The Low Income Investment Fund (LIIF) and Enterprise Community Partners (Enterprise) are partnering with Living Cities to better understand how to preserve affordability and diversity in high-opportunity, transit-accessible areas, and we’ve turned to Big Data to help us answer this question.

This is the third in a series of four posts about how to navigate the realm of data, big and small, to connect low-income people to the jobs and amenities they need. Read Blog 1 and Blog 2 in the series.

What do you do when valuable information is held in people, not data files?

Human knowledge is just as valuable, if not more, than the scores of data sitting in data warehouses. As we dug deeper into our research, it became very apparent that the people on the ground were critical to providing otherwise unobtainable background information, local context and insights about how our research would plug into existing efforts in the region.

For our project, we chose to focus on transit-rich neighborhoods where we believed rents were increasing but naturally occurring affordable housing still existed. After facing the challenges we discussed in yesterday’s post, we realized that we weren’t going to find comprehensive or current rental data—especially for properties with less than 50 units, which is the stock we expected to still be affordable—to help us chose our case study locations, so we reached out to our local connections in each city. These individuals were part of local branches of our national offices, local and regional governments, collaborative tables, affordable housing developers and local brokers. These people have made it their job to intricately understand the places in which they work, so they were already thinking about how gentrification is moving through their region at a larger scale.

People like Heather are instrumental in providing context and background information that those working outside of the region may not have.

For example, Heather Hood, senior program director with Enterprise’s Bay Area market, lives in Oakland and has spent the last seven years of her career working in the Bay Area community development space. When we needed to identify a case study neighborhood in the Bay Area, she quickly stepped in, offered her local perspective, and volunteered to ground-truth our preferred neighborhood by spending an afternoon driving around the area. As a result of her insight, we were able to select an area along International Boulevard in Oakland, California that was meaningful to both local residents and practitioners as our case study neighborhood. People like Heather are instrumental in providing context and background information that those working outside of the region may not have.

With Heather’s knowledge, we were able to understand the social and cultural dynamics involved in the patterns of neighborhood change. While finding the data to back up lived experiences and perceptions of neighborhood change is difficult, relying on local staff and community members for their expertise offered information and a comprehensive story that was unavailable in the numbers alone.

Balancing quantitative data with qualitative knowledge is incredibly important to creating a holistic understanding of a place.

Balancing quantitative data with qualitative knowledge is incredibly important to creating a holistic understanding of a place. We imagined our research would be heavily reliant on data, and through our process found that we still needed qualitative, human input to produce meaningful work.

Now that we’ve covered quantitative and qualitative data, our last blog post will be looking at how to improve the ways we store and manage our data so as to not reinvent the wheel every time the community development industry conducts a research project. Follow along on social media with #ConnectUS!


Special thanks to Erin Austin for her contributions to this blog post.

Photo: Sound Transit System Map by Oran Viriyincy, Flickr. CC by SA-2.0.