The document discusses some key shortcomings of big data modeling, including models being based on unrealistic assumptions, identifying correlations between random variables as significant when they are just noise, and ignoring important variables. It notes that when evaluating an employee's earnings performance, a model may ignore their role as a manager. A manager should be aware that big data models may rely on impractical assumptions, identify spurious correlations, and omit important variables when making projections. They must consider an employee's leadership role and past performance for accurate analysis of their future earning capacity.