Challenges to Becoming Data-Driven

This blog post is an excerpt from our Industry Perspective, Empowering a Data-Driven Government. To download the full report, head here.

Government agencies face three major challenges to becoming data-driven organizations: silos and lack of alignment, technology gaps and an inability to derive value from this data deluge.

The first major issue is a lack of alignment between the data government agencies are collecting and the objectives they want to achieve with that data. Organizations aren’t necessarily collecting the right information to meet the dynamic business/ mission environment of today. They are awash with digital information, but often aren’t sure how to organize it or even what to do with it. Furthermore, agencies are often working with data in disjointed efforts and siloed departments, so not everyone can access the necessary information. “If you can’t match the types of information that are required to meet your mission, you’re going to have a gap, and that can lead to inefficiencies, increased risks and higher costs,” said Zavala.

The second obstacle is the technology gap between the analysis that needs to happen and the IT infrastructure that agencies have in place. Traditional systems and architectures do not have the computing power or scalability to process the variety of data at the speeds necessary to deliver actionable results. Agencies need to assess whether their IT infrastructure is up to par to perform real-time data analytics.

A third challenge is an inability to turn data into actionable information. This goes beyond technological capabilities, and touches on the personnel necessary to mine the data and turn it into something useful. In a recent poll, HPE found that 23 percent of government respondents said strategy and talent are the two leading areas that are slowing government from having a comprehensive approach to leveraging data.

Public agencies need to employ the right talent, as well as educate employees, constituents, end users and other organizations on the value of data analytics.