Moreover, a careful analysis of data generated by experiments can enable companies to better understand their operations and test their assumptions of which variables cause which effects. With big data, the emphasis is on correlation—discovering, for instance, that sales of certain products tend to coincide with sales of others. But business experimentation can allow companies to look beyond correlation and investigate causality—uncovering, for instance, the factors causing the increase (or decrease) of purchases. Such fundamental knowledge of causality can be crucial. Without it, executives have only a fragmentary understanding of their businesses, and the decisions they make can easily backfire.