In the world of taxes, finding the right data is critical to compliance and avoiding unnecessary tax penalties and costly audits. It’s all about quality—the data must be both accurate and complete.
The term “Big Data” refers to the recent, explosive growth of the availability of data. The promise of Big Data to enable more accurate analysis, operational efficiencies, cost reductions and reduced risk are just a few of the reasons for the hype. Every business seems to want as much data as they can get their hands on.
For tax departments, however, more data is not always better. In reality, most tax departments need only a small portion of what’s available in the massive sea of corporate Big Data. Too much data can be crippling and impossible to analyze. In the world of taxes—whether dealing with income, sales, property, or international taxes—finding the right data is critical to compliance and avoiding unnecessary tax penalties and costly audits. It’s all about quality—the data must be both accurate and complete.
So how can tax departments navigate the Big Data landscape? If you are like most companies, you will likely use automation technology to manage calculation, reporting and compliance. But keep in mind that not all technology is created equal.
Since the various types of tax compliance (e.g., sales, international, property, or income) are different enough to warrant specialized solutions, for simplicity, we will use indirect tax compliance as an example. Indirect tax compliance is a cumbersome process with many correlating steps within the automation process. Fail at any of those steps, and the results could be disastrous—and result in audits and penalties. Indirect tax compliance is where the adage “garbage in, garbage out” applies more than ever. As a result, companies need to look at the automation process from a holistic standpoint or risk a breakdown of the overall indirect tax compliance process.
• The first step in the process is to make sure your company has the most up-to-date tax research, which includes rates, rules, logic and product taxability information. For example, in the U.S. alone, businesses had to comply with over 580 indirect tax rate changes in 2012, spanning more than 14,000 jurisdictions and 44,000 different rate/jurisdiction combinations. Without the most accurate data, accurate calculations are impossible.
• Once accurate tax research is in place, the next step is to select a robust tax determination engine, which provides tax jurisdiction, taxability, tax rate tables and tax calculation logic, along with full transaction reporting. With thousands of taxing jurisdictions, all with continually changing tax rates, having a robust tax calculation and determination engine ensures that the correct tax rates are charged from the get-go.
• Since most companies don’t have just one system, indirect tax integrations are critical to providing a complete view of various transactions from ERP systems, as well as e-commerce, POS and legacy financial systems. Bringing tax automation to as many finance systems as possible extends the benefit that can be brought about by automation.
• The final step is compliance, which provides return preparation, electronic filing (where supported) and audit reporting. If necessary, the ability to import transaction data from multiple financial systems into the compliance solution is critical. Again, without the complete and accurate view of data, creating accurate returns and audits reports is a moot point.
The operational resources required to achieve tax compliance (in particular within indirect tax) can be overwhelming. Not only are companies required to navigate a dynamic indirect tax landscape, but a renewed emphasis on indirect tax has resulted in a flurry of new tax laws, making an already complex process even more cumbersome. Couple this inherently complex process with Big Data initiatives, in which companies aim to amass as much data as possible, and it’s difficult to find the needle in the haystack.
It is imperative that tax departments select automation technology aimed at consolidating transactional data stored in multiple systems and melding that data with the thousands of tax law changes typical in a given year. The result is the transformation of Big Data into actionable, accurate data and the end of siloed, error-prone tax calculations that put companies at risk.