The tax function gathers data from various sources and systems across the enterprise, uses it to solve problems and find answers, and then delivers information in the form of return filings, reports, and presentations. Data analytics is fundamentally changing tax’s role by providing the ability to explore and explain data in new ways.
Tax analytics can help answer questions that couldn’t be cracked previously. For example, analytics can help illuminate the impact on tax rates of external and internal changes in the business environment. Or analytics can be used to scour contracts for language that could lead to different-than-expected tax consequences.
Visualization — a form of tax analytics can be a useful technology any time humans look at data output and make decisions based on it Visualization-oriented tools, as well as visualization capabilities found in statistical and business intelligence tools, can help equip tax specialists to explore and explain data in new ways and allow users to understand data better by seeing it in context.
Visual analytics helps users reach insights more quickly by more readily presenting factors and insights. Visualization can be used to explore the interplay of different scenarios on the global tax footprint, providing the ability to change the assumptions of one scenario and quickly see the impact across others. Visualization can also highlight anomalies in large sets of transactional data, improving the ability to investigate discrepancies.
Other than visualization, another attribute that relates to tax analytics is Sound data management, which is both essential to effective use of fax analytics and potentially a substantial challenge. Along with the large, disparate data volumes involved, tax calculations are routinely created in multiple instances of spreadsheet programs and stored in separate systems, and often the data generated isn’t fed back into source systems. Important data from different areas of a company can also have errors or inconsistencies or be incomplete, making it more difficult to extract, analyze, and manage data.