Is an outdated procurement approach preventing federal agencies from becoming data-driven organizations?

Is an outdated procurement approach preventing federal agencies from becoming data-driven organizations?

by Jake Bittner

Over the past fifteen years, we’ve heard government clients, prospects, and partners pledge to become “data-driven organizations.” It’s an important goal that the federal government needs to prioritize. Becoming more data-driven would help federal agencies dramatically improve mission performance.

But becoming a data-driven organization takes more than a commitment to doing so. If public sector leaders want to truly realize the benefits of being a data-driven organization, they’ll have to rethink the procurement process and, ultimately, change how they structure their organizations.

Stephen Goldsmith, former mayor of Indianapolis recently said, “Government is organized vertically, but people live horizontally.” Government agencies are structured around doing things (e.g. issuing permits). Similarly, government IT departments contract to build transactional systems to support these services (e.g. processing and distributing permits). Since business intelligence and analytics capabilities are bundled into the same contract, the BI consists of a set of basic reports that only examines data relating to that individual service or transaction (e.g. how many permits were processed).

This outdated set-up and procurement approach leads to two problems. First, there’s an inherent conflict of interest when the same business unit manages both the system and the analytics measuring its performance. Second, bundling BI/analytics within the contract to build the transactional system prevents BI from looking horizontally across the organization, limiting the outcomes and thwarting any efforts to make the organization as a whole more efficient, transparent, or effective.

To become data-driven organizations, agencies must uncouple BI/analytics work from the transactional system contracts. Instead of building transactional systems and then plopping analytics on top of them, we must create a Business Intelligence unit that analyzes data across departments and enforces standards of analytics, so that any internal analysis is consistent, accurate, worthwhile, and valuable.

Qlarion’s work with the City of Boston shows how powerful BI can be when it’s separated from an individual system. Community Center integrated data from disparate sources into dashboards and reports that allowed city leaders to make data-driven decisions to directly improve citizens’ lives. For example, our “Problem Properties” dashboard, designed to make neighborhoods cleaner and safer, combined data from 6 data sources, including the Police Department, Neighborhood Development, and Basic City Services, and created a map to identify the most troubled areas of the city. With traditional, siloed BI, this data would have been analyzed separately, and probably never shared among departments. But the citizens in these areas don’t see their homes as pieces of data in several different databases. A complaint about a landlord, a crime report, and a request for a streetlight repair fall into the same category for those citizens: community safety. Our dashboard looked at the data from this perspective. The result? A 63% reduction in calls related to troubled addresses.

We should be focused on getting the best answers to improve the efficiency of programs and impact the lives of the people the government serves. The only way to accomplish this is to rethink the procurement approach, separate BI from the transactional system contract, and look at data across the organization to ensure that our analysis leads to real-world solutions.

In the next few weeks we’ll be writing about how we can make this necessary shift happen by building BI Centers of Excellence. In the meantime, share your thoughts with us on Twitter by tweeting @qlarion.