Shh! Don’t tell anyone, but you are a data company

I still recall the look on her face when I said to the executive director of the non-profit, ”well if you are using a medical record system, you are a data company.”

She was taken aback. Yes, they have systems in place to manage appointments and capture the interactions with their constituents as well as manage their resources. However, they were just starting to analyze and use the data to improve their operations. Their only interaction with the data they had was canned reports from their systems and a few one-off spreadsheets. No one in their organization spent much time on the data. When they had a question, they would ask their team what they thought and try to kludge together something from disparate opinions and what little data they understood. It was enough to get by, but it was an uncomfortable conversation.

She responded, ”I know that we should be doing better, but we just don’t have the people, time, or systems to be a data company. What you are saying really is not us at this time.”

And that’s the problem. Many non-profit organizations don’t realize the value that their data holds, so they leave so much on the table.

So, I set-out the following logic for her:

First of all, we talked about the questions and challenges she gets in her role. She, like many non-profits, is dealing with three fundamental issues:

  1. Donor retention
  2. Board expectations
  3. Mission impact

We talked through why donor retention is so difficult. The biggest challenge is getting donors to continue to engage and increase their giving. Donor hesitation comes down to understanding the impact of their donation on the mission. While there may be anecdotal testimonials, impact at scale is inextricably tied to the data within the operation.

Hers, like many boards, is well-intentioned but not grounded in the day-to-day operations. Board members tend to come from large organizations where they rely on data to get insights into the performance of the non-profit. Therefore, the core processes and systems should be the catalyst for such conversations.

The most important factor for any non-profit is its ability to execute its mission. There must be a focused effort to understand the constituency being served and how the organization is making a measurable impact. There must be a way to capture these signals and show outcomes.

Now, in her case, they have a core system that actually collects data that can be used for these and other questions. As we walked through her situation, I probed how her current system could be used to answer those questions. Her tone moved from skepticism to optimism. We arrived at “yes, I think that is possible.”

Great news, but how do we get there?

We talked through the challenge: we may have the systems, but we don’t have the people. That’s where I introduced the concept of a data product. 

DJ Patil is known for defining the term “data product” in his book Data Jujitsu: The Art of Turning Data into Product. He simply states that a data product is “a product that facilitates an end goal through the use of data”. So, if we have the data in the system, then we simply need to find a way to make that data available to those who need it for their goals.

She agreed that she has the type of data that is needed to address her challenges and others’ needs. We talked about how data products could be created from her systems to fulfill the requirements. In our conversation, we arrived at some simple and attainable starting points:

  1. Develop a simple list of questions to answer (e.g., who do we serve, how do we serve them, how much does it cost)
  2. Determine what data could answer those questions (i.e., what data can we pull out of our systems)
  3. Provide access to the data to answer the questions (e.g., reports, exports, data feeds)


In hers and other examples, something is better than nothing. Even a simple summary report may be enough to get started. The data and the report are, in fact, data products. Over the weeks that followed, we looked at the system’s data and extracts that addressed her needs. We then looked at which parts of the data could and could not be shared (think: personal data) and how it could be represented. We then crafted distinct reports for her needs and shared them as needed.

Going forward, her team is responsible for the processes that create the data, such as the intake process, and the quality of the data in the source system. A shared team manages the data product in terms of who can access it as well as updates and maintenance. The Asgard Data team works with them to help make sense of the data and explore ways to productize it for internal and external stakeholders.

Does your organization have a similar challenge? Try our assessment. It will help you gather your thoughts. We are also available to answer your questions, share more about this and other customer stories, and get you started on your own journey. Let’s set up a conversation.

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