Automation Has Power to Reduce E-Commerce’s Indirect Tax Burden

While often perceived as a burden to business, indirect taxes have been part of the US economy for more than a century. West Virginia enacted the first state sales tax in 1921; today, there are almost 10,000 sales and use tax jurisdictions. And in any given year, a number of these tax rates change.

The explosion of e-commerce over the last decade has further increased the complexity with buyers and sellers from different states conducting online sales transactions. This complexity, in and of itself, poses the question: Why are some companies still collecting and paying indirect taxes manually?

The very nature of indirect taxes is complicated and unwieldly. Indirect taxes are imposed on a person or group such as retailers, then passed on to a different payer, such as consumers. In the US, state sales tax rates vary from 2.9% to 7.25%; on-state sales or use taxes range from 1% to more than 5%.

The most affected industries include retail stores and e-commerce platforms, hospitality and tourism, automobile manufacturers and dealers, the energy sector (fuel and electricity), telecommunications (mobile, cable, and internet services), and alcohol and tobacco. Businesses may recover the cost of the taxes by charging higher prices to customers, paying lower wages and salaries, paying lower dividends to shareholders, or accepting lower profits.

The complexity lies in several factors. Data often comes from different sources in multiple formats. To make matters worse, the data set isn’t always complete. Often, there are missing transactions for a variety of reasons.

E-commerce further complicates data extraction. For example, a buyer in Texas could be making a purchase via mobile phone from a vendor in Florida through a company based in New Jersey. The solution to complex manual operations is to shift to automation using different tools during different stages of the process: data extraction tools, data analytics tools, and software solutions.

For example, during the data extraction stage, data can be collected from different sources (without missing transactions) and compiled into the same format to feed into the system, making it easier for businesses to track collections and payments of indirect tax with greater accuracy. This process is often referred to as extract, transfer, and load, or ETL.

Like ETL, data analytics tools and software solutions can be technologically configured to meet the specific requirements of any given client. During this stage, data is both cleansed and verified, thus reducing error, and companies can generate an automatic data validation summary report.

The next step is to ensure compliance. With automation, data can be imported directly into a compliance system, and tax returns can be quickly generated.

While automation requires an initial investment up front, the return on investment can be realized relatively quickly. The investment is low spend in nature, especially considering that companies can reduce more than 50% of their human efforts in manipulating data manually within six to eight weeks. This reduction in effort is continuous with automation; when indirect tax rates change, or other variables affect the data input and output.

The beauty of automation is more than a timesaver. Sophisticated, customized software allows businesses to remain agile and responsive, reducing their risk in compliance with real-time software vendor updates, reducing a company’s risk.

Ultimately, an investment in automation also requires an investment in your people. Chances are many of your team members won’t know these tools. Automation of indirect tax processes gives companies the opportunity to upskill their people, leading to greater employee retention. And the time saved with an investment in automation can be used for other strategic business growth objectives, including research and innovation.

As Max Baucus once famously said, “Tax complexity itself is a kind of tax.” But if businesses take heed, automation is one thing they can do to reduce the complexity and burden of indirect taxes.

This article does not necessarily reflect the opinion of Bloomberg Industry Group, Inc., the publisher of Bloomberg Law and Bloomberg Tax, or its owners.

Author Information

Josh Din is a tax partner in Baker Tilly’s tax evolution and automation group. He specializes in implementing leading edge tax technology solutions and practical processes for tax functions to optimize data, process, technology, and people.

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