It was analyzed the incorrect or misleading use of the data analysis in the business making a business decision. The misuse of the statistics could be addressed by bias or inadequate tools, or the lower knowledge or expertise to develop the data analysis. Misleading statistics are recognized in six distinct categories: misleading data visualizations, selective bias, purposeful, using the small sample size, data fishing, and finally polling. We will describe each misleading of statistics, and we are going to analyze two cases. The first cases expose the misuse of small samples, and data fishing could provide the wrong view of business strategies and affect business decision-making. The second case explains how flawed correlations and faulty polling affect innovation and market surveys when companies introduce new products or services.