How to Build Your Organization’s Data Muscle

Mayor Peter Saenz of Laredo, Texas, faced a conundrum in the summer of 2018. Despite a booming economy, low unemployment, and rising land values, Laredo consistently ranked among the poorest cities in the nation, with nearly three in ten residents living in poverty. ¹To help, graduate student Santiago Mota collected data from various city agencies to create “heat maps” identifying local conditions (such as single-parent households, income levels, health concerns, and transportation issues), block by block, that could be driving poverty. Mota found that residents of Laredo’s downtown had benefited little from the city’s economic boom. During regular briefings on the project, he discussed his findings with city officials, who planned to use the maps to understand the situation and resources needed in specific neighborhoods and identify which efforts were making a difference. The maps also became part of Laredo’s Open Data Project, which allowed residents to access findings and carry out their own inquiries.

It wasn’t fancy new technology—or even Mota’s technical expertise—that made the difference in Laredo. Instead, it took a mayor who nominated the issue for action and created space for using data in new ways. It also took departments willing to collect and share information, and staff prepared to ask questions and make data-informed decisions. But how do organizational resources and individual skills add up to real capabilities for solving urban problems? Our study in Data & Policy investigates the patterns of behavior that allow groups of people to use skills and technology to generate insights from data and apply them towards better results. Unlike technology or technical skills, data capabilities cannot be outsourced. As one city official in the study noted, they must be built internally, “like a muscle.” The study also shows that leaders play a critical role in boosting their organization’s data capabilities by creating the space and conditions necessary for data-informed work.

Comparing Data Capabilities Across Three US Cities

To better understand what shapes the development of data capabilities, we interviewed members of three cross-departmental teams selected from nine US cities. They were participating in a two-year program to address property distress and abandonment. Teams were selected based on their level of success in using data to tackle the problem at hand, as evaluated by two program managers who worked closely with all nine teams. Since all teams had similar funding, technology, and technical assistance—and since all faced a similar challenge—the approach allowed us to examine how differences in team capabilities (rather than resources or expertise alone) related to outcomes.

Our analysis revealed the key factors associated with teams’ ability to leverage existing skills and resources towards a better use of data in tackling the challenge at hand: processes or formal practices related to data use; routines or established patterns of actions across group members; and team members’ attitudes or level of enthusiasm regarding the value of data in how they approach and carry out their work. We also explored the role of leaders in building organizations’ data capabilities. We found that mayors can make a critical contribution to effective data use by serving as role models and removing roadblocks. Senior managers can also help by selecting the right team members, securing resources, and keeping up employees’ motivation.

The highest-performing team had formal processes and routinized behaviors around data use, including tracking systems, reporting protocols, weekly data-centered meetings, cross-functional “show-and-tell” sessions led by a senior department leader, and regular check-ins with the mayor, who habitually requested data to track progress on projects and was described as a “source of inspiration.” The lowest-scoring team, on the other hand, took an ad-hoc approach, with no regular data meetings and no formalized process to collect and share data within the organization. The team relied on outside vendors for many data-related tasks.

Building Your Organization’s Data Muscle: Takeaways for City Leaders

The study identifies four takeaways for local leaders looking to strengthen their own organizations’ data capabilities.

1. Focus on the problem first
   Put the challenge front and center; then ask what data you need; then see what technology, skills, processes, and behaviors are required to use data effectively.
2. Invest in building routines
   Talent and training are important, but so are regular data-informed meetings, protocols, and other practices that make data use a lasting habit.
3. Build capabilities in-house
   Invest in your organization’s in-house “data muscle,” and don’t fully outsource the capabilities you need to make data-informed decisions. Vendors can supplement.
4. Cultivate data champions
   Ask questions that need data-based answers and build a culture of curiosity. Hire, retain, and reward data enthusiasts who grow the data muscle.

Endnotes

¹Christina Pazzanese, “A Summer of Service to Cities: Mapping Patterns of Poverty in Laredo, Texas,” The Harvard Gazette, September 25, 2018, https://news.harvard.edu/gazette/ story/2018/09/harvard-fellows-help-mayors-improve-lives-through-bloomberg-partnership/. The subsequent details in this paragraph also draw from this article.