Unstructured Data to PrioritizeCities and large organizations operate multiple systems—from utilities to CRM platforms—that can create an almost unimaginable volume of data on any given day. Making good use of that data can ensure operations run smoothly and increase revenue. Conversely, becoming overwhelmed by massive volumes of unorganized, unstructured data can be an operations nightmare.

The end goal of IBM’s Intelligent Operations Center, a data management software suite designed for cities or large organizations, is to analyze incoming data in real time, find correlations for important events and guide end users on how to act on this information. The ability to prioritize data and deliver answers to the right people can make management more efficient and more effective at every level.

For city officials, a high performance data organization/normalization delivery system can make every process more efficient, from emergency response management to identifying business fraud or tax evasion. Emergency response might seem like an intuitive example. For instance, imagine a passerby snaps a picture of a cat stuck in a tree and sends it to the local police dispatcher, who in turn uses the metadata in the photo to send animal control a rescuer  to the scene.

Identifying business fraud or tax evasion might seem less obvious. But consider organized data that locates a large amount of water or electricity being used at a site that doesn’t hold a business license. That much utility usage could, for example, be tied to a manufacturing center that is operating without the proper registrations and licenses to avoid paying taxes and fees. The ability to process and analyze data feeds across the city can help to identify potential fraud and stop the illegal activity.  This could quickly would result in major revenue recovery for a city.

The key in the above examples is that the municipality must work with IT service providers to define how data will be organized and prioritized when it comes into its system. This can be more challenging than it sounds. Most city managers or business executives are good at knowing the goal they want to achieve. End goals are generally clear since they’re driven by the wants and needs of their constituents or customers.

However, each of these clear end goals needs a starting point, and that’s where the challenge emerges. This starting point allows you to see the types of data you have and how technology can be applied to expedite service delivery and operating efficiency. So, while it may be a difficult process, a good place to start is with a defined list of priorities for your city or organization and very clearly align them with the most useful data and the most informative presentation of information. Most cities and organizations have this list of goals and vision already in place, however identifying the right data feeds and realistic initial goals can help drive this vision to reality.

A good example here is IBM’s recent awarding of a Smarter Cities Challenge grant to the city of Houston. The grant is designed to focus cities on solving a particular problem within four to six weeks with more effective collaboration and communication. Houston dedicated its grant to assist its Department of Neighborhoods better serve people by helping them share ideas and resources for addressing challenges in their area.

While outside observers may have expected the grant to be directed at a more tangible issue such as natural disaster emergency response management, the chosen direction indicated a shift toward more collaborative solutions derived from data provided by citizens. A world with greater access to more organized data is a world where every end user can contribute to informed decision making.