Analysis of 311 call data can lead to better service, lower costs


Many cities and counties are taking the lead of private industry and developing 311 call centers to consolidate incoming calls for service and information requests from citizens. The business advantages are clear:

  • Citizens have one number to call for service and information rather than having to waste time searching for the right number.
  • Citizens are not shuffled from department to department looking for the appropriate respondent.
  • Responses can be standardized for more consistent performance across all service areas.
  • City/County managers and elected officials can learn more quickly how timely response is across various departments.
  • Trained department staff can spend their time performing more professional work instead of answering the phone.  

These 311 call centers produce a wealth of data that can be used to evaluate organizational and departmental performance against key performance indicators. This data can be help identify service delivery problems within any function, reveal the location of larger city/county infrastructure or staffing problems  and evaluate response times and effectiveness of the response. 

Of course, in order to answer even these elementary questions the 311 call data must be supported by a software system that collects and arranges data based on key performance indicators (KPIs). It would be even better for organization credibility and public transparency if the KPIs were displayed in dashboards and score cards and available on the web.

Data integration, data quality and business intelligence reporting are all necessary to glean useful information from call system data. This information gives managers, elected officials and the public an accurate picture of current performance. If predictive analytics is added to the tool box and applied to call data, an entirely new level of analysis can be achieved.  Analytics will correlate 311 data with other available data (work order, maintenance, weather, consumption, omputer-ided ispatch and ublic afety records management system data, etc ) on the  water and sewer systems and equipment, pavement conditions, parks, traffic signalization, public buildings, solid waste and recycling or any other operation. 

It will create correlations and models that predict future infrastructure problems. Repairs and replacements can be made proactively to reduce overtime costs, prevent more expensive repairs and prevent environmental damage. The analysis can inform managers about the types and frequency of repairs and maintenance needed, which will allow more precise control of parts and equipment inventory kept on hand. The potential to improve service and lower operations costs using these data analysis tools is truly unlimited.


About Author

Bill Coleman

Advisory Industry Consultant

Bill Coleman works with SAS local government customers across the US to understand best practices and solutions. Coleman applies his more than 30 years of experience as a senior leader in city and local government to guide SAS product and marketing management. From 1994 to 2008, he served as Town Manager of Cary, NC, the seventh-largest municipality in the state with a population exceeding 130,000. Coleman was responsible for planning, organizing and directing municipal operations, which included more than 1,000 employees and 11 departments providing a full range of municipal services. Under his leadership, Cary was the first municipality in North Carolina to work on performance enhancement system. The system was designed to help the town maintain its high quality of life by improving resource allocation and operational efficiencies throughout town government, beginning with the areas of public safety and development services.

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