Better Data, Better Decisions

In the Next Generation of Government Training Summit session, “Analyzing Data to Make Better Decisions,” Kirsten Dalboe, MGMT Cube Program Manager at DHS, and Gray Brooks, Senior API Strategist at GSA, shared their successes with using data to improve performance and efficiency.

Kirsten was the “data scientist” behind the DHS Management Cube, which integrates financial, human capital, contracting, asset, and security data on a common platform to produce comprehensive trend analysis, which will lead to better decisions, and ultimately a stronger Department.  Benefits include improved data integrity, the ability to explore trends and relationships across data sets, and improved collaboration.  Kirsten stressed the importance of:

  1. Leveraging existing initiatives and funding sources
  2. Regular meetings and constant communication
  3. Shared data, rather than a “need-to-know” basis
  4. Strong leadership support
  5. Involvement of all lines of business (builds trust and stronger collaboration)
  6. Patience

Gray is a member of Team 18F, a team of designers, developers, and product specialists at GSA, headquartered at 18 and F streets in Washington, DC.  18F partnered with the Digital Analytics Program (DAP) to create, a Google analytics account for federal government agencies which shows how people are interacting with the government online.  For example, what web pages are customers viewing?


Another 18F and DAP team effort was, which measures how federal government domains are following best practices for federal web sites.  Take a look at Pulse and see if your agency is (i) supporting the HTTPS protocol and (ii) participating in the DAP!


Do you have any data analytic projects that resulted in better decisions at your agency?  If so, please share with us in the comments section below!

From July 20th – 21st we’ll be blogging from GovLoop and YGL’s Next Generation of Government Training Summit. Follow along @NextGenGov and read more blog posts here.

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Mark Hammer

To this I will add my assertion that data is like soup. It is rarely enough to simply cook soup until the contents are gummable. Rather, it always needs to be simmered long enough to acquire a coherent flavour.

All too often, folks who work with data are expected to generate inferences from data before the soup is ready, or the folks they report to draw mistaken inferences, under the assumption that all you really need is the numbers. Insight, and the sort of pattern recognition that leads to it, requires time.

Always work with the data, but NEVER forget to give yourself the needed time to make wise use of good data. That’s where good decisions come from.