What is often a limitation when too many factors are considered in a model?

When too many factors are considered in a model, it may obscure the key objectives of the problem. This limitation arises because as more variables are added, the complexity of the model increases, which can lead to difficulties in focusing on the most critical elements that impact decision-making. An overload of information can make it challenging to identify which factors are truly significant, potentially leading to confusion or misinterpretation of data. As a result, stakeholders might lose sight of the primary goals they are trying to achieve, making it harder to derive actionable insights from the model.

In business research, clarity is crucial for effective decision-making. When the core objectives become obscured by a plethora of lesser factors, the quality of decisions may suffer. Thus, simplifying a model to focus on the most relevant variables is often advisable to enhance understanding and facilitate better outcomes.