A Data Capability Framework for the not-for-profit sector

Report by Anthony McCosker, Frances Shaw, Xiaofang Yao and Kath Albury: “As community services rapidly digitise, they are generating more data than ever before. These transformations are leading to innovation in data analysis and enthusiasm about the potential for data-driven decision making. However, increased use of personal data and automated systems raises ethical issues including gaining community trust, and introduces challenges in building knowledge, skills and capability.

Despite optimism across the not-for-profit (NFP) sector about the use of data analysis and automation to improve services and social impact, we are already seeing a growing data divide. Private sector companies have for some time invested heavily in data science and machine learning. However, many in the NFP sector are unsure how to meet the demands of these digital and data transformations. With limited resources, small, medium and large organisations alike face challenges in building their data capability and channelling it toward improved social outcomes. Working with marginalised clients, collecting sensitive personal information, and tackling seemingly intractable cycles of disadvantage, the sector needs a data capability revolution.

This short guide sets out a Data Capability Framework developed with and for the NFP sector and explains how it can be used to raise the bar in the use of data for impact and innovation. It conceptualises the core dimensions of data capability that need to be addressed. These dimensions can be tailored to meet an organisation’s specific strategic goals, impact and outcomes.

The Framework distils the challenges and successes of organisations we have worked with. It represents both the factors that underpin effective data capability and the pathways to achieving it. In other words, as technologies and data science techniques continue to change, data capability is both an outcome to aspire to, and a dynamic, ongoing process of experimentation and adaption…(More)”.