By Rich Majerus • December 7, 2016

Data-Informed Philanthropy Organizations


Fostering a data-informed culture in your advancement organization can be an arduous task. When it comes to adopting more analytical approaches to our work, I have learned that there are at least three data-requisites to creating organizational buy-in and to cultivating data-informed decision making:

  1. Quality - Is your data accurate?
  2. Coverage - Do you have (close to) comprehensive information on all of your constituents?
  3. Usability - Is your data accessible and presented in engaging ways?
I have come to think of these elements as forming the base of a multiplicative model of the prerequisites for creating a data-informed culture (i.e., Quality x Coverage x Usability). So, if any of these elements is zeroed out, you are out-of-luck. If you have made progress on each, then you have a shot, and the further along you get with each element the faster the growth of your data-informed culture. In the remainder of this post, I am going to focus on the third element, which may be the most relevant for Gravyty’s work (and is the one that I happen to find the most interesting).

I have yet to see an Advancement CRM that reaches the data-usability bar. From my experience, Advancement CRMs are adequate repositories of information that in their current states do a decent job of serving up the information that users know they are looking for. I have not seen an Advancement CRM that provides data and analysis that users can easily leverage to make data-informed decisions. I know (and hope) that this may change.

In the meantime, for advancement teams to develop modern approaches to data use and analysis, there are two general options: 1) roll your own, or 2) contract out. At Colby, we have gone with the former and have developed an internal web-based analytical-tool using R/Shiny. Gravyty, of course, represents an approach to the later option.

Both approaches have their own opportunities and obstacles a few of which are listed in the following two-by-two table...

  Opportunities Obstacles
Roll Your Own

No/low financial cost

Highly customizable to fit institutional needs

High labor/time cost

Vulnerable to losing developer(s)

Contract Out

No labor cost

Multiple clients — leverage scale and learn from other insitutions

Faster development cycle

High(er) fInancial cost

Multiple clients — you may not always be the top priority


Regardless of which approach you choose, it is import to think about how you can accomplish the following three objectives early and often:

  1. Engage your users with interactive data visualizations
  2. Demonstrate clear and compelling value through presenting users with insights beyond the raw information
  3. (Quickly) Improve user-interface to respond to needs

Meeting these three objectives will help you establish a base of daily active users within your organization. This group will be critical to cultivating a data-informed culture and to achieving universal adoption of any analytical platform.

If you are interested in trying to roll your own web-based platform I would be happy to chat with you. If you are looking to partner with a vendor, I would recommend demoing and comparing several, including Gravyty.

To contact Rich email him at rmajerus@colby.edu or visit www.richmajerus.com

bluish.jpgRich Majerus is a data scientist and the Director of Advancement Strategy and Analysis at Colby College where he oversees prospect research and develops new approaches to modeling and visualizing of fundraising data. He also serves on their campaign leadership and principal gifts teams.