Data science is the poster child of the 21st century and for good reason. Data-based decisions have streamlined, automated, and made businesses more efficient than ever before, and there are practically no industries that haven’t recognized its immense potential. But when you think of data science application, sectors like marketing, finance, technology, SMEs, and even education are the first that come to mind. There’s one more sector that’s proving to be an untapped market for data—the social sector. At first, one might question why non-profit organizations even need complex data applications, but that’s just it—they don’t. What they really need is data tools that are simple and reliable, because if anything, accountability is the most important component of the way non-profits run.
Challenges for Non-profits and Data Science
If you’re wondering why many non-profits haven’t already hopped onto the data bandwagon, its because in most cases they lack one big thing—quality data.
One reason is that effective data application requires clean data, and heaps of it, something non-profits struggle with. Most don’t sell products or services, and their success is reliant on broad, long-term (sometimes decades) results and changes, which means their outcomes are highly unmeasurable. Metrics and data seem out of place when appealing to donors, who are persuaded more by emotional campaigns. Data collection is also rare, perhaps only being recorded when someone signs up to the program or leaves, and hardly any tracking in between. The result is data that’s too little and unreliable to make effective change.
Perhaps the most important phase, data collection relies heavily on accurate and organized processes. For non-profits that don’t have the resources for accurate and manual record-keeping, clean, and quality data collection is a huge pain point. However, that is an issue now easily avoidable. For instance, avoiding duplicate files, adopting record-keeping methods like off-site and cloud storage, digital retention, and of course back-up plans—are all processes that could save non-profits time, effort, and risk. On the other hand, poor record management has its consequences, namely on things like fund allocation, payroll, budgeting, and taxes. It could lead to financial risk, legal trouble, and data loss — all added worries for already under-resourced non-profit organizations.
But now, as non-governmental organizations (NGOs) and non-profits catch up and invest more in data collection processes, there’s room for data science to make its impact. A growing global movement, ‘Data For Good’ represents individuals, companies, and organizations volunteering to create or use data to help further social causes ad support non-profit organizations. This ‘Data For Good’ movement includes tools for data work that are donated or subsidized, as well as educational programs that serve marginalized communities. As the movement gains momentum, non-profits are seeing data seep into their structures and turn processes around.
How Can Data Do Social Good?
With data science set to take the non-profit sector by storm, let’s look at some of the ways data can do social good:
- Improving communication with donors: Knowing when to reach out to your donors is key. In between a meeting? You’re unlikely to see much enthusiasm. Once they’re at home with their families? You may see wonderful results, as pointed out in this Forbes article. The article opines that data can help non-profits understand and communicate with their donors better.
- Donor targetting: Cold calls are a hit and miss, and with data on their side, non-profits can discover and define their ideal donor and adapt their messaging to reach out to them for better results.
- Improving cost efficiency: Costs are a major priority for non-profits and every penny counts. Data can help decrease costs and streamline financial planning
- Increasing new member sign-ups and renewals: Through data, non-profits can reach out to the right people they want on-board, strengthen recruitment processes and keep track of volunteers reaching out to them for future events or recruitment drives.
- Modeling and forecasting performance: With predictive modeling tools, non-profits can make data-based decisions on where they should allocate time and money for the future, rather than go on gut instinct.
- Measuring return on investment: For a long time, the outcomes of social campaigns have been perceived as intangible and immeasurable—it’s hard to measure empowerment or change. With data, non-profits can measure everything from the amount a fundraiser raised against a goal, the cost of every lead in a lead generation campaign, etc
- Streamlining operations: Finally, non-profits can use data tools to streamline their business processes internally and invest their efforts into resources that need it.
It’s true, measuring good and having social change down to a science is a long way off — but data application is a leap forward into a more efficient future for the social sector. With mission-aligned processes, data-driven non-profits can realize their potential, redirect their focus from trivial tasks, and onto the bigger picture to drive true change.