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‘How do we do better?’ Chief data officers see hiring challenges persist

When asked to rank how much time they spent on a handful of certain analytics-related activities, respondents said they spent 23% of their time gathering data, and about 17% percent on “work not related to analytics.” Other top activities included analyzing the data (8%) and explaining the results of their data analysis (14%).

At the OMB orientation, which Conlin said included 50-60 data officials from across the government, chief data officers were given a presentation on a Harvard University study, based on data from both the Census Bureau and the IRS, that found a correlation between a person’s hometown and their economic mobility.

While the study aimed to demonstrate the value of combing disparate data elements from different agencies, Conlin said DoD is doing some “serious number-crunching” to see if it can build off the results of the study to reach new conclusions relevant to service members.

We’re looking at how do we bring that data, to merge it with data that we’ve got, and test not only whether we’ve had a positive impact of economic mobility … [but] can we improve the impact that we’re having,” he said during panel discussion.

“This is ultimately the question: How do we do better?” While the Evidence Act created new C-suite positions across government — CDOs and chief evaluation officers — and laid out new goals for agencies to meet, neither the legislation nor the Federal Data Strategy has given these officials new authorities or funding to fulfill their mission.

“That’s not a new challenge for anybody in government, it’s not a new challenge for anybody in any commercial sector organization either.” William Wiatrowski, the deputy secretary of the Bureau of Labor Statistics, said the Evidence Act has enabled “real pushes for agencies to share information where there aren’t restrictions,” but breaking down those data siloes remains a challenge elsewhere in government.

But in order to build that level of engagement in the agency leadership, Conlin said his team have held “literacy classes” for Senior Executive Service-level leaders that focus on basic data quality and descriptive statistics skills.

SBA, for example, has long employed statisticians who have worked on predictive modeling, but don’t fit the role of “data scientist.” “Data science is a more recently coined term, but I think a lot of the skills that can be used to draw insights from data, we have people that have been doing this work for a long time,” Knickerbocker said.

“But at the lower level of sophistication, where you just want someone who maybe has exposure to R and Python and you’re willing to do a little bit of training, we’ve had OK success.” One of the challenges is the lack of a federal job series for data scientists.

The first-year action of the Federal Data Strategy also addresses this data needs gap, and tasks agencies with identifying the skills they’ll need for data analysis, assessing current their staff capacity for those skills and then draft plans to address those skills gaps.

“A lot of the success that the Bureau of Labor Statistics has had in using machine learning and other analytics is some typically younger person saying ‘Why am I sitting here, day after day, going through this boring data and turning it into codes and publishing it?

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