Overreliance on Data: Organizations often place too much emphasis on data without considering qualitative insights, leading to decisions that may not fully align with the context or organizational goals.

Quality of Data: The quality and accuracy of data are crucial. Poor data quality can lead to incorrect conclusions and misguided strategies.

Bias in Data: Data can often reflect existing biases, which can be perpetuated if not addressed. It's important to critically evaluate the sources and methods of data collection.

Complexity and Interpretation: Data-driven decisions can be complex, and misinterpretation of data can lead to errors. Effective decision-making requires not just data analysis but also the ability to interpret results accurately.