We predict the data trends that will shape charities data strategy throughout 2020 - and beyond.
Charities of all sizes are collecting more data than ever before about their supporters, the initiatives they launch, and the digital fundraising campaigns they run. But the data itself has no integral value. It’s only when it is analysed that insights can be drawn out of it and it can become the lifeblood of a charity that is committed to digital.
This begs a hugely important question: what is the best way to manage and use this data so that these valuable insights can be extracted? The answer, in general terms, is through data optimisation. This is the practice of collecting, organising and managing all the charity’s information in a way that allows it to be analysed effectively so that insights can be drawn from it and put to work as quickly as possible.
The ways in which charities are optimising and using their data are changing rapidly. Here are five data trends which are expected to develop of the course of the next year:
Charities are taking steps to become more data-driven – using data rather than anecdotal evidence, personal
experience, or gut feeling, to guide their activities.
Taking a cue from the private and public sectors, digital leaders will increasingly be using data to drive internal changes including team or department restructuring, switching operating models, redistributing job responsibilities, and changing IT applications.
To do this successfully, charities will have to secure leadership buy-in for these changes, equip staff with the right skillsets, and overcome outdated cultures and mindsets.
Analysing data can be hard and time-consuming, and at the moment it may require staff with data analytics expertise to get at the most valuable insights. But in 2020 an increasing proportion of data-based tasks will become automated, making data analytics available to more charities which lack the resources and skills to carry out these tasks manually.
Perhaps more importantly, machine learning (ML) and artificial intelligence (AI) tools will increasingly become available to help digital charities spot hidden relationships in data and make sense of them, turning statistical correlations into actionable insights with little human oversight.
Analysing data used to involve creating complex database queries which required a considerable level of database expertise. But in 2020 it is expected that about 50% of analytical queries will be generated by search, natural language processing or voice, according to IT research house Gartner.
This should make analysis as straightforward as carrying out a Google search, but the next stage – conversational analytics – will make analysis even easier.
Conversational analytics will enable digital leaders to analyse their data by asking questions like “how many of our supporters within 25 miles of London switched from single to repeat givers this year compared to last year?” – as if they were having a conversation with a colleague or digital assistant.
International data privacy laws such as the EU’s GDPR apply to charities and other non-profit organisations as well as to businesses, and that may be one of the key reasons that many charities will be looking to beef up their data security measures in 2020.
Other drivers include the fact that 25% of charities reported at least one cyber-attack last year, and the latest figures showing that charities reported more than 100 data breaches to the Information Commissioner’s Office in the second quarter of the year.
One of the biggest challenges to charities’ efforts to become more data-driven is the fact that charities – and many other organisations – commonly store their data in a number of different silos: in different centralised storage systems, on employees’ computer systems, and also in the cloud.
A key part of data optimisation is putting a data strategy in place which makes it easier to access all of an organisation’s data, wherever it is located, and that’s where data fabric technologies can help. These are a collection of technologies which make disparate storage siloes as accessible as if the data were all stored in a single storage system.
Although data fabrics may currently be too expensive for all but the largest of charities, falling costs will likely mean that an increasing number of charities look to data fabrics as an alternative to de-siloing efforts in order to make their data more accessible to anyone wishing to carry out data analytics.