Free Tools and New Ideas from the 2017 Nonprofit Technology Conference (Part I of III)

Nonprofit Technology Network Logo

Nonprofit Technology Network Logo

The Nonprofit Technology Conference (#NTC17) met in March in Washington, DC, the headquarters of all nonprofits.  The conference was vast with inspiring keynotes and information-filled panels.  The following is only a sampling of what was available and reveals my passions and interests: Data, Diversity and Communication. If you want to try to get a sense of the greater paths for the conference, check their social feeds @ntenorg and #ntc17. A list of the plenaries and panels attended is at the bottom of this post.   Today we focus on data: collection, interpretation and dissemination.


Data is power and everything can be data; therefore, data is often overwhelming.  Thus, it is crucial for organizations to take time to prioritize the data they collect.  With all possible data streams coming into an organization, how can a director of marketing, programming or IT cull to the critical mass?  A place to start is to identify the data aligned with your organization's strategic plan's goals.  How will the organization know if it has accomplished its goals?  You can also take time at the beginning of each planning cycle (organizational or departmental)  to evaluate your intended outcomes and goals then identify the necessary data. This is easiest, of course, if your programs are driven by logic models, but if not just ask yourself why you are doing the program. What will it accomplish and how will you know?  Data in an institution breaks down into 3 stages:  knowing what data to collect, how to interpret it, and with whom to share it. 

Critical to understanding how to collect data is understanding what you want to do with it afterward?  If the organization knows X, what will the organization do differently? Additionally, how can you visualize your data to best understand and interpret it? Two excellent examples are the Southern Poverty Law Center's Hate Map.  Here they use standard data and geographical visualization to share.  They share it with the intent to bring light to the subject and help those for equity to understand the geographic and typographic levels of hate across the USA. 

Southern Poverty Law Center's Hate Map (

A second example reveals how to collect and display data in a visceral, physical form.  Johns Hopkins University wanted to understand the level of food waste on campus and share it with the students to help them know the result of taking too much and throwing away food.  The data was food.  Students were asked to put their leftover food into tubs they could see.  The change was to get rid of trays so students were aware of the quantity of their food choices.  This endeavor was part of JHU's "Know Your Foodprint" initiative. 

Once the data is interpreted, organizations need to share results broadly to all relevant stakeholders.  In the food waste example, the containers of leftover food were left in the dining hall for the students to see.  In the example of the Hate Map, the Southern Poverty Law's web site and communication pathways share the data with the world.   

Transparency is the driving theme in data collection, interpretation and sharing.  All relevant stakeholders should be shown the results, including the subjects of the data collection.  If an organization asks for feedback on a program, the feedback should be shared back.  If executive staff asks for information from the staff, the results should be shared. For example, one institution created an online "post-mortem" to the institution's activities.  In a Google form they asked "what have you learned from doing X?" and "Who in the organization should know about it?".  The results are shared, live, with the entire organization on a google drive document. 

As demonstrated above, high-forms of technology are not needed for data informed decision making.  The key is:

  • Intentionality
  • Plan for sustainability
  • Accountability to mission

And, transparency.  Remember to complete the feedback loop:  Gather data, interpret data, articulate resulting action plan, implement, share change, back to gathering data. 

Coming soon:

  • Part II:  Storytelling: How It Matters 
  • Part III:  New Tools and Methods for Effective Communication