Just as John D. Rockefeller and Henry Ford did nearly a century ago, business leaders today, including Bill and Melinda Gates and Warren Buffet, are leading a new golden age of philanthropy to address some of the world’s most important challenges.
One major difference for philanthropists in 2020 is the abundance of data available to help them decide where to give and how to measure the impact of their investments.
Because of this they want to and are expected to give in a faster, bolder, and smarter way. Data-driven giving is one way of living up to those expectations.
Despite the benefits, many philanthropists struggle to apply new technologies and to adopt data-driven approaches to design more effective and efficient interventions.
Questions like; what is it that we need to learn and how will we learn it; which technologies really make sense, and which don’t; what do we put our emphasis on; and how effective are the selected activities and interventions; seem to be more relevant than ever.
Going big on data
Philanthropic data pioneers John and Laura Arnold fund research studies before any intervention is made. The Arnolds treat philanthropy as R&D. They argue that: “Without good data, it’s impossible to know what the real problem is or what the best solution is.”
Today, there are a variety of approaches to using data in philanthropy. Some philanthropists start from scratch and build basic capacities to use data while others use advanced analytics and apply technologies like artificial intelligence or machine learning.
Because using data requires such a substantial amount of effort and time, philanthropists need to make sure that building the capacities to harness data is a strong fit with their mission. This also means that philanthropists need to be even more explicit about what it is they want to achieve through their giving.
Here are our top tips for philanthropists starting to use data to drive their giving strategy:
- Be very clear about your mission and what you want to achieve
- Assess which data you already have at hand (structured or unstructured) and think about how to best leverage it
- Understand what data would potentially bring most value to pushing your mission forward
- Reflect on potential additional sources of data (in the future) and how this data might help you achieve your goals in a more effective and efficient manner
- Make a plan on how to build capacity to use data for the long-term
- Try to access or collect more granular data through surveys, text methods service, Internet of Things devices, interactions with focus groups, field experiments
- Test the quality of your data using comparable samples
- Consider automating your data collection
- Analyze your data using appropriate methods and tools
- Reflect on your findings and list actionable items to improve your intervention
- Collect feedback from relevant stakeholders and design a feedback loop for your future interventions. If you are collecting real-time data, you can also build in more agile and real-time iterations
- Reflect on the specific context you are in and prioritize actionable items
- Make data culture systematic and scale up whenever possible
In-house or outside?
Not all data expertise needs to be developed in-house. If building a data culture in-house is not an option, connecting with developers and service providers who want to be engaged in the social sector is one way to go about it.
Another way of accessing outside expertise is by collaborating with a diverse set of stakeholders who share a collective purpose of designing more effective interventions. This provides philanthropists with guidance, structure and accelerates their learning.
What are the opportunities?
Data can help philanthropists work at a larger scale than ever before, be more efficient and transparent, and solve problems more effectively.
Data is an asset for philanthropy because it enables philanthropists to better grasp the needs of their beneficiaries, carry out more effective interventions and improve how philanthropists assess impact. Data-informed decision-making about philanthropic investments and grants helps philanthropists get the most out of every dollar they invest.
What are the challenges?
Data doesn’t always give the whole picture and it can be used in non-productive ways.
There is also the risk that it can be biased and lead to the wrong conclusions. Bias can be introduced at any stage: collection, analysis, conclusion and there are statistical biases as well as systemic biases. Furthermore, not all data is transferable to different contexts. Philanthropists need to constantly question what biases could be affecting their data and revisit their processes.
A common mistake of many less-experienced philanthropists is building a data strategy around a funding source or “impact washing” – when a company or fund makes impact-focused claims without having any demonstrable positive social or environmental impact. As a result, they may deviate from their true mission, wasting resources on activities that are irrelevant to their central purpose.
Philanthropists should start by strengthening their current capabilities and using data already available to them. The goal of effective giving is to use data to drive problem solving to make the world a better place. To achieve that, philanthropists need to develop the right mindset to create a culture built on data. In a world of complexity and no easy answers, data should become part of every philanthropists’ DNA. In short, philanthropists need to understand and use data if they want to bring about real social change.