State leaders are using data to drive efficiency

When a hurricane approaches Florida, the state’s top priority is to rapidly send resources to high-risk areas. Emergency supplies, first responder teams and evacuation plans are coordinated based on real-time data flooding into the State Emergency Operations Center.

In the aftermath of the hurricane, the focus shifts to recovery and paying thousands of invoices for supplies and services to ensure communities receive aid. Leaders at every level rely on data to make these decisions accurately and efficiently.

The process can be complicated, but data offers an opportunity to streamline while maximizing preparation and response.

The Division of Emergency Management (DEM) is modernizing operations and improving how it uses data to help the state work faster during emergencies and manage taxpayer money responsibly.

DEM’s efforts include building a powerful system to collect and analyze data, as well as a machine learning tool to detect unusual invoices. It’s partnering with Slalom, a technology consulting firm, to maximize efficiency.

“Slalom is proud to partner with such an innovative agency, tackling firsthand the challenges that our citizens, businesses, and communities face in the aftermath of a hurricane or other emergency,” said Beau Williamson, Florida General Manager of Slalom.

DEM has been working with the firm since Hurricane Ian in 2022. It created a data platform, built on cloud infrastructure, that serves as the backbone for DEM analytics needed for decision-making processes and operations.

It includes a centralized data platform that integrates and stores information securely from the Division of Emergency Management Solution (DEMES) and other sources. It also utilizes a data governance strategy, which implements rules and guidelines to ensure data is clear, accurate and easy to understand. Advanced analytics also help DEM deploy end-user tools to unlock significant value, including finance and procurement dashboards, invoice anomaly detection, and GenAI for disaster declarations.

Slalom has also created an anomaly detector designed to identify and mitigate financial risks when processing invoices for payment. It identifies and interprets multiple types of invoice differences with more than 99% accuracy and delivers on the state’s commitment to financial integrity by detecting and promptly addressing unusual invoices. The detector also optimizes the invoice process, allowing for faster resolution and better resource allocation.

In the first 30 days of its deployment, the anomaly detector identified three major invoice irregularities valued at nearly $600,000. It works by analyzing past invoice data to create trends and identify deviations from these trends. This process teaches a machine learning model to distinguish between normal and abnormal invoice behavior. When something unusual is flagged, the detector sends notifications for further review.

Enhancements are in progress to optimize financial operations and move invoice anomaly detections upstream.

Taken together, the process and tech upgrades offer the state transformative insights.

Data is essential for leaders charged with protecting and serving Floridians before, during and after a disaster. By leveraging advanced analytics and machine learning, DEM has empowered its leaders to transition from manual information collection and research into a modern, data-driven approach. This shift has significantly enhanced the Department’s ability to analyze and act on transformative insights rather than spending time combing through unstructured data from multiple sources.

The goal is to strengthen DEM’s workforce to effectively fulfill its mission and support Florida’s economy following a disaster.

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