When Every Second Counts, So Does the Data
Imagine this: a fire dispatcher juggles multiple incoming 911 calls, each more urgent than the last. A commercial structure fire erupts on the city’s south side just as EMS resources are already committed to a mass casualty collision uptown. Within minutes, command is activated, but no dispatcher is consulted on resource availability, mutual aid coordination, or historical call volume data. Tactical decisions unfold—but without one of the most valuable voices in the room.
Too often, dispatchers are left out of strategic conversations despite having direct access to one of the most powerful tools in emergency response: data.
In this post, we’ll explore how big data is reshaping emergency response across the country—and why dispatch professionals should play a central role in this data-driven future. From predictive modeling to real-time analytics, we’ll unpack practical ways data can drive smarter decisions and elevate dispatcher voices in operational planning.
The Power of Big Data in Emergency Response
Big data isn’t about massive spreadsheets—it’s about actionable insights. In fire and EMS services, data analytics transforms raw information into patterns, trends, and decision-ready intelligence. Dispatchers and incident commanders can now anticipate risks, allocate resources more efficiently, and reduce on-scene time.
What qualifies as “big data” in fire and dispatch operations?
- Historical call volume by type, location, and time of day
- CAD and RMS (Computer-Aided Dispatch and Records Management Systems) logs
- GIS mapping and heatmaps of incidents
- Response time metrics
- Mutual aid frequency and effectiveness
- Community risk assessment data
- Weather, traffic, and infrastructure overlays
Key Benefits of Leveraging Data:
- Improved Response Times: Identifying patterns in peak call volume helps optimize shift scheduling and unit deployment.
- Informed Resource Allocation: Data highlights areas with frequent structure fires, guiding decisions on equipment placement or staffing needs.
- Better Community Outreach: Trends in false alarms or medical assist calls can shape public education campaigns or fire prevention efforts.
- Enhanced Dispatcher Leadership: Providing data-backed insight to the command staff strengthens dispatcher credibility in ICS planning.
Data Tools Transforming the Fire Service
Several platforms and frameworks are helping fire services and dispatchers collect, interpret, and use big data effectively:
1. NFIRS (National Fire Incident Reporting System)
Standardized reporting helps identify national trends. Dispatchers can contribute to cleaner, more accurate NFIRS entries by ensuring proper event categorization.
2. IAED ProQA and AQUA Software
For agencies using structured call-taking, ProQA’s reporting features can identify protocol compliance trends and support QA/QI programs.
3. GIS-Based Predictive Analytics
These tools help agencies identify geographic zones with high fire risk or EMS call volume. Dispatchers can use this data to recommend staging areas or pre-alert tactics.
4. Real-Time Dashboard Tools
Some CAD systems now include real-time dashboards with KPIs like response times, unit availability, and pending calls—empowering shift supervisors with actionable intel.
This level of high-stakes decision-making reflects patterns discussed in “The Impact of High-Stress Calls on Dispatcher Mental Health.” Access to quality data helps reduce ambiguity, which in turn eases the mental burden on frontline dispatchers.
Integrating Data into Daily Dispatcher Workflows
1. Shift Briefings Powered by Data
Instead of anecdotal reports, use yesterday’s call data to brief crews and telecommunicators. Highlight units that were overextended, repeat callers, or delayed response zones.
2. Dispatcher-Led Operational Reviews
Invite dispatchers to monthly after-action reviews (AARs) with data to back up their insights. Were mutual aid units delayed due to jurisdictional confusion? Did call queues spike during a social event?
3. Pre-Incident Planning Collaboration
When fire agencies review tactical pre-plans, dispatch input on address verification challenges or unit response history can be game-changing.
Bold Takeaway: Dispatchers equipped with data can shift from reactive roles to strategic contributors in agency planning.
Challenges in Adopting Big Data—and How to Overcome Them
While the benefits are clear, implementation isn’t without friction.
Common Barriers:
- Data Silos: CAD, RMS, and HR systems often don’t communicate well.
- Understaffing: Many centers lack the time or personnel to analyze data effectively.
- Training Gaps: Some dispatchers aren’t trained in data interpretation or reporting.
Solutions:
- Advocate for dispatcher training in data literacy and dashboard tools.
- Partner with IT or analytics teams to build simple weekly reports.
- Encourage interdepartmental meetings where dispatch insights are formally reviewed.
Real-World Case: Using Data to Predict Fire Risk in Tulsa, OK
Tulsa Fire Department implemented a data-driven risk reduction program using GIS overlays and call history to identify high-risk buildings. Dispatch played a key role by flagging repeated calls from the same locations, enabling targeted inspections and public education. The result? A measurable reduction in fire incidents in specific neighborhoods over 18 months.
This type of proactive approach exemplifies the impact of integrated data—and how dispatch centers can be at the heart of that transformation.
Conclusion: Elevating Dispatcher Voices Through Data
Big data isn’t just a buzzword—it’s a tool that empowers smart leadership and operational success. Fire dispatchers and communication center supervisors must claim their seat at the table by harnessing data to inform ICS planning, staffing, and response.
When we move beyond anecdotal reporting and into evidence-based decisions, dispatchers become not just the voice of the call—but the voice of strategy.
Action Step:
Share this post with your leadership team or analytics department and ask: How can we better use data in our daily operations?
