Jennifer Bachner: Communication key for analytics leaders

[Click here to watch the video.]

(US and Canada) Jennifer Bachner, Director, Data Analytics and Policy Program, The Johns Hopkins University, speaks with Michael C. Fillios, Founder & CEO, IT Ally, about her career in data analytics and applying analytics for efficient law enforcement.

Bachner initially pursued her Ph.D. in political science to study public opinion on political behavior. She was exposed to analytics while using it to discern political behavior.

She points out that evidence-based policymaking is one of the most important uses of analytics. Over the last few years, government agencies have invested substantial resources in developing their analytic capacities, leading to improved government services and programs in various areas.

Accordingly, in 2014, Johns Hopkins launched a Master of Science in Government Analytics for professionals in the public and private sectors.

Bachner says that apart from good statistical analysis, analytics leaders need creativity and communication skills. She notes that a good analytics leader must communicate findings effectively.

According to her report on preventing crime with data and analytics, she says that police officers are using analyses correctly to forecast and prevent crime. However, data-driven approaches are not substitutes for the relationships and trust officers must build with citizens to create safe communities. They must also address privacy and security concerns as they develop and manage their data analytics capabilities.

Sharing her perspectives on the challenges of evolving government analytics, Bachner says that the Foundations for Evidence-based Policymaking Act of 2018 — also referred to as the Evidence Act — is one of the biggest change catalysts. It requires all government agencies to develop statistical evidence to inform policy-making and increase government data access.

One of the biggest challenges analytics leaders face is securing buy-in from organization leaders and employees who are skeptical about over-reliance on data. Another significant challenge she points out is resource investment.

She suggests addressing that challenge in three steps. First, leaders must demonstrate good stewardship with the resources given. Second, they must be specific and goal-oriented in their requests for resources and be clear about what tasks need to be completed. Finally, analytics leaders must retain qualified staff who can perform rigorous analysis and communicate findings clearly.

[This content was originally published on cdomagazine.tech.]