How it's used

Big data analytics can help nonprofits make better decisions about the most effective way to allocate their scarce resources to maximize social impact. For example, big data analytics could be employed to:

  • Generate insights about the behavioral patterns of beneficiaries and how they use programs and services. Then use that insight to allocate resources to the beneficiaries or geographies with greatest need, which can be determined using methods such as collecting and analyzing hotline data both for immediate response and large-scale pattern recognition (Global Human Trafficking Hotline)
  • Target new programs or services at underserved geographies or unmet needs that can be identified by, for example, integrating emergency response service and labor statistics data to locate neighborhoods with a high need for new services (Buffalo's Operation Clean Sweep)
  • Increase response rate to disasters and emergencies by employing techniques such as using GPS data to identify population movements after catastrophes (2010 Haiti earthquake response)

Big data that is useful for nonprofits is most likely to come from local, state, or federal government databases relating to education, public assistance, health, criminal justice, or transportation systems. Increasingly, however, social entrepreneurs are using more newly available sources such as social media interactions, consumer transactions, GPS data, weather, and traffic patterns. In many cases, important insights can be gained by linking previously separate databases (e.g., identifying parents involved in the criminal justice system and targeting their children with education support services, or using student performance data to rate teacher training programs).

Though there are many barriers to overcome in the social sector (e.g., lack of coordination, unreliable or inconsistent data, privacy concerns, underdeveloped data-processing systems, insufficient talent, scarce resources), there may be an increasing number of significant opportunities for the social sector to take advantage of big data analytics.