SF is spending big on homelessness. But I wanted to know where the money is going.

Back when I first started covering homelessness in San Francisco, I looked at what progress had been made to bring a newly created department into the 21st century by turning reams of paper-based records into digital files that would allow caseworkers to better track people they were trying to bring off the streets. 

At the time in 2019, I found the city hadn’t made much progress in implementing its version of coordinated entry. This is a form of triage where people are asked very personal — and, at times, traumatizing — questions about their life circumstances that led them to live on the streets. 

I originally wanted to look into this system with a special emphasis on equity issues for the Data Fellowship. 

Anywhere from 45% to 50% of San Francisco’s unhoused population is Black, despite the fact that they made up only 5.6% of the city’s overall population. I wanted to see what percentage of unhoused Black residents were getting prioritized for housing, among other things. 

But my senior fellow pushed me to take on a different project that would allow me to use the advanced Excel skills she was going to be teaching me. Better to look at how the city’s homelessness department was spending or a related measure that would still hit a major theme of my project: accountability of a city department with a big budget that had no formal oversight. 

Homelessness had exploded in the pandemic, as did the need for all types of shelter and housing — transitional and permanent. Money was flowing into the city from federal and state sources to help cover expenses driven by the public health emergency, particularly shelter-in-place hotels. There was also money to fuel recovery, some of which allowed the city to purchase hotels and hostels to convert to shelter and housing. 

Where was all this money going? That question led me to look into the contracting practices of the city’s Department of Homelessness and Supportive Housing (HSH). 

San Francisco’s homelessness agency depends heavily upon a network of over 50 nonprofits to carry out its mission of getting unhoused residents off the streets and into housing and services.

That’s because it spends only 5.3% of its overall budget on staff salaries and benefits, compared with the citywide level of 45%, according to the Office of the Controller.

Since just before the pandemic, the department had been leaning heavily upon a shelter emergency ordinance allowing it to bypass any preapproval process through the city’s legislative branch to issue no-bid contracts for shelter and housing. This would cut down on the time it took to bring units and services online to help people. 

San Francisco is a “housing first” city, meaning it emphasizes bringing people into shelter and then offering services to help them with issues including mental illness and substance abuse. It treats housing as a form of health care. So anything that expedites the availability of housing and shelter is considered a boon to the city. 

Except that all of this has happened against a backdrop of a major corruption scandal resulting from an ongoing federal investigation that has taken down San Francisco officials like a slow-moving cascade of dominos, all tied to donations from and relationships with city contractors. Neither the homelessness department nor their contractors have been involved or implicated, but with no formal oversight, shoddy contract management, and personnel turnover, it was very much worth looking into.

Through my training in the fellowship, I gained the confidence and skills to look into large datasets and ask pertinent questions. I interviewed my data, as my senior fellow often advised us to do. 

I looked at both the no-bid contracts and who was benefiting the most from this practice, and used my newly learned skills to clean up data and analyze it to determine who were the top recipients by amount, as well as by percentage of total contracts. 

Two of the city’s biggest contractors in terms of money overall were among the top. But so was a relative newcomer nonprofit, one that had been tapped to be a part of a controversial program in our city’s Tenderloin district — a quasi-security guard force that wasn’t the police. 

I was torn at first on where to throw my public records requests and investigations. I was bound by a time limit of the fellowship as well as resources. As a writer for a small publication, I was an investigative team of one. My editor was very supportive, but he had lots of writers to manage. 

We decided it was best to focus on the newcomer nonprofit when looking into the no-bid contracts — and it proved very fruitful. My public records requests turned up a lot, both in terms of their conduct as a manager of some of the city’s shelter-in-place hotels and the terms of these contracts. I was also able to find similar patterns of behavior in a few other cities where this relatively new nonprofit was also trying to operate.

In the end, I wound up with a two-part investigation into the no-bid contracting practices of our city’s homelessness department and the conduct of the nonprofit in San Francisco as well as in other cities.

As I fact-checked the pieces, I downloaded the latest data on contracting and discovered the formatting for the data had changed so much that it was hard to analyze in Excel. I tried every trick my senior fellow had taught me. Then I realized it was beyond Excel. I got some help with a script written in Python, and it did the trick of making the data readable and analyzable. 

Because of the nature of some of the information I’d found through public records requests, my editor and I knew we needed to get some legal review. My senior fellow suggested a couple of places, and we were able to get a pretty quick review. It was helpful and reassuring to know we were in good shape with the data, the documentation, and how we were representing some of the issues.

The Data Fellowship training gave me so much confidence throughout the project in terms of organizing a major project, analyzing the data, and great advice on how to represent the salient points in prose as well as in graphics.

I was especially grateful for my senior fellow, MaryJo Webster of the Star Tribune, who made herself available for reviews of drafts of the stories. The program is really dedicated to supporting reporters throughout the process of putting together a major investigation.

I have to say I’m ready to level up to other skills such as R and Python, and I feel completely prepared to use my skills in future stories.