Economic decisions are those where choices are made under conditions of scarcity. In other words, firms have a finite amount of resources and they have to decide how best to use or spend those resources to maximize their profits. Sample data can support and inform economic decision making by taking that raw data and converting it into information. That raw data is the most objective standard of inputs an organization has, and by utilizing sample data organization can look for correlations between data sets. Those correlations show the relationships between two disparate sources of data and potentially a causation. This way firms can know that by altering an input in a certain way it can affect output in another way.

Decision makers must be careful that their underlying data is accurate of course, but they also have to be careful in making assumptions about the data even when the raw information is accurate. For example, correlation might not necessarily correspond with causation. An often-cited example is the Hawthorne Effect. In the early twentieth century researchers studied productivity at the Hawthorne Works plant by altering several inputs (light levels, cleanliness, etc.) and each time an input was altered productivity rose. Researchers eventually figured out that it was the workers? knowledge of their presence, not the altered input, which rose productivity.