The private sector has used predictive analytics for many years, but it is still not widely used in the nonprofit community. Yet, predictive analysis can be a powerful tool for nonprofit organizations to improve operations or program design to ensure that beneficiaries can be empowered more efficiently and effectively.
Welcome to the wonderful world of “big data.”
Predictive analysis is a tool that uses historical data and analysis to find relationships among different variables to predict the likelihood of future patterns. Analyzing the data can help to reveal insights related to beneficiaries, such as demography records, the type of development program they went through, and define the factors that create a better impact for beneficiaries.
Here are some critical areas where a nonprofit organization could make use of predictive analysis:
Designing development programs
Using the history of beneficiary progress tracking or monitoring, for example, via survey data, it is possible to identify which parts of the program create a better beneficiary impact.
Using the example of an SME program, we can extract common factors of the group of businesses that indicate a successful outcome over time. We can use this data to inform activities and create sustainable development for future beneficiaries.
Using algorithms to enhance programs
With good beneficiary data collection, it is possible to make algorithms to define the factors that differentiate groups of beneficiaries and identify those with the greatest impact. We should also be mindful that discrimination can occur with algorithms, as Betsy Anne Williams points out, “discrimination can occur in any socio-technical system in which someone decides to use an algorithmic process to inform decision-making.”
Using predictive analysis, organizations can justify supporting programs or activities by equipping beneficiaries with the necessary knowledge, technology, and skills, to produce optimum program results.
Recruitment of beneficiaries
Effective analysis will assist in defining target beneficiary profiles that have the most significant multiplier effect on indirect beneficiaries. Using the example of education programs, it is possible to define indicators that optimize student learning by segmenting data to identify suitable master teachers. By creating a persona, looking at the special additional activities master teachers attend, certified programs they obtain, or associations they are members of, and by recruiting the best master teachers it is possible to deliver and design more engaging programs to increase the multiplier impact to students. This information will help organizations focus on the ideal master teacher profile.
Post monitoring and evaluation to assure long-lasting program impact
Using mobile applications, tracking behavior change can make data collection more viable and applicable to all generations. With the accessibility of the internet and technology, after the program and monitoring and evaluation (M&E) has reported, follow-up programs can track beneficiary progress. Since true impact generally takes a long time to measure, consistent data collection practices can evaluate social impact.
The cornerstone of predictive analysis is robust data collection to identify patterns and insightful information to make realistic forecasts. Over the past 25 years, Kenan Foundation Asia has empowered more than three million beneficiaries. Kenan Foundation Asia is using the knowledge that data provides to benefit us all – and predictive analysis is enhancing our ability to reach more beneficiaries and empower people with the knowledge, technology, and skills necessary for a better future. Find out more here: www.kenan-asia.org/vision-and-values/
HR and General Administration Manager