How reliable is your data based on the assumptions you make?

The statement that your data is only as good as your assumptions emphasizes the fundamental role that assumptions play in data analysis and interpretation. When making decisions based on data, the assumptions underpinning the data significantly influence the outcomes and insights derived from it. If the assumptions are flawed or not well-founded, it can lead to misleading conclusions, resulting in poor decision-making. Therefore, the reliability of the data hinges upon the validity of those assumptions.

For example, if data is collected under the assumption that it reflects typical consumer behavior but doesn't account for seasonal variations or market shifts, the insights drawn from it might be inaccurate. The emphasis on assumptions highlights the need for robust initial judgments to ensure that data-driven decisions are sound and based on a solid foundation.