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.