In the context of developing a machine learning model for predicting customer churn in a telecommunications company, the team is discussing the importance of 'framing' the problem correctly. The project has constraints including a tight budget, the need for high accuracy to ensure customer retention strategies are effective, and compliance with data privacy regulations. Considering these constraints, what is the primary significance of 'framing' the machine learning problem in this scenario? Choose the best option.