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IBM Survey: Too Much Data in Public Sector Stymies Effective Analysis

An overwhelming amount of data was cited by public-sector executives as the main driver for increased complexity.

Public-sector leaders struggle with overwhelming volumes of data and have difficulty effectively analyzing it, according to a new study by IBM’s Institute for Business Value. The study, released in March, addresses the value of analytics and why analytics discipline should be implemented in management practices in the public sector.

The Power of Analytics for Public Sector surveyed 100 leaders in federal, state and local governments, and non-governmental and nonprofit organizations worldwide. The public sector has seen an “information explosion” in recent years, the report said, with more information available today than ever before.

The overwhelming amount of data is more than needed for effective decision-making, according to the IBM Global CEO study. In fact, the information explosion was cited by public-sector executives as the main driver for increased complexity.

Executives also reported having little insight available on this data, which has created a “data paradox.” Public-sector analytics professionals reported spending 47 percent of their time collecting and organizing data and less than a third of their time on extensive analysis.

“The glut of data creates challenges in getting the potential value from massive amounts of data that organizations collect, store and manage,” the report said.

The combination of the data paradox and the information explosion creates challenges and complexities for effective information reporting in the public sector. Twenty-four percent of leaders surveyed said the data paradox is the greatest barrier for analytics adoption and use.

Some organizations have been deemed successful with their approach to improving analytics within their agencies. The report highlighted two major government agencies that have successfully deployed analytics tools on high volumes of information.

The Alameda County, Calif., Social Services Agency created a “lifecycle” view to track customer interactions with county and state social service resources. From this new approach, the agency was able to identify $11 million in fraud and waste in the first year of implementation.

The New York State Department of Taxation and Finance deployed a data analytics system to predict how likely a tax return is to be questionable, which allows the system to prioritize which cases are least likely to be eligible. The system then rejects ineligible refund requests to prevent them from going through the audit process. The state has saved more than $889 million while processing tax refunds faster.

Lynn Reyes, the government lead for the IBM Institute for Business Value and one of the study’s authors, said public-sector leaders need to develop an analytics competency within their organizations. According to the study, analytics competency is an “organization’s capacity to use analytics in an expanded, systemic manner and advance it as an enterprise skill.”

“[Analytics competency] requires an analytics talent and analytics capabilities, and those are certainly tools, technology, techniques and analytics leadership,” Reyes said. “In essence, government organizations need to ‘go pro’ in this area so they can use this information.”

Four key steps for obtaining analytics competency, according to the study, include focusing on outcomes rather than current issues, orientating the management of information  (as opposed to only collecting information), using analytics-enabled insights to meet objectives, and modeling and embedding analytics discipline into management practices.

 

 

 

Lauren Katims previously served as a staff writer and contributing writer for Government Technology magazine.