QUT’s June 2014 working paper on tax-deductible donations, along with Generosity Magazine’s recent article on Private Ancillary Fund (PAF) data, indicated a sharp rise in health donations from PAFs, up from $18 m in 2010/11 to $33m in 2011/12. The research sector was also reported to have been a winner, with PAF distributions up from $4.9m in 2010-11 to $32m in 2011/12. Although health and research may appear to be some of the big winners, not all funding categorised amongst these two focus areas is for medical research projects per se. The way in which the Australian Taxation Office (ATO) classifies the data it collects can make it difficult for those analysing the data to determine how the donations are being applied. Some may have been allocated to public health studies, safety studies, health education, equipment or other activities.
Grant classification in itself can be ambiguous. Should a PhD scholarship be categorised as education, research or health? Should a gift to support an arts program aiming to improve health of the disadvantaged be classified as arts, health, cultural organisations or welfare? Should the focus area of an organisation dictate a grant’s classification, or the nature of the activity for which the grant is directed? As you can see there isn’t ‘clear-cut’ answer. Categorisation is a grey area and can often be very subjective.
Leading on from this, another concern is when different bodies and organisations release data that has been classified using different codes. Even if the codes are the same, different methodologies can mix oranges with bananas. This makes it very difficult to cross-reference and conduct data analysis of ‘where the money goes’. Data is a lot more useful when it is consistent, accurate and reliable. Data that is vaguely classified may also mislead donors into thinking a particular sector is well-funded, when in fact there may be significantly under-funded niche gaps within the sector.
In the philanthropic space, accurate data on giving can be particularly useful in aligning funding decisions against need and to assist with data-driven decision making. Whilst sector consultations have proven very useful in identifying gaps, reliable data is always a great supplement. I have yet to come across an organisation/sector that has said: thank you, but we really do have enough funding – your donation could be better used elsewhere. Therefore, relying solely on sector consultations may also be misleading.
Back in 2007, Philanthropy Australia developed a grant classification code, with input from various funding bodies and partners. For the health and medical research sector, the National Health & Medical Research Council (NHMRC) has also developed a detailed code that sits within the health and medical research classification. For the philanthropic sector, choosing to adopt standards for public reporting on funding remains voluntary. There was a sign of hope with the recent establishment of the Australian Charities and Not-for-profits Commission (ACNC) and the possibility for it to develop a unified system and collect data against it, but it’s with disappointment that we hear of its future being in jeopardy.
Perhaps it may be time to revisit this issue and together develop what may be a universally adopted classification system?