Many companies have considered, and rejected, the use of data analytics tools in their efforts to improve efficiency and reduce process costs. Often, CFOS and their CIOs may feel that the need for better data quality is too big of a hurdle to overcome. As the saying goes: garbage in, garbage out.

But John Lucker, Principal at Deloitte Consulting, says that CFOs should stop getting hung up on data quality. "All too often, CFOs and their CIO colleagues think that the quality of their data has to be perfect to be used for business analytics, and it does not."

Lucker says that the value of business analytics is such that missing out on the opportunity to make use of data analytics for fear of having imperfect data would be a great loss. "Greater value can be realized by just moving on and using the data available for business analytics activities," he adds, stressing that no data is ever perfect.

In fact, given that data analytic exercises tend to involve trend analysis and make use of statistical modeling, the data used for most business analytics doesn't need to be perfect as the statistical underpinnings of analytics are able to adapt and compensate for imperfect data.

Analytics can be used across a broad range of functions and processes in order to improve efficiency and have a deeper understanding of what is driving a particular internal--or external--business trend. Generally the biggest obstacle is not data, but rather the internal unwillingness to change.

Says Lucker: "The CFO has a big role in pulling together the magic concoction that leads to business intelligence and business analytics success.  Working closely with the CIO, the CFO must build the information infrastructure necessary."