Situational Awareness: Moving from incident management to predictive modeling

By Mike Caralis

The world has changed a lot in the last few years, reshaping how we live and work. The introduction and rise of the hybrid work model has introduced new complexities to cybersecurity, while global supply chain disruptions have driven a shift toward nearshoring, impacting manufacturing, production, and trade. The world is evolving rapidly, and according to Amy Jeffs, the president of Status Solutions, situational awareness is in the midst of its own evolution from incident management to predictive modeling; in other words, getting out ahead of what is happening right now.

The foundation of situational awareness

Incident management is a cornerstone of situational awareness, referring to proactively identifying, analyzing, and responding to critical incidents in a given environment. The overarching goal is to use real-time data to educate and inform appropriate community constituents. Supplied with the most current and relevant information, said constituents can take effective, timely measures to contain or mitigate an incident. In other words, how do we notify the right people at the right time so that they may respond to any circumstance swiftly and decisively? That's the question that Status Solutions, our customer, has based their whole platform around.

The underlying principle of incident management is straightforward, but its execution is complex, requiring coordination across disparate systems, organizations, government agencies, businesses, and public buildings. Even the systems within the same building aren't always interoperable. Physical security systems, for example, were analog and siloed for a long time. Though that has largely evolved, the broader point remains: systems don’t always talk to each other, even within the same building or organization. A portrait of complexity begins to take shape when you consider that there are many organizations and buildings with many systems in place.

Status Solutions bridges these gaps by serving as the connective tissue between individuals and organizations during critical events, leveraging its core middleware to provide situational awareness.  A recent example is their role at the Westerville Music and Arts Festival in Central Ohio. The situational awareness provider deployed its latest solution, CATIE Mobile (Communication and Access To Information Everywhere), which enabled real-time updates, safety alerts, and streamlined communication between festival organizations, vendors, volunteers, and first responders. Festival attendees who opted in received timely updates on their smartphones about schedule changes, weather alerts, and other critical information related to the festival. CATIE Mobile enhanced communication and safety for thousands of attendees, vendors, and volunteers. 

Anticipating incidents

As mentioned, the challenges and variables of incident management are only multiplying. Data volumes are exploding, and being able to harness all that data and information in a timely manner is increasingly difficult. Fortunately, advancing technologies allow us to approach situational awareness in new ways.

As Jeffs has remarked, the way forward for situational awareness is predictive modeling and the ability to anticipate and even prevent incidents. This is where the power of predictive analytics, a type of artificial intelligence (AI) and machine learning (ML), comes into play. By connecting and coordinating across disparate entities, organizations can use data to identify patterns and trends that enable proactive intervention. 

This can play out in many different ways, according to Jeffs. One example is a student who is exhibiting behaviors that suggest they may be at risk of committing a violent act. Insights gleaned from previous events can reveal patterns that typically precede a violent episode, like inconsistent attendance, frequent visits to the school nurse or a sudden drop in GPA. When coupled with additional context provided by relevant parties, such as parents or teachers, these patterns can guide timely, informed interventions to help prevent potential harm.

Another scenario involves an elderly individual who is aging in place. There may be certain signs that they’re increasingly at risk by living alone: missed doctor’s appointments, not maintaining consistent eating habits, and isolating themselves. These events may typically precede a fall or accident in the home. Predictive analytics can help to identify these inflection points, providing an opportunity to intervene before a critical incident occurs.

The role of 5G

One of situational awareness's most powerful advantages is the ability to predict and even prevent incidents. However, achieving this requires significant processing horsepower. While data is invaluable, its true benefits lie in the ability to analyze and act on it quickly—a difficult challenge given the explosive growth of information. AI’s predictive analytics can effectively separate the wheat from the chaff, especially when paired with the speed and capacity of 5G technology.

Verizon Business 5G networks provide more bandwidth, lower latency, and faster speeds, facilitating near-real-time transmission of data. With 5G as its foundation, AI can process data a lot faster, enabling it to arrive at better insights more quickly. This is a powerful combination, given that speed and the quality of insights are instrumental to situational awareness. 

Verizon Business’s 5G networks enable Status Solutions to maintain a reliable connection, one of their top priorities and absolutely critical when protecting people and spaces. Redundancy means that critical information is received, whether it’s on a digital screen, an audio page, text, or a standard phone line.

People and technology

Predictive modeling and AI are the future of situational awareness. The more data we acquire, the better informed our models can be. The faster our networks, the faster we can process data. The faster we can process data, the faster we can identify and anticipate incidents. While these technologies may drive the evolution of situational awareness, we mustn’t overlook the other critical component of situational awareness: people.

Data and insights are critical, but they don’t get the job done by themselves. The right people must see the right data and insights at the right time. That requires building networks of people across a wide range of organizations, departments and agencies; it requires building a system of triggers and alerts, powered by intelligent solutions; and it requires connecting leaders and decision makers to the right people and the right systems. Smart people and smart systems will define situational awareness of the future.

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Mike Caralis is Vice President for Business Markets at Verizon. Connect with Mike on LinkedIn.