Successfully reported this slideshow.
We use your LinkedIn profile and activity data to personalize ads and to show you more relevant ads. You can change your ad preferences anytime.

NJ Future Redevelopment Forum 2017 Collum

169 views

Published on

Data-Driven Cities

Published in: News & Politics
  • Be the first to comment

  • Be the first to like this

NJ Future Redevelopment Forum 2017 Collum

  1. 1. Township of South Orange Village Sheena C. Collum, MPA, Village President
  2. 2. DATA-DRIVEN CITIES: EFFECTIVE CIVIC ENGAGEMENT AND DECISION-MAKING Case Study 1: Citizen Engagement • SO Inform (Civic Plus) • SO Engage (Peak Democracy) • SO Connect (Civic Plus) • SO Community Map (Gov PILOT) • SO Alerts (Civic Plus) • SO Volunteer (Volunteer Hub - Coming Soon)
  3. 3. DATA-DRIVEN CITIES: EFFECTIVE CIVIC ENGAGEMENT AND DECISION-MAKING SO Engage (Peak Democracy)
  4. 4. DATA-DRIVEN CITIES: EFFECTIVE CIVIC ENGAGEMENT AND DECISION-MAKING SO Engage (Peak Democracy)
  5. 5. DATA-DRIVEN CITIES: EFFECTIVE CIVIC ENGAGEMENT AND DECISION-MAKING SO Connect (Civic Plus)
  6. 6. DATA-DRIVEN CITIES: EFFECTIVE CIVIC ENGAGEMENT AND DECISION-MAKING SO Connect (Civic Plus)
  7. 7. DATA-DRIVEN CITIES: EFFECTIVE CIVIC ENGAGEMENT AND DECISION-MAKING Case Study 2: Public Safety Depts. South Orange Police Department (ICMA Study & Implementation) • Changed work schedule from 10 hours 40 minutes to 12 hours (negotiated) • Reduced head count from 53 to 47 • Eliminated one of two Captain positions, reduced Lieutenants from 9 to 6 • The new 12 hour patrol schedule projected to reduce overtime by $200,000 per year • Consolidated multiple divisions into a single “Special Operations” division • Upgraded/replaced technology to take a “data-driven” approach to public safety deployment Deployment and Main Workload
  8. 8. DATA-DRIVEN CITIES: EFFECTIVE CIVIC ENGAGEMENT AND DECISION-MAKING Case Study 2: Public Safety Depts. South Orange and Maplewood Fire Departments Study Goals • Improved effectiveness • Increased efficiency • Improved productivity • Improved customer service • Enhanced or expanded services • Cost savings • Improved allocation and utilization of resources, including manpower, facilities and equipment. • Cost avoidance(s) • Coordination and improved efficiencies in mutual aid • Standardization of services • Improved training • Improve ISO rating(s) • Additional funding sources
  9. 9. DATA-DRIVEN CITIES: EFFECTIVE CIVIC ENGAGEMENT AND DECISION-MAKING Case Study 3: Redevelopment Irvington Avenue (Partnership with SHU Market Research Center) • Data-driven community approach to neighborhood revitalization (3 focus groups) • Outcomes: Events & promotion (Food Truck & Craft Beer Festival, Holiday Tree Lighting), enhanced lighting for safety, rebranded to “Seton Village”, creation of SV Committee, town- wide rehabilitation designation, Together North Jersey Grant (with surrounding towns)
  10. 10. DATA-DRIVEN CITIES: EFFECTIVE CIVIC ENGAGEMENT AND DECISION-MAKING Case Study 3: Redevelopment Sale of South Orange Village Hall • JGSC Market Research Report • Importance of public opinion in redevelopment decisions • Data analysis on project and full disclosure on all financial terms • The challenges of soliciting informed feedback (with any project!) • Data alone doesn’t make for good public policy

×