How we took a crucial inner-city programs from data scarcity to data abundance

Last year, funding for our Winter Emergency Response (WER) program was in jeopardy.

The program, which allows to keep our doors open and help Edmonton’s most marginalized fend off winter’s bite, had poor data. Though just as busy, we reported a 50% decrease in visits from the year before; in those visits we were missing 57% of the demographics necessary for reporting. We needed a change, fast.

In just a few months between funding cycles we completely turned our data around. With a new approach and technology, we more than doubled our reported visits while eliminating all 57% missing demographics. With our accurate data now available on demand, we developed a one-of-a-kind live data visualization advocacy project that has been covered in the Edmonton media. So how did we go from lagging to leading? Our change can best be described as an emphasis in what we like to call “data ergonomics.”

What is ergonomics and how does it apply to data?

Ergonomics is concerned with designing and arranging people and their tools to increase effectiveness and efficiency by improving the ways in which people interact with tools by minimizing technological, physical, or organizational pain points. In this case, we completely redesigned our data process: which data we collect, where we store it, and how we access it.

Staff are averse to bad ergonomics, not data

We see data as story-telling. An important assumption to data ergonomics is that staff have an intrinsic motivation to represent the important work they do. This motivation fails when a data-system…

1) is overly bothersome

2) feels meaningless because collected data is not used

By enhancing the ergonomics of data entry to address 1) and data visualization to address 2) we can generate staff buy-in naturally.

To help visualize how data ergonomics can be considered in our sector, lets divide the data process into 3 main elements:

 

Where collection is how data is collected and entered, architecture is process of storing the data, and visualization is how the data is seen.

Database administrators know the importance of designing database architecture, but often accept the “default” methods of data collection and visualization. When carefully integrated with people and environments, the design of collection and visualization can have profound impacts on program data.

Out with the old

Our previous data was managed by a ‘Web-based Case Management System’. Though it handled the architectural element of data well enough, customization for collection and visualization was limited.

In searching for software that would be able to fulfill our dreams of great data-ergonomics, we decided on a group of Microsoft products that are deeply customizable and communicate well with each other. Microsoft offers significant discounts for non-profits to use this technology (around 80%) which lets organizations like ours adapt the latest in business technology to our mission. Though monthly upkeep license costs are only $50/month, the system does need to be custom-built and consultants in this space can easily charge $125/hour. Over-the course of ~6 months, we had a tech-savy employee with a background in software and UX design develop our solution in-house, learning as they went.

We implemented the new technology into each element, as can be seen in the updated model below:

 

Architecture

Designing architecture requires a delicate balance between funder desires, organizational desires, and reality. In reviewing our practices, we found we were collecting information that wasn’t being asked for. We collected data that gave us a sense of unique visitors and demographics over months, while the funder was asking only for data tallied daily. In theory, our collection method should have covered both the funders needs and our curiosities, but in reality, it was a mess.

We began to streamline our practices. What resulted was a “daily visit” approach to our program’s data. With this approach, we entered demographics for each community member’s first visit and marked subsequent visits as “return visits” with no demographics. This completed all funding requirements and provides extra data about our building’s flow, something Boyle Street has been curious about for a while.

The web-based system’s architecture could be designed to fit this approach, but it couldn’t save data as fast as people were entering our building. Because of this, we moved to a system with better options for data entry: Dynamics 365.

Collection

One of the most immediate ways to improve ergonomics is to eliminate the redundant data-work created by a “paper-first, database later” approach. In combing data collection and data entry, we went from the data collection sheet below:

To the following PowerApp:


PowerApps, the underlying technology, is a fantastic way to quickly build custom data entry experiences. In the hands of a pro, a data collection app can be made in a couple of days. Apps are accessed via phone, tablet, or web browsers: perfect for non-profits with a rag-tag assembly of technology. PowerApps talks with our Dynamics architecture easily. The technology is very new (released October 2016) but we’re very excited to see where it progresses.

Visualization

Now that our data is entered directly into the database, it becomes much more accessible and powerful. Dynamics has built-in reporting capabilities, but PowerBI allows us to make interesting and interactive data visualizations fast. Our Drop-In Coordinator now completes the funder’s report in mi.

With renewed confidence in our data we now use it to advocate for our community. Using the live-visualization capabilities of PowerBI, we created boylestreet.org/data, a transparent look at poverty in Edmonton’s inner-city automatically updated every day. We believe this is an exciting new way for non-profits to engage with community and funders in the information-age.

 

The lead for this project is David Woodruff, originally the Data Coordinator at Boyle Street, David now develops custom data-systems in the non-profit space.

Find him at datapunks.ca