Data is a powerful tool for philanthropic organizations to improve their impact, efficiency, and accountability. But how can they use data effectively for decision making? In this article, you will learn about some of the best ways for philanthropic organizations to use data for decision making, such as:
Before collecting and analyzing data, you need to have a clear idea of what you want to achieve and how you will measure it. This means defining your goals, objectives, and indicators that align with your mission and vision. You also need to establish a data strategy that outlines how you will collect, manage, store, share, and use data. Having a clear data strategy will help you avoid data silos, duplication, and inconsistency.
Activity metrics are a critical element of goal setting - not just cash in the door. This will help measure and motivate your team to talk to people, move through the cultivation cycle, and compete asks.
Assessment and Impact measurement is important in data driven decision making process. Establish clear, measurable goals and key performance indicators (KPIs) to assess the impact of philanthropic initiatives. Collect and analyze data on outcomes and outputs to evaluate the effectiveness of programs and projects. Utilize surveys, interviews, and feedback mechanisms to gather qualitative data on the experiences of beneficiaries.
Definitivamente los indicadores clave para las organizaciones filantrópicas son los que miden el impacto de la institución en su entorno y los resultados de sus programas en su población beneficiaria. Sin ellos no podemos ser contundentes a la hora de comunicar nuestra causa a los donates y aliados actuales y potenciales.
One of the benefits of data is that it can help you test your assumptions and hypotheses about your interventions and outcomes. You can use data to design and conduct experiments, such as randomized controlled trials, quasi-experiments, or A/B tests, to compare different approaches and measure their effects. You can also use data to monitor and evaluate your progress and impact, and to identify what works and what doesn't. Using data to inform and test your assumptions will help you learn from your successes and failures, and to adapt and improve your strategies.
Testing assumptions is an important way to continuously improve results and ROI. By experimenting in areas such as messaging in annual giving asks you can understand the impact of different messaging using a small sample, learn from it, and adjust accordingly for your full audience.
Another benefit of data is that it can help you communicate and collaborate with your stakeholders, such as donors, beneficiaries, partners, and policymakers. You can use data to tell compelling stories about your work, your impact, and your challenges. You can also use data to solicit feedback, input, and support from your stakeholders, and to engage them in co-creating solutions. You can also use data to build trust and transparency, and to demonstrate your accountability and credibility. Using data to communicate and collaborate will help you increase your visibility, influence, and sustainability.
A third benefit of data is that it can help you innovate and scale your impact. You can use data to identify new opportunities, needs, and gaps in your field, and to generate new ideas and solutions. You can also use data to assess the potential and feasibility of scaling your interventions, and to measure the cost-effectiveness and efficiency of your operations. You can also use data to leverage new technologies, such as artificial intelligence, machine learning, or blockchain, to enhance your capabilities and reach. Using data to innovate and scale will help you increase your relevance, value, and impact.
Of late 'Data' has become a buzzword and a commodity. However, philanthropic organizations need to be truthful to the mission. Ethics is a cornerstone of philanthropy. Therefore use of data needs to be responsible and meaningful, from data collection to processing to storage to destruction. In the entire cycle, how to handle data responsibly and then how to use data to generate valuable insights for drawing inferences and use that for innovation and scale remains a challenge. While we can certainly talk about AL/ML, Blockchain, etc. I often feel that most organizations grapple with the basics. Simple analysis using Excel and SPSS can be the starting point. Then audience/ user specific building relevant dashboards would come into picture.
Finally, one of the challenges of using data is that it can pose ethical and legal risks, such as privacy breaches, data misuse, or bias. You need to use data ethically and responsibly, and to respect the rights and dignity of your data subjects. This means following the principles of data protection, such as consent, purpose limitation, data minimization, accuracy, security, and accountability. You also need to follow the principles of data justice, such as fairness, inclusion, empowerment, and participation. Using data ethically and responsibly will help you avoid harm and ensure compliance.