When people hear the term “data science,” they think of how insight from data analytics is being used to create new technologies, target ads to consumers, and maximize profits and sales in business. However, data science and analytics can serve another purpose – one that sparks social good.
To learn more, check out the infographic below created by Maryville University’s Bachelors in Data Science program.
What is Data Science for Social Good?
All types of organizations can use data for social good. Nonprofit organizations have a particularly strong interest in getting the most out of their data.
What is “Data for Good?”
The “data for good” concept may feature one or several key characteristics. For instance, it could be the product of volunteers that create a data product for a subsidized rate or for free. It could also be representative of nonprofits or government agencies receiving the product. Additionally, it may be linked to tools for data work that are donated or subsidized. Finally, the term could associate with educational programs that build technical capacity in underserved communities.
Statistics of Nonprofits Using Data
In a survey of 460 nonprofit professionals, 90% said their organizations are collecting data, 46% said their data is spread across multiple systems and software platforms, and 50% said they use software to collect and analyze data as part of their email programs and donor management processes. In a separate Salesforce survey of over 450 nonprofit professionals, 53% collect program data, 47% analyze program data, 46% track the effectiveness of programs, and 41% quantify the overall impact of programs.
Applications of Data for Nonprofits
Nonprofits can utilize the data they source in a wide variety of ways. Some of these uses include tracking and analyzing nonprofit staff activity, streamlining operations, measuring return on investment, and identifying potential donors.
Benefits of Data for Nonprofits
There are several key benefits available for nonprofits that source data. These perks include an increase in cost efficiency, improvement to the budgeting process, strengthening fulfillment operations, and improving donor relations.
Data Serving People and their Communities
Organizations across the government, nonprofit, and private sectors use data to serve their communities and effect lasting change.
One of the more visible data-driven organizations is Change.org, a website that runs campaigns that aim to save lives and change laws. A second example is the Food and Drug Administration (FDA), which announced plans to utilize data analytics to combat the opioid crisis. Another example of data-driven organizations in action, Community Technology Alliance (CTA), was founded to develop data-driven solutions to poverty and homeless. The platform Ginger.io uses data to provide behavior health coaching, therapy, and self-led guides and assessments.
Another data-driven organization doing good is Qlik, a company that provides nonprofit organizations with data to make important decisions. Finally, the organization Data For Good was founded to help organizations and communities to create data-driven strategies to solve various challenges.
9 Steps for Nonprofits to Implement Data Analytics Tools
For nonprofits ready to implement data analytics tools across the entire organization, there are a few key steps that should be taken to get started. The first step is to identify potential analytics platforms and data warehouses. Secondly, it’s important to invest in technology that will best meet the organization’s data management needs. It’s also important to establish performance metrics and mission-driven indicators. Additionally, it’s vital to acknowledge and embrace the need for change when implementing the technology. Nonprofits should also encourage collaboration among departments during the process to help the organization operate as a whole. It’s also important to develop in-house analytics capabilities or hire qualified data analysts. Nonprofit organizations should also be prepared to commit to acting on data insights and trends. Additionally, it can be important to form a cross-functional committee devoted to acting on data insights. Finally, it’s important to make an organizations-wide commitment to an ongoing data analytics program.
The Real Winners of Data Competitions
Data science is a growing field with measurable benefits for organizations of all sizes and types. Though not all organizations can afford a data science team, data competitions are creating opportunities to attract qualified data scientists to develop solutions to social challenges.
Data Scientists & Data Competitions
According to the U.S. Bureau of Labor Statistics (BLS), computer and information research scientists earned a median annual salary of $118,370 in 2018. This high earning potential of qualified data specialists makes it difficult for nonprofit organizations to attract top talent. Because of the talent shortage at nonprofit organizations, data competitions have been developed to attract data scientists from across the world to solve social challenges. Data competitions appeal to data scientists for many reasons, such as getting the chance to learn best practices and advanced skills. Popular data competitions include Kaggle, Crowdanalytix, Drivendata, and Datakind.
Data scientists around the world are passionate about using their skills to develop solutions to social challenges. For nonprofit organizations, data-driven solutions may be just one data competition away.
BizTech Magazine, “Why Nonprofits Need to Implement Data Analytics Solutions”
Bureau of Labor Statistics, Computer and Information Research Scientists
Data For Good, “What Is Data for Good”
EveryAction, “5 Things You Need to Know About Nonprofits + Big Data”
Gartner, “Use Data for Social Good”
HealthITAnalytics, “FDA: Data Analytics, New Policies Will Curb Opioid Abuse in 2019”
InsideBigData, “Using Data Science for Social Good”
Salesforce, “Nonprofit Trends Report”
Tableau, “7 Data Competitions for Data Scientists and Analysts”
Towards Data Science, “Why ‘Data for Good’ Lacks Precision.”