Data on Staff: Solving the staffing crisis with data and predictive analytics.

Public safety telecommunicators play a critical role ensuring emergency response operations run smoothly. But the smooth operations of emergency communications centers (ECCs) are imperiled by staffing challenges related to high turnover rates, increasing call volumes and mental health concerns. Effective emergency communications staff management can benefit from innovations in the use of data and predictive analytics that optimize staffing and improve response efficiency while enhancing workforce well-being.

THE CHALLENGES FACING ECCS

Turnover rates in ECCs remain a persistent issue. The demanding nature of the jw highstress situations, long shifts and emotional strain — often results in job dissatisfaction and burnout. A report found that annual turnover rates in ECCs range from 17% to 30%, depending on the region and center size.1 

Staffing shortages compound the issue, leading to mandatory overtime, increased workload and heightened stress levels among telecommunicators.

ECCs are experiencing increased call volumes due to population growth, urbanization and more complex emergencies. The COVID-19 pandemic underscored this trend, as many ECCs reported significant spikes in emergency and non-emergency calls.2 Additionally, calls now frequently involve mental health crises, natural disasters and multi-agency coordination, requiring PSTs to manage more complex situations with greater expertise.

Continuous training is essential for PSTs to stay current with evolving technologies, protocols and emergency response procedures. However, budget constraints and staffing shortages often limit professional development opportunities. Without adequate training, PSTs may struggle to adapt to emerging emergency scenarios, contributing to job dissatisfaction and decreased performance.

Mental health concerns remain a critical issue in emergency communications. PSTs routinely experience secondary trauma from distressing calls, leading to conditions such as post-traumatic stress disorder (PTSD). The 2019 NENA Critical Issues Survey reported that nearly 17% of PSTs exhibited PTSD symptoms related to their work.3 

Without robust mental health support systems, job performance and overall well-being suffer.

"Advanced scheduling software incorporates predictive analytics to balance staff availability with operational needs, reducing fatigue and improving employee satisfaction.”

LEVERAGING DATA AND PREDICTIVE ANALYTICS

Predictive analytics harness historical data to anticipate call volumes and demand fluctuations. By analyzing trends based on time of day, day of the week and seasonal variations, ECCs can optimize staffing levels. A study by the International City/County Management Association (ICMA) revealed that implementing predictive analytics reduced PST overtime by 20% in pilot programs across the United States.4

Data-driven scheduling solutions enable ECCs to align workforce allocation with anticipated call demand. Advanced scheduling software incorporates predictive analytics to balance staff availability with operational needs, reducing fatigue and improving employee satisfaction. A 2023 study by the National Institute of Standards and Technology (NIST) found that predictive scheduling reduced shift-related fatigue by 15% and increased staff morale by 10%.5

Analytics-driven training assessments help ECCs pinpoint areas for improvement. By evaluating call-handling patterns, response times and error rates, agencies can develop targeted training programs. This approach enhances PST competency in handling specialized emergency situations, such as behavioral health crises and multi-agency incidents.

Predictive analytics can also be applied to mental health initiatives. By monitoring indicators such as absenteeism, overtime and employee feedback, ECCs can proactively identify signs of burnout. Some agencies use predictive models to assess burnout risks based on workload and call types, allowing supervisors to implement timely interventions. According to a 2023 study by the American Psychological Association (APA), ECCs that introduced data-driven wellness programs saw a 25% decrease in burnoutrelated turnover.6

The Phoenix Fire Department successfully implemented predictive analytics to improve staffing efficiency. Facing high turnover rates and rising call volumes, the department developed a predictive model to forecast demand patterns. This allowed it to dynamically adjust staffing levels, ensuring optimal coverage during peak periods while minimizing unnecessary overtime.

Within the first year, the department reported a 30% reduction in PST overtime, a 15% decrease in turnover rates and a 20% improvement in call response times. Employee satisfaction surveys indicated higher morale, attributed to better scheduling and reduced workload pressures.

IMPLEMENTING PREDICTIVE ANALYTICS IN ECCS

Agencies must invest in robust data collection and management systems that integrate with existing emergency dispatch platforms. Reliable data sources ensure accurate forecasting and support informed decision-making. Implementing predictive analytics requires coordination among operations, human resources and technology teams. Collaborative efforts ensure that data insights are effectively utilized to enhance workforce management. ECCs lacking inhouse data expertise can benefit from external partnerships. Public safety technology providers offer specialized analytics tools and training programs to support predictive modeling initiatives.

A culture of data-driven decision-making enhances the effectiveness of predictive analytics. Encouraging staff engagement in data analysis and demonstrating tangible benefits help build organizational support for analytical approaches.

Staffing challenges in emergency communications require innovative solutions. Predictive analytics provides ECCs with the tools to optimize staffing, enhance scheduling, improve training and support PST well-being. By adopting data-driven strategies, ECCs can improve operational efficiency, reduce costs and create a healthier work environment for public safety communicators.

Ready to bring the future of workforce management to your agency? 
Visit smartprotectpublicsafetysolutions.com today to learn how SmartProtect can help you take the next step. 

REFERENCES

1 National Emergency Number Association (NENA). (2021). Critical Staffing Issues in 911 Centers. NENA Report

2 International City/County Management Association (ICMA). (2022). Leveraging Predictive Analytics in Public Safety. ICMA Report

3 National Emergency Number Association (NENA). (2019). Critical Issues Survey Report. NENA Critical Issues Survey

4 International City/County Management Association (ICMA). (2022). Predictive Analytics and Call Volume Management. ICMA Study

5 National Institute of Standards and Technology (NIST). (2023). Shift Scheduling and Staff Management in Public Safety. NIST Report

6 American Psychological Association (APA). (2023). Impact of Data-Driven Wellness Programs on Public Safety Agencies. APA Study