Government has access to massive amounts of data, but what’s the point of all that data if you can’t take advantage of it? How should the data be stored? How can we sift through it all? What should we do with all of it? The answer is effective data analytical strategies. Which is why this month’s DorobekINSIDER LIVE: Understanding Data Analytics dived into how to best approach data analytics in government.
Dennis McDonald, Program & Project Planning Management Consultant, and Nicole Johnson, GovLoop’s Technology Writer, sat down with Christopher Dorobek to share their expertise and experience with data analytics. In the end, both experts agreed that now is the time for analytics.
“Analytics is what makes big data come alive. Without analytics, big datasets could be stored, and they could be retrieved, wholly or selectively. But what comes out would be exactly what went in-raw data,” Johnson said.
Have a Clear End Game
Without a clear objective in mind you may just get lost in all the data. “When your goal is to improve how you manage data and/or when part of your deliverable is some analytic service, you sometimes don’t know what you will find,” McDonald stated. He went on to explain that the more defined the objective is, the easier it will be for govies to achieve the desired outcome. Otherwise, “you can get lost in the architecture of big data. You don’t want to fall into the trap of paralysis by analysis.”
Johnson agreed that agencies need to have a set goal in mind when they approach data analytics. She shared GSA’s recent experience with data analytics. GSA realized they could better utilize data collected for human resources by centralizing it and, in turn, providing it as a service to other agencies. For example, in 2013, GSA noticed that there were less people being employed in the government. Through a clear outcome, they used data analytics and found that they hired fewer people at higher GS levels (with higher pay), which dried up their pipeline at the junior level. They then responded by implementing a program to fill the much-needed entry-level positions.
Once you have a clear objective in mind, make sure you work to get leadership buy-in. The best way to go about this is to try to tie it into one of the organization’s pre-existing initiatives, Johnson suggested. She shared an example in the case of Indiana. The governor was already focused on trying to deal with the opioid epidemic and his team was able to tie in the importance of data analytics into this initiative. As a result, his team reached out to public health agencies, coroners, and law enforcement, to gather data by county to find a solution to the problem. As the governor was already focused on this project, the team was able to build a case for data analytics and built momentum for its use in the long run. McDonald also agreed that regardless of the end game and format you chose, agencies need tie it into the organization’s management to show them some of the small-term benefits you could deliver. Therefore, govies must be able explain how your data will play a role in fulfilling an initiative in your agency/organization.
Lastly, make sure this is a collaborative effort across the agency. Once you have a clear objective and you have leaders’ buy-in you want to continue using data analytics for future needs. Consequently, it costs money to manage data and the best way to address the costs upfront is through open collaboration. “Addressing the cost is a really important issue because eventually you are going to realize you cannot address these resources in a silo-by-silo basis,” McDonald highlighted.
We may not have all the answers, yet, when it comes to data analytics, but through the support of leadership, clear objectives, and collaboration government can better utilize the data it collects. Otherwise, data will continue to be just endless research.
If you are interested in reading more stories about how various government entities are using data analytics, please find GovLoop’s latest guide, How You Can Use Data Analytics to Change Government, here.