It’s often said that “time is money” but many companies may be leaving money on the table by failing to capitalize on the Federal Research and Development (R&D) Tax Credit.
Introduced in 1981 and intended to encourage R&D spending in the United States, the Section 41 R&D Tax Credit is a general business tax credit that applies to businesses investing expenditures on certain qualified research activities, such as:
- Developing new or improved products, processes, software or hardware
- Experimenting and testing new materials, concepts and technology
- Customizing products to meet customer’s needs
- Building prototypes including computer-generated models
- Adding equipment to improve processes
The R&D Tax Credit is one of the most carefully scrutinized credits. Yet, for the estimated 20,000 companies that apply for the tax credit every year, the process can be a laborious one. As a result, it’s critical that companies be well prepared to substantiate claims by providing adequate documentation of their expenditures in both personnel hours and costs.
It is in this aligning of project data and documentation with the tax rules that is the main challenge of the R&D credit. Consider that in the 1990s, the industry faced two key problems. First, documents were in hard copy form and stored in bankers boxes making it almost impossible to access and leverage the information. Second, the tax rules lacked clarity.
The solution to these challenges in 1990 was to personally interview stakeholders about projects and ask R&D experts to interpret the rules. But almost 30 years later, the world is very different and those two issues have been resolved.
Data and documentation is now electronically stored, making it easy to access, structure and leverage in R&D analysis. This is a very significant change. Consider that in 2015, IBM revealed that 90% of all of the world’s data had been created in the previous two years. “We’re in a data-rich environment today,” said Mark Andrus, Grant Thornton R&D Credit Leader. “The IRS would like to see detailed time tracking specific to the R&D credit for every taxpayer captured in one system.”
In addition, thanks to actions by the courts and the IRS, R&D rules have also now been clarified. “Today, the R&D rules are more clear than in the past,” noted Andrus, “We can now align taxpayer data and documentation with the R&D rules much more efficiently than the old status quo process which involved interviewing people every year, asking for some estimates and then trying to defend that expenditure with the IRS.”
Inefficient and antiquated documentation methods not only result in less than optimal results but also incur hidden costs such as missed credit opportunities, denied credit on earnings or unnecessary time spent on manually managing processes. That’s why as today’s tax departments grapple with tight budgets, fewer sources and increased compliance requirements, they are increasingly turning to automation to revamp cumbersome manual documentation processes.
Not only does an automated process reduce the high cost of interviewing research staff, centralizing the data in one system provides companies the opportunity to analyze, calculate the anticipated credit and better utilize the data for forecasting and planning. “We now live in a world of data and it’s time to leverage technology to use that data to compute the R&D tax credit,” Andrus said.
“We now live in a world full of data and it’s time to start to use that data to compute the R&D tax credit”
Using a technology solution to automate your R&D tax credit process enables companies to effectively:
- Reduce the burden on subject matter experts
- Streamline the documentation process
- Effectively defend tax positions
- Better forecast and analyze credit position at federal and state levels
- Identify and sustain more research tax credit
- Minimize audit exposure
- Improve relationships with R&D team
- Better protect sensitive information
Andrus suggested that as companies look to automate the R&D credit documentation process, they should start thinking in terms of data points rather than complete documents. “Businesses should start thinking about specific data points that exist within their company networks and identify which data points are most valuable,” Andrus explained. When developing a project list, for example, companies may need to identify data points from within multiple departments as they think about collecting and automating documentation.
More tax insights
No Results Found. Please search again using different keywords and/or filters.