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Technology reshapes tax operations

Technology reshapes tax operations

Technology reshapes tax operations

Post-reform, technology reshapes tax operations

Modernizing the tax department with ever-advancing technologies like data and analytics and intelligent automation has a permanent spot on nearly every CTO’s wish list. And now, the new US tax law — which has pushed tax to the top of the business agenda — is helping them make a stronger case for investment. Over the next two to five years, tax departments will be especially focused on introducing innovative tools to better manage data and automate human tasks.

As organizations begin to navigate the ins and outs of US tax reform, data — or lack thereof — is becoming a major cause for concern. Many companies — especially those with global operations or online businesses — must collect more data, with more detail, from more jurisdictions than ever before. In the most highly regulated industries, the data requirements have become truly massive.

Unfortunately, many tax functions have found they either don’t have all the data they need or it’s not managed in a way that makes it practical for everyday tax operations. At the same time, their current tax code calculation processes simply don’t provide the mix of scope and detail required to meet the complex requirements of the new law. But it’s not just a data volume issue. US tax reform in particular has introduced a number of tax “cliffs” that now require significant precision in determining tax attributes. Simple human error can now have significant tax consequences.

For example, one of the most immediate challenges facing tax departments is meeting the need for legal entity data. Many organizations currently lack legal entity data or only have it in a relatively unusable format. In fact, legal entity data management often relies mainly on Excel and manual and time-intensive processes that lead to a number of critical issues: duplicate work, version confusion, lost data, and audit difficulties.

CTOs are tackling the legal entity data challenge in a number of ways. Some are working to establish global legal entity reporting within a new consolidation tool. Others are implementing more robust reporting processes through its legal entity management system or have plans to invest in workflow management tools to improve data access, management, and automation.

Tax reform is serving as an impetus for other technology improvements as well. Facing new responsibilities and compliance demands, many CTOs are seeking to embed intelligent automation — a broad spectrum of digital technologies that augment human tasks — into a wide variety of tax processes to assist human tax professionals. As tax teams manage increasingly complex regulatory requirements, these novel tools can help save time, reduce costs, and improve quality. For example, many tax functions are experimenting with intelligent automation for simple and repetitive tasks, such as cutting and pasting content from one tax system to another, as well as far more complex work, such as analyzing unstructured data sets used in certain filings.

Of course, data can sometimes be a stumbling block. We have seen a variety of data issues hamper efforts to transform the tax function through intelligent automation. For example, impure data, particularly in the general ledger, often delays automation goals. Even tax functions that are already far down the road with an automation solution may need to go back and add front-end data cleansing processes, reducing planned efficiencies.

To solve data quality challenges, some tax functions are deploying user-friendly tools to advance data gathering, organization, and analysis — and get data ready for automation. Others are building data lakes or warehouses designed to draw in the underlying data required to improve overall data quality and drill down capacity in the general ledger.

Questions to consider

  • How does tax reform change your tax function’s business case for technology spend?
  • As you build the tax function of the future, is your data good enough for the tools you want to use?
  • What tax system alternations will help you address data-related roadblocks?