Optimizing Staffing for the Frederick County Division of Emergency Management

Abstract

The Frederick County Division of Emergency Management (DEM) is responsible for ensuring the community’s safety and security by handling 911 call intake and dispatch services for emergency response teams, including fire, police, and animal control units. With Frederick County experiencing significant population growth, DEM has seen a corresponding increase in 911 call volume, placing new pressures on staffing levels and operational capacity. Historically, the department relied on previous call volume trends to guide staffing decisions, but changes in call behavior—particularly during weekend nighttime hours—have rendered traditional staffing models insufficient.

The Data ConQUEST team partnered with DEM to assess current staffing needs, identify areas of operational inefficiency, and recommend strategies to better align staffing levels with call volume demands. This project utilized existing 911 call data from January to July 2024, focusing on variables such as call frequency by hour, day of the week, and holiday-related spikes. Using statistical analysis, data visualization, and predictive modeling, the team uncovered patterns that can inform optimal staffing decisions.

The analysis revealed two critical call volume trends. First, most 911 calls occur during weekday working hours, from 9 am to 5 pm. However, DEM's existing “power shifts” currently cover 2 pm to 7 pm, leaving a significant portion of peak call hours under-supported. Second, the analysis identified an unexpectedly high call volume during weekend nighttime hours, a trend that had not been observed in previous analyses. These patterns suggest a misalignment between existing staffing schedules and actual call demand.

To address these discrepancies, the Data ConQUEST team recommends the following: 1. Shift Restructuring: Adjust current power shifts to align more closely with peak call hours. For weekdays, the 9 am to 5 pm period requires more robust staffing coverage, while on weekends, nighttime coverage should be better distributed. Implementing larger early morning shifts, such as 6 am to 6 pm and 8 am to 8 pm, can better distribute workload during peak call hours and improve emergency response times. 2. Predictive Modeling: Use the predictive model developed by the team to forecast future call volumes and proactively schedule staffing. By incorporating call trends from weekdays, weekends, and holiday surges, DEM can create staffing schedules that account for seasonal and event-based call fluctuations. 3. Data-Driven Staffing Reviews: Conduct periodic reviews of call volume data and staffing levels to ensure alignment with changing trends. Continuous use of predictive modeling will enable DEM to respond to emerging patterns and adjust staffing schedules accordingly.

By implementing these recommendations, DEM can reduce call wait times, improve emergency response times, and ensure a more efficient allocation of human resources. With stronger staffing alignment, DEM will be better positioned to handle increased call volumes resulting from population growth and other unpredictable factors. The findings and recommendations in this report are designed to serve as a blueprint for future staffing assessments and operational improvements.