What We Learned

Through this process, we learned that while there are numerous quality data sources available, we often lack the capacity to turn these numbers and charts into something meaningful. However, the skills and ability necessary to make it happen are available (as the Data Dive weekend demonstrated) – we just need better ways of tapping into the expertise and to decide as a sector that using data for the greater good is indeed a priority. Here are some of the most important lessons we learned in this process:

• Ask for Help - There are a number of data scientists available who may be willing to assist your organization in sorting through your data, but you must be willing to ask for their help. Promote data analysis and visualization as a volunteer role or ask organizations who have people with these skills for pro bono help.
  
• Search for Data Sources in Unusual Places - How many people retweeted something you posted on Twitter? Does the U.S. Census have information that may be helpful to you and your organization? You may be overlooking existing sources of data that could help you meet your mission. Think critically about your data question, then be open and creative in finding ways that will help you answer it.
  
• Make Using Data for Decision Making a Priority - Leaders in your organization must agree that using data in decision making is a top priority. You won’t always need an excel spreadsheet or results from 50-word questionnaire, but your organization must be committed to finding ways to incorporate data into the decisions made by your team.
  
• Data as Product – We often think about data solely as input into our programs or as part of how we evaluate and understand performance. What we also need is a mindset that understands data as a product in the social sector; namely, how through our actions and programs we’re creating data that provides public value. Think of the information public health programs have on individual behavior, or the insights crisis hotlines have on troublespots in communities. The challenge for us is how we create an information architecture in the social sector that helps nonprofits understand the value of the data they’re collecting, and freely share and remix.
  
• Building a Pipeline of Talent – The ability to understand, visualize, communicate and use data will be a critical next generation skill for individuals in the social sector as we move into the era of big data. As a sector, we need to be developing people that have these skills, and attracting new talented designers and data scientists into the nonprofit sector. Informal events, such as the Data Dive, provide early opportunities to start creating the bridges and relationships that will help drive future innovation in the use of data to advance the effectiveness of the social sector.