The Center for Data Innovation spoke with Melissa Schigoda, Director of the Office of Performance and Accountability in New Orleans, Louisiana. Schigoda spoke about the challenges and opportunities of municipal agencies using data to have a positive impact on residents.
Daniel Castro: Please tell me about your path to the Office of Performance and Accountability. What led you to pursue a career in public service?
Melissa Schigoda: Hurricane Katrina hit New Orleans during my senior year at Tulane and that had a major impact on my career trajectory. I studied international development and planned to work abroad, but there was so much work to do right here in New Orleans that I decided to stay. After interning at a neighborhood association network that emerged after Katrina, I got my first job at Tulane’s Center for Public Service coordinating service learning partnerships between faculty and community organizations engaged in rebuilding. From there, I went on to my first tour of duty at the City of New Orleans, as a Mayoral Fellow in the Housing Recovery Division.
After that, I worked at a local data think tank called the Data Center, which partnered with Brookings to track recovery from Katrina and provided data for decision making to policymakers, businesses, and residents. That’s when I really got interested in how people use data for decision making in complex adaptive systems and started my Ph.D. dissertation on the subject. I came back to the City as a Performance Manager in 2015, was promoted to Director in 2018, and I’ve been in this role now for four years.
Castro: You’ve led or partnered on a number of important data analytics programs in New Orleans, such as ResultsNOLA and ComSTAT. What has been the impact of these programs?
Schigoda: They’ve had a number of impacts depending on the specific program or project, but there are definitely a few common threads. They all empowered departments heads to speak with numbers about what they do, how much they do it, and how well they do it, which sounds very basic but was actually a huge win. Also, just making the measures and goals public and looking at them in monthly data-driven management meetings quickly led to a great deal of improvement. Then as time went on and the pace of improvement began to slow, we found that targeted analytics projects could be used to address some of the stickier problems departments faced like prioritizing backlogs or most efficiently targeting limited resources.
Castro: The NOLAlytics program partners with various city departments for analytics projects. What are the challenges of getting agencies to pursue new analytics projects?
Schigoda: The biggest challenges that we have faced with getting agencies to pursue new analytics projects are staff time and data constraints. A lot of city department staff are overextended and end up spending a lot of time putting out fires, so it can be a challenge to get them to carve out time to effectively partner with us on a project. We also still face data constraints in many areas. Sometimes the data we need for a project doesn’t exist, it’s not being captured in a way that’s useful, or there’s an issue with extracting it.
Castro: The public sector has always had some focus on performance management, but with programs like ResultsNOLA and ComSTAT there is a much greater emphasis now on data and analytics. How has this shift changed how cities approach performance management–both in the day-to-day operations as well as their longer-term strategic approaches?
Schigoda: The advancement of analytics has made many city department heads more open to performance management, because it offers a potential solution to some of the problems highlighted by their performance metrics. They don’t want to be held accountable to meeting goals that they don’t feel they are properly resourced to meet, but if we can offer assistance meeting their goals with analytics, that makes them more willing partners. City leaders see how Amazon and other private companies are delivering great service to their residents, which raises the bar for them. They want to get there, and they see that data and analytics present an opportunity to move in that direction.
Castro: How has the city’s focus on data and analytics helped it respond to the pandemic?
Schigoda: It’s been enormously helpful. Our mayor has taken a strong stance throughout the pandemic about following the data when it comes to making policy decisions about shutdowns, mask mandates, etc. At the beginning of the pandemic, we set up a public dashboard with key covid-19 measures like number of new cases, infection rate, positive test rate, and number of hospitalizations that she would point to during press conferences. This helped get everyone on the same page about how the city was trending and build support for making some tough decisions that ultimately saved lives.
Castro: What advice do you have for other cities that are just beginning their journey to greater use of data and analytics?
Schigoda: There are so many different paths a city can take on their journey. I think it can be helpful to start by assessing where you are today. What are your strengths, weaknesses, opportunities, and challenges when it comes to data and analytics? The What Works Cities criteria, the standard of excellence for data-driven local government, is another tool that can help you get a sense of where you stand compared to other cities in a variety of areas. If you’re trying to build buy-in for a data and analytics program, probably the most important thing is to be able to demonstrate a few quick wins and build momentum. People tend to get frustrated if they think you are peddling “data for data’s sake,” so make sure you’re able to show that your data projects are having a positive impact that residents can see and feel. Be wary of expensive technologies that claim to be able to solve all of your problems. They tend to only be as good as the processes they cement and the city employees’ ability to utilize and make changes as needed. Finally, look for opportunities to build a data culture among city employees. Not everyone will be running statistical analyses in R, but the more people you have thinking analytically about how they do they job and identifying opportunities, the bigger your potential impact will be.