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Philanthropy And The Social Economy (#Blueprint17): Some Lessons For Singapore

Taken from http://www.asianphilanthropyforum.org/assets/AVPN_first_panel.jpg.

Philanthropy and the Social Economy (#Blueprint17): Some Lessons For Singapore.

Philanthropy and the Social Economy: Blueprint 2017” is an annual industry forecast penned by American academic and writer Dr. Lucy Bernholz, who works at the Centre on Philanthropy and Civil Society in Stanford University, and who has been consulting to philanthropy and the social economy since 1990. “The Huffington Post” called her a “philanthropy game changer”.

Many of the perspectives in the blueprint may have been written with an American audience in mind – to galvanise further conversations within the sector and within organisations – but some are also applicable around the world. I have therefore summarised a few perspectives which may be relevant to the Singapore context, and in this vein perhaps even further contribute to a personal pool of research questions for the future.

Digital dependence, infrastructure, and governance

Organisations in the non-profit sector are dependent upon digital infrastructure, and to underscore the point Dr. Bernholz painted a scenario in which the organisation’s server goes offline for a day and everything on it is lost, resulting in recovery costs, costs of reputational damage, and the other time lost. “The digital infrastructure includes the software, hardware, networking, and telecommunications services that drive … daily communications, fundraising, marketing, advocacy, meeting planning, accounting, financial reporting, grants management, performance measurement, and outcome reporting” (page 10). Three worksheets can be used too:

Worksheet: Digital Data Inventory

Worksheet: Digital Data Inventory

Digital governance is important too. In Singapore, charities have been given guidance relating to data protection – especially for fundraising appeals, under the Personal Data Protection Act, or the PDPA – yet little has been said about digital infrastructure and governance. “Now non-profits and foundations need people on their boards who understand how digital works, what the relevant policy domains are, and how to manage digital risk” (page 14), and the same will apply to the Singapore context.

Software and apps for civil society

While no study or research has been done, this development has yet to gain traction. There are independent endeavours – TechLadies (through which women take part in a 10-week part-time coding bootcamp, developing apps for non-profits), the Computing for Voluntary Welfare Organisations initiative in the National University of Singapore School of Computing (through which IT systems are built for charities), and DataKind (through which data scientists provide social organisations with pro bono assistance), though more can be done.

An important caution, furthermore, is that “most digital data and systems are designed by corporations, monitored by governments and regulated by oversight organisations that few non-profits and foundations can even name” (page 12), and hence attention must be paid to software protocols and regulatory regimes. Intermediaries could be useful in this regard.

Experiments and evaluations of programmes

Dr. Bernholz predicted that “experiments with the policies and practices of universal basic income will spread” (page 24), and even though it is unlikely to happen in Singapore – given Prime Minister Lee Hsien Loong’s remarks during an interview with “TIME” Magazine – policymakers can look forward to two developments. First, the results from the upcoming experiments in Canada, France, the Netherlands, and especially Finland will allow the present discourse to move beyond the superficial and the general. Will the basic income cause recipients to loaf around? Or will it improve work incentives? And will bureaucratic systems for welfare payments be eased?

We have no real clue, which is precisely why the experiments will be helpful. In this vein, the second tangential development – in Singapore – could be greater openness to the evaluation of programmes run by non-profit organisations. My dissertation found that while charities in the country had no trouble articulating their outputs in the form of descriptive data, the same cannot be said when it comes to outcome data. Resistance against randomised trials or even quasi-experiments, nevertheless, must be managed.

Financial and tax information of charities

In the context of the United States, Dr. Bernholz had previously predicted that “clean, machine-readable tax files from 2014 for [American] non-profits will be online for anyone to access”, and the Internal Revenue Service has actually released 600,000 machine-readable files. In Singapore, financial information about charities – especially the Institutions of a Public Character – are available both on the Charity Portal and on their respective websites, but the limitation here is that the data is not machine-readable.

For an econometrics module, we had a plan to study the effect of government funding on the financial efficiency of charities in Singapore, though we ran up against this roadblock. Instead, data from Canadian charities were used. Making such data and information available and machine-readable in this country will allow for meaningful research on a macro-level.

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About guanyinmiao

A man of knowledge lives by acting, not by thinking about acting. Carlos Castaneda.

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