This is an overview of how different areas of the digital economy take up funding for innovation through the tax system. Other sectors are covered in separate posts.
When looking at whether or not funding can be claimed through the tax system for digital innovation there is a test of ‘obviousness’ which is easily overcome in this sector. Converting big data into actionable insight requires both quantitative and qualitative intelligence which very often gets over this hurdle. Businesses in this sector often describe the challenge of ‘sifting through sawdust’. Anyone in that position is likely to have a strong claim.
Machine to machine communications are a strong source of R&D tax relief claims at the moment as they raise significant technical uncertainties. Similarly, the way in which different, and often very diverse, data sets can be reformatted in order to be analysed and compared with other data sets raises huge challenges, particularly around the speed of conversion and analysis.
Another strong indicator that R&D tax relief is available is the involvement of highly skilled or technically knowledgeable people involved in a business. Data management and analytics businesses tend to have a higher percentage of people working in the business with PhDs and Masters qualifications than other (often more creative-focused) digital businesses and work more closely with universities than other digital businesses. This is particularly the case for those involved in artificial intelligence and machine learning and these hallmarks of innovation are strong indicators that funding support can be claimed through the tax system.