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Otto Doll, Chief Information Officer, City of Minneapolis

Otto Doll, Chief Information Officer, City of Minneapolis

By Otto Doll

As Chief Information Officer of Minneapolis, I used to get asked a lot about what will be the next big killer app. Today, I’m asked what’s the next big killer outcome.

The processes that drive Minneapolis are very focused on data. Each week, city leaders and council members sit down together to review and make decisions, but increasingly we’re doing more than looking at data about the past, today we’re on a path to see our city in two, three and even four dimensions. The goal is to turn data into better decisions and better outcomes for our citizens.

To do this, analytics is key. By looking at patterns, event correlation, hot spotting and anomaly detection, we’re now using technology to tell meaningful stories through data—where the participants help generate the content.

A lot of times decision makers and city workers want information to make it easier to do their jobs. They need to see patterns and cause and effect. We’ve worked with IBM to create a common set of reusable analytics that are changing how the city operates. These analytics don’t serve a single purpose, but can be used across the many different data sets within the city to answer questions about situations from the police department to city hall. For example, the same analytics used to look for hot spots of criminal activity can be reused to spot flu outbreaks or concentrations of vacant properties that may indicate economic development challenges in a neighborhood.

We’re using analytics in other ways. For example, for a local organization wanting a permit for a special event, we can look at all activities across the city on a given day and advise that the first Saturday of the month is the best time to host that 5K they’ve been planning. For major emergencies that stress all our resources, we can analyze where office-duty police are geographically located and determine who can respond first if we need them. For crime-fighting, we’re not just looking for hot spots of crime, but we’re drilling down into the data to look for the root causes. On top of that, we’re overlaying a view of how police resources have been applied so we can evaluate if our approach is working.

Tracking more than 1,250 metrics across the city, we’re helping better understand how our city is performing against our goals. We’re also evaluating our practices more carefully.  In evaluating our snow emergency parking restrictions, we’re correlating census data, parcel structures, digital divide data, etc. to where we are issuing parking violations, in order to understand why people are not moving their vehicles in time.

By using analytics that can run “what-if” scenarios, we’re taking a lot of the guess work out of running a city. We’re also putting the power of analytics into the hands of more city employees. Our hope is to maybe even one day put this power into the hands of our citizens.

For Minneapolis, using Big Data and applying analytics is all about improving the quality of city services, making city operations run more efficiently, and most importantly addressing the needs of our citizens.

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June 4, 2014
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This is exactly what other countries should do. Our responsibility as citizens is to find the way to help our governments/ organizations to plan better and make decisions base on data and predict future scenarios.
If governments manage country operations, projects and finance using analytics, starting with the integration of information from different entities such as hospitals, social security, police department, ministries and then applying big data techniques to make decisions, we should be able to see an improvement in the live quality, decrease in costs, improvement on the programs effectiveness, city growth and many other benefits.


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June 3, 2014
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May 30, 2014
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Collection and analysis of data in better ways can help any organization be more responsive to citizen’s needs and help to create a better, more efficient quality of life. Cheers to Minneapolis and IBM for showing us how!


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Big data should not be restricted to any particular activity in the city to make it intelligent. It is a combination of all knowledge that makes a person intelligent. All departments in a city must collaborate on information they have to get the real big picture and proper analysis.


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