“It’s easier to edit than create”
That applies to everything that is created, not just to writing. The creative process requires that a person nurture an idea and bring it to life while editing is about honing and improving someone else’s idea.
This principle is the basis for more effective R&D credit interviews. It is easier to validate a narrative than to create a complete narrative.
SPRX R&D Credit Tip – Ask SMEs to validate information rather than create information. This simplifies the task, improves attitudes, and results in higher credits.
Typical R&D credit interview
Most R&D credit interviews follow a common agenda. The CPA explains the tax rules, gives a few examples of the rules, and then ask the SME some specific questions. The key question of all R&D credit interviews is, “how much time do you spend on qualified research”.
Responding to that question requires the SME to create an on the spot with little or no reference data. This is a difficult request. The question requires the SME to interpret tax rules, recall all activities conducted during the prior year, apply their interpretation of the tax rules to those activities, and compute a percentage.
Validating a pre-computed percentage would be a much easier request.
Validate vs Create
Consider the R&D credit interview through the validation lens. The CPA explains that she has analyzed all available data and applied the tax rules, and then asks the SME to help validate that the results.
It is much easier to validate the accuracy of an analysis than it is to create the analysis on the spot. The SME has the advantage of seeing the available data and of relying on the tax specialist’s interpretation of the tax rules. The SME adds her knowledge of past events, asks clarifying questions, and provides unique input to fill gaps in the data.
Technology facilitates the validation interview
Technology makes the validation interview possible. Artificial intelligence tools can quickly predict results based on an analysis of available data. Employee data, time data and project data can be loaded into an A.I. model. The model can quickly process the data and predict how much time employees may spend on qualified research activities.
Predictive results are the basis for validation interviews. SMEs can review the results, spot gaps in the data, and validate or edit the results based on what they see. The result is a more accurate R&D credit prepared in less time. Additionally, everyone involved has a better experience.
SPRX.tax has predictive A.I. tools built specifically for the R&D credit analysis.
At SPRX.tax we build the tools that save you time…and money