INFORMATION TECHNOLOGY FOR MINNESOTA GOVERNMENT

4/25/2012

Big Data and the State of Minnesota

Immature space for state government

As with many new areas, government is slower to move

Lagging behind private sector in terms of investment

Big Data in MN State

Government

We are “data rich, but information poor”

Large number of state systems

Large volume of data

Systems are aligned to specific functions, data

Efforts have been made to leverage data within systems to drive value for citizens and better government (Business analytics, Unemployment Insurance system)

Big Data in MN State

Government

Next Step: Begin to aggregate data from multiple systems

Have looked at data within systems, now must bring that data together in a way that creates value

This is where HUGE potential lies, holy grail of Big Data in government

Example: Aligning data from DNR, MnDOT and DEED to assess impact of transportation projects on recreational activity and tourism during MN summer

Frontiers for Big Data in

MN

Challenge 1: Technical barriers, new data processes, data alignment. (Similar to private sector)

Challenge 2: Stewardship and storage of data, state and federal regulations, data restrictions, data ownership (not similar to private sector)

Tension: Must not neglect responsibilities as “stewards” of public data in effort to overcome technical challenges of Big Data

Challenges for Government

in Big Data

There is potential to use Big Data for:

Human Resources: tying internal workforce data to outcomes, analyzing business processes, providing integrated services

Public Services: Crime prevention (Memphis PD uses multi-layered crime analysis of “hot spots” based on crime data to allocate resources)

Citizen Outreach/Empowerment: Boston’s “Adopt-a-Hydrant” program uses geographic data to empower citizens to clear hydrants after snowstorms

Where We Go from Here

Business IntelligenceRFP was issued in April 2011 for use of data analytics to reduce waste, fraud and abuse in state programs and agencies in 9 categories including:

Fleet Management Building Efficiency Medicaid Fraud and

Investigation Tax Fraud and

Investigation

Current Big Data Efforts

Statewide Longitudinal Data System

MN awarded $12.4 million in 2010 for the design and implementation of a statewide longitudinal data system

Examine student progress from early childhood through K12, higher education and into careers

Transition Minnesota’s education data capacity to a fully interoperable, enterprise-level data collection, reporting and analysis system

Includes data sharing connections across multiple state agencies

Current Big Data Efforts

Impact of IT consolidation for citizens

Chief Analytics Officer/Chief Data Officer

Next Steps