Australia
5 tips to avoid an R&D claim review by AusIndustry
1 October 2016 | Minutes to read: 3

5 tips to avoid an R&D claim review by AusIndustry

By Dr. Rita Choueiri

The Research and Development (R&D) tax incentive scheme promotes and boosts innovation, research and development, and productivity in Australia by providing tax offsets to businesses that undertake R&D in Australia.

Eligibility for R&D tax incentives is self-assessed by the applicant so may be subject to a review by AusIndustry by way of:

  • Pre-Registration Reviews
  • Registration Reviews
  • Desk Reviews
  • Activity Reviews
  • Large Business Innovation Reviews

Reviews can delay the process and increase the time spent on the claim, both of which can have a negative impact on the business. I’ve been fortunate in my ten years as an R&D tax incentive consultant to have never had an R&D claim application reviewed.

In this article I share my top tips for avoiding an R&D claim review:

Tip 1- Put yourself in the AusIndustry assessor’s shoes

Review your own application and ask yourself, would someone who knows very little about your company and project understand what the activities relate to?  For example:

  • Have you used acronyms that don’t make sense to anybody external to the company?
  • Have you given enough background detail to set the scene and provide context?
  • Have you included specific details and measurable parameters of intended outcomes?
  • Have you adequately described the knowledge gap?
  • Have you set out and described the scientific method?

The aim is to limit the number of questions that AusIndustry need to ask to understand the eligibility of the activities.

Tip 2 – Write a meaningful hypothesis

A hypothesis is a statement that can be validated or invalidated. Use your experience and knowledge on the topic to form an ‘educated’ likely answer to the scientific question that requires investigating.

The hypothesis should:

  • Have an “experimental” and “control” comparison
  • Demonstrate how success will be measured
  • Give the reader a fair idea of what you plan to achieve and an idea of the experiments that would be required to test the hypothesis

The following is a fictional example of a poorly written hypothesis:

Implementing new RF scanners on Line A will enable defective goods to be removed from the production line.

Using the principles outlined above, the same hypothesis has been re-written below in a more acceptable format:

Designing and implementing new RF scanning systems (involving developing new software and algorithms for off-the shelf scanning products) into Line A at Aust Co Pty Ltd’s Widget manufacturing facility will allow operators to identify, tag and remove faulty Widget As during the manufacturing process to decrease packed defective goods incidents from x% to y%.

Tip 3 – Provide specific relevant experimental details that took place during the financial year

In providing details of what has happened throughout the year, don’t use the same generic experimental details that have been outlined the experiment planning phase. They describe the various activities that will be undertaken as opposed to what actually was done.

I recommend drawing up a list of all the steps that were undertaken to test the hypothesis during the financial year (in past tense). Set the scene by briefly describing the activities that took place in the preceding financial year and expectations for the following financial year.   For example, in a 2016 financial year application you might write; “during FY15 the machinery required for the experiment was installed and we expect to continue observations during FY17”.

Ensure the activities listed in the experimental section relate to the hypothesis, if they don’t, tweak the hypothesis. Include whether anything went wrong and how it was rectified. Did you need to go back and retest anything or create new tests to answer new questions? Some companies describe the first set of activities but do not adequately describe any reiterations or changes in direction etc.

Tip 4. Include a conclusion that validates or invalidates the hypothesis

Your conclusion should be consistent with the hypothesis and indicate if further investigations will be required or if the product/process/service is ready for implementation/commercialisation. Do not leave the reader guessing.

Below is an example of an acceptable conclusion:

By conducting our manufacturing trials, it was found that designing and implementing new RF scanning systems (involving developing new software and algorithms for off-the shelf scanning products) into Line A at Aust Co Pty Ltd’s Widget manufacturing facility did not allow operators to identify, tag and remove faulty Widget As during the manufacturing process to decrease packed defective goods incidents from x% to y%. Further investigations are required to determine the causes for not achieving the intended outcome.

Tip 5. Include at least one supporting activity

Describe the preliminary research and activities undertaken before the commencement of the experiments (e.g. literature research, planning, purchasing of equipment, set up of experiment etc.) and include them as a supporting activity.

Comprise any supporting activities that took place after the new knowledge was achieved, e.g. monitoring type of activities and why they are relevant.

In summary, as you prepare the project descriptions, ask yourself, does the reader have enough detail to make an assessment on the eligibility of the activities? Don’t leave holes that may potentially instigate a question. If AusIndustry doesn’t understand what you are doing, why you are doing it, and how you are doing it, then expect a review.

5 tips to avoid an R&D claim review by AusIndustry

Dr. Rita Choueiri

Dr. Rita Choueiri is a scientist and the head of the Melbourne R&D Incentives division. She is a keen promoter of innovation and is a highly regarded R&D specialist helping companies to identify R&D opportunities, determine project eligibility and set up the systems and processes to maximise tax offsets and minimise exposure.

Related Insights