Research & Development Incentives

Best Practices

Follow These Best Practices And Eligibility Rules To Qualify For The R&D Credit

Companies that invest in research and development activities to develop new or improved business components (product, process, technique, formula, invention, or software) can qualify for the R&D credit under Internal Revenue Code (IRC) Section 41 and can receive a tax credit of as much as 20% of qualified research and development expenses.

In order to properly and accurately document your R&D tax credits it’s critical that companies follow best practices to fully comply with the many rules and regulations surrounding the R&D credit.  The following information defines what is “research” according to the tax code and what activities will be considered eligible.

Research and development activities are more than just activities performed in a laboratory, conducting blue sky research new to the world.  The “research” definition is much more broad and general and only has to meet the four-part test:

  • Permitted Purpose: The activity must be intended to develop or improve a business component’s (product, process, technique, formula, invention, or software):
    • Functionality
    • Performance
    • Reliability, or
    • Quality
  • Technological in Nature: The activity performed must not rely on any social sciences and instead, must fundamentally rely on principles of: Physical science, Biological Science, Computer Sciences, or Engineering.
  • Elimination of Uncertainty: The activity must be intended to discover information to eliminate technical uncertainty concerning the capability or method for developing or improving a product or process, or the appropriateness of the business components design.
  • Process of Experimentation: Substantially all of the activities must be elements of a process of experimentation:   The activities must involve the evaluation of one or more alternatives to achieve a result where the method of achieving that result is uncertain. Activities should include designing experiments to evaluate and test alternatives through processes of systematic trial and error, simulation, or modeling.

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