget constraints and minimum promotional requirements for each movie.
Optimization Problem: Determine the optimal allocation of a fixed promotional budget to different movies to maximize the expected increase in their average ratings. Each movie has a different sensitivity to promotional spending, and there are minimum promotional requirements for each movie.
Objective: maximize sum(promotion_sensitivity[mID] * budget_allocation[mID])
Tables Created: 2
Tables Modified: 0
Tables Deleted: 0
Key Change: Schema changes include creating new tables for missing optimization data and updating business configuration logic for scalar parameters and formulas.
Status: Complete
Confidence: high
Next Focus: Ready for convergence
Mapping Adequacy: mostly_good
Business Configuration Parameters: 2

Triple Expert Data: Values were determined based on typical promotional budget allocations and expected sensitivity of movie ratings to promotional efforts, ensuring a balanced distribution across movies.