Making the most of your data

Data and analytics used to increase impact for non-profits

Geoff Zakaib from Data for Good shares how non-profits can increase their community impact. Here, in part two of our interview: where to begin, where you can find outside data to supplement your own, and when it’s time to engage outside IT and data expertise.

Geoff Zakaib is a Board member and the Calgary chapter lead for Data for Good, a volunteer-driven, Canadian non-profit organization dedicated to improving life in our communities through better data use. Part of their work involves showing non-profit organizations how effectively collecting, organizing, analyzing and sharing their data can generate insights that lead to increased impact.

You can learn about Data for Good at https://dataforgood.ca/ 

You can find information on the Calgary chapter at https://www.meetup.com/Data-for-Good-Calgary/ 

Last week, we talked about how data helps you determine ways to increase your community impact.

I think it ultimately comes down to impact. “What is the impact that they’re having in the community? is a frequently asked question. But to answer that question, you need to make evidence-based observations and decisions. Data is the foundation that leads to insights about your organization, how you are doing. Are you delivering your services efficiently and effectively? Who else out there is doing similar work? Are you engaging broadly with the community and society? There are a ton of questions we can ask and answer through data to help determine your impact.

One challenge is making sure you have a comprehensive organization-wide approach to data collection.

Yes. It’s the unspoken aspect of all this stuff around the power of data, analytics and digitalization, AI and all that stuff. It’s that old adage—garbage in, garbage out. And so in those very early phases on deciding what data to collect, how to collect it, what infrastructure you’re using, who’s doing what to make it into data, quality is extremely important. It’s often overlooked and it’s the reason why many of these initiatives are not successful. We find out that, yes, you’ve got data, but it’s junk and you can’t analyze it. For example, in capturing info about a program, there may be gaps in the data you collected, perhaps some entries in a spreadsheet have incomplete fields. Before we begin, we do a quality check, how many fields are complete, etc.

Do you have to rely solely on the data you collect yourself?

No. You can use your own data, but you can also combine it with external data sources.

For example, by looking at Canadian statistics and other population-based data such as neighborhood data, an organization can potentially see areas they aren’t currently serving. So now you’re in a better position to ask “How can we extend our services, how can we reach out to more individuals?

Where can non-profits look for that type of information?

There are tons of what’s called “open data” from the City of Calgary, the Government of Alberta, Government of Canada. There’s also a lot of other data sources that are available—economic data, social data, data from elsewhere.

When should you engage Data for Good? When should you seek help with other full-time professional services?  

It really depends on the scope of your challenge. We’re data professionals but we are a group of volunteers, so we cannot commit to a project that’s going to require 40 hours a week for six months. We tend to focus on the use of existing data, get involved more on the analytics and visualization and trying to draw insights from the data. So if you’re having challenges with your back-end IT infrastructure, getting data into or out of your CRM, your volunteer management system, or you need to do some back-end integration, that’s not the kind of project that we get involved with.

Last week, we discussed why non-profit organizations need to enter the world of data-management, analytics and visualizations to thrive. We also discussed initial questions to ask when you sit down to do the work. Read Part One here: Data for Good Part 1

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