Methodology

Given the challenge of data availability and access, and the talent and technology required for analysis, nonprofits should carefully consider when big data analytics is appropriate. When it is, the steps are:

  1. Identify an appropriate topic: Identify the key questions or critical decisions that could benefit from big data analytics (e.g., participant selection, prioritization of new geographies)
  2. Determine the available data sets and sources: This may include the organization's own data, government data sets, and data from other nonprofits, universities, or corporations. Clarify what it would take to access the desired data (e.g., completing a memorandum of understanding with a government department and adhering to privacy regulations, negotiating a nonprofit rate with a for-profit data warehouse). It is possible that the ideal data is simply not available, in which case proxies will have to be used instead or the desired data will have to be tracked and gathered over time.
  3. Decide on the analysis plan: Clarify exactly what analysis will need to be done to generate the desired insights, and what talent and technology is required to complete this assessment. Depending on the scope of the project, it may be possible to conduct the analysis with existing staff, or it may be necessary to hire an expert firm, a consultant, or a new staff member. New software may also be required, especially if the analytics are likely to be repeated regularly. Ensure that the analysis plan complies with relevant privacy regulations and the organization's ethical standards.
  4. Conduct the analysis and generate insights: Implement the analysis plan, and identify the key findings, reality-checking all insights using firsthand knowledge and expertise.
  5. Learn, share and refine: Decide how to change the nonprofit's programs or activities in response to the findings. Share the findings with other organizations that could benefit from them. Test and refine new approaches to create deeper impact.