I recently visited with DBI’s leadership and its chief data officer, Brita Andercheck, to better understand their progress and its implications for other cities. Andercheck’s agency creates value by extending data use and capacity throughout the city, breaking down barriers. These accomplishments come from increasing both the likelihood and the frequency of operating agencies partnering with DBI in solving problems and from increasing data literacy.
A system that relies on a highly centralized approach creates its own set of barriers. I first realized this issue early in my term as mayor of Indianapolis when I visited the city’s GIS official, who demonstrated his impressive set of resources. When I asked him about other city officials who possessed such spatial analytic skills, he brushed me off with what he meant as a helpful comment — that he “could handle all their requests.” His answer communicated good and bad news: We had impressive capacity, but a lack of broad-based use restricted the benefits.
A few years later, Indy became one of the first U.S. cities to put municipal services online, forming an “e-gov” team. After two years we recognized the same mistake illustrated by that GIS conversation: All government should be e-government; it should not be considered as an alternative approach dominated by a separate agency.
Which brings us back to Dallas. DBI’s office location within the structure of city government, its relationships and its responsiveness ensure that its work isn’t sequestered, and the benefits are experienced across the organization. While this may seem like something of a contradiction — advocating for a large data intelligence office while extolling the virtues of decentralized data usage — a close examination of how DBI operates reveals that broad, cross-organization improvements must be grounded in one place of data excellence.
Two of DBI’s main goals, defining and leading data governance and nurturing a team that can deliver high-quality services, are priorities that other cities should now consider table stakes. Without a team like DBI accomplishing those activities, cities cannot progress and will surrender opportunities for progress. Two additional DBI goals, enhancing data accessibility and cultivating a strong data culture, promise to produce true breakthroughs because of what they mean for the entire city enterprise. After all, the full digitization of city hall should facilitate, if not force, the use of data and analytics in every function of government, supported and catalyzed by an agency of experts but much more distributed in its use.
Additionally, defining and preparing city data takes on new importance with the emerging power of OpenAI and other generative artificial intelligence tools. Especially in a city like Dallas that has 900-plus data-source systems and more than 15,000 employees, providing access to clean, high-quality data is essential.
A Strategic Organizational Location
DBI is unique in its positioning: It is under the city’s chief financial officer, alongside the team that manages performance metrics and budget decisions. Analytics intricately connected to the budget process are most helpful when evaluating what works, quickly identifying problems, and redirecting resources to where and to whom they do the most good.
According to CFO Jack Ireland, including the data office in his portfolio results in more data-informed decision-making. “More and more our city manager is asking, ‘What’s the data on that? Show me the numbers,’” he said. “We are moving in the direction of elevating evidence in the decision-making process.” Ireland believes data and analytics are necessary infrastructure investments that should no longer be thought of as a case-by-case ROI decision but rather as part and parcel of every action and budget. Supporting Andercheck’s office in his department’s budget, he said, allows DBI to “be in a position to work across all of the operational departments.”
DBI ’s goal of creating and investing in a strong data culture starts with relationships — cultivating agencies as partners and clients. This involves a combination of outreach, learning sessions and training on data literacy. Andercheck leads the outreach through personal conversations with other department heads. “So many of these projects develop because I'm having coffee with the person, and they are explaining a problem,” she said, “and I can be on the lookout for an operational problem occurring and say, ‘What if we get in front of it this way?’ You've got to be able to hear a non-technical problem coming at you and convert it into how I could solve for that.”
DBI’s large internal capacity allows agencies to depend on it in times of crisis. Unlike a consulting firm, DBI does not lose months to a procurement process and onboarding, and it can support an emergency operations center almost instantly. “We talk to our counterparts in the other departments without using jargon,” Andercheck said. “No department director has ever called me and said, ‘Brita, can I have a linear regression?’ They don't know what that is. What they know is that they have operational problems.”
‘Dream Sessions’
Cultivating relationships and communicating the power of data also derives from what Andercheck calls “dream sessions”: “We bring a department director in here, have a group of our people around and say, ‘Don't worry about what is possible. If you could know X that would make your life better, what would that be?’” The relationships flourish because of constant effort, from both informal exchanges and more formal biweekly meetings among senior staff that allow a review of progress and identify new demands, whether in emergency response, building inspection or even the location of smoke detectors.
Scott Pacot, deputy chief of Dallas Fire-Rescue, illustrates the success of the DBI outreach and relationship model. Agencies, and in particular uniform agencies, often are apprehensive when they don’t control all of their data services internally. Dallas Fire-Rescue first developed its synergistic relationship with DBI in response to a major tornado when it needed instant analytic capacity. As Pacot explained, “Having that information readily available [in the tornado response command center], with maps and dashboards of the recovery progress in every aspect, from tracking calls for service to coordinating responses, proved invaluable.” DBI’s spatial analytics capacity particularly enhances its value to the agencies.
The Dallas story shows a path forward for government operations. Cities such as Nashville and Dallas lay out a path for city halls to become data-driven enterprises, producing better results per dollar spent for their residents.
Governing’s opinion columns reflect the views of their authors and not necessarily those of Governing’s editors or management.
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