Each year the Australian Taxation Office (ATO) updates a set of financial benchmarks aimed at helping small business owners assess the state of their business.
The benchmarks cover one hundred industries including clubs and pubs, serving more than two million small businesses nationwide. Updates for this year have now been released.
These benchmarks serve as a health check and enable small business owners to compare their business performance with others in their industry.
Tony Goding, ATO Assistant Commissioner said these tools are similar to a routine GP visit, in that they assist small businesses to “diagnose their strengths or spot the early warning signs”.
Finding out how a small business fares against the industry standards can show owners if the business plan needs an adjustment or if it is doing well.
Goding warns that if a business’ numbers fall outside the benchmark range, they are more likely to garner attention from the ATO.
Non-compliance is a serious issue. When businesses avoid their tax obligations it is regarded by the ATO as participation in the ‘shadow economy’.
Deliberate participation in the shadow economy accounts for nearly 60 per cent of the total small business income tax gap, representing approximately $11.2 billion in lost tax revenue each year. Most of this amount is due to both over claiming of deductions and under reporting of income.
“The benchmarks are just one of the tools we use to tackle the shadow economy, along with community tip-offs and data matching,” said Goding.
“It’s all about levelling the playing field for honest businesses who are being undercut by their dishonest competitors that aren’t paying the tax they’re supposed to.”
The ATO advises small business owners who need assistance to consult their registered tax professional or a business adviser. It also offers a learning platform for further assistance.
The benchmarks can be found on the ATO website and on the ATO app.
The methodology for the benchmarks is consistent with methods used internationally and has been independently verified as statistically valid.
