Why data analytics matter to accountants

Accountants will be increasingly expected to add value to the business decision-making within their organizations and for their clients,” comments Associate Professor Wendell Gilland. He teaches Data Analytics for Accountants at UNC Kenan-Flagler Business School. “A strong facility with data analytics gives them the toolset to help strengthen their partnership with business leaders.”

Here are a few examples:

Auditors, both internally and externally, can shift from a sample-based model to employ continuous monitoring where much larger data sets are analyzed and verified—the result: less margin of error resulting in more precise recommendations.

Tax accountants use data science to analyze complex taxation questions related to investment scenarios quickly. In turn, investment decisions can be expedited, allowing companies to respond faster to opportunities to beat their competition — and the market — to the punch.

Accountants who assist or act as investment advisors use big data to find behavioral patterns in consumers and the market. These patterns can help businesses build analytic models that, in turn, help them identify investment opportunities and generate higher profit margins.

Four types of data analytics

To better handle big data, it’s essential to understand four key types of data analytics.

1. Descriptive analytics = “What is happening?”
This is used most often and includes the categorization and classification of information. Accountants report on the flow of money through their organizations: revenue and expenses, inventory counts, sales tax collected. Accurate reporting is a hallmark of solid accounting practices. Compiling and verifying large amounts of data is essential to this precise reporting.