(Editor's Note: This article in the “Real Words or Buzzwords?” series examines how real words become empty words and stifle technological progress.)
For years, I’ve been writing about how the physical security industry lags behind IT by five to 15 years. But for the first time, that gap is shrinking. And where, of all places? Guard force management. The old phrase “guards, gates, and guns” is making way for something new: “guards, gates, and AI.”
I’ve long advocated for making security operations and security management more data-driven, just like most enterprises today. Surprisingly, guard force management is leading the charge.
AI-Enabled Guard Force Performance
What threw me for a loop was discovering several enterprises using AI-driven guard management platforms to track and improve performance—complete with dashboards they share with senior leadership. Yet not a single end-user mentioned to me that the platforms were AI-based. This technology has been busy transforming guarding performance for over five years, apparently, in some cases, flying under the radar regarding its AI capabilities.
Take HELIAUS, for example. It’s an advanced AI-powered workforce management platform developed by Allied Universal and launched in 2019. Its mission? To enhance safety and reduce risk by optimizing on-site security operations. And, refreshingly for this industry, the technology actually delivers on that promise. Now, I mention HELIAUS specifically, not to mention other platforms — it’s just the one I’ve seen in action through my clients.
Here’s the kicker: I found it embarrassing to realize that I’ve been five years behind in recognizing this trend. I asked myself, “Why?” It became apparent that it’s because it has been that long since I’ve been called in as a consultant to evaluate guard services or assess a guard force’s performance. Could guarding and guard force management have improved that much while I wasn’t looking? Turns out, it has.
Security’s Watershed Moment Revealed
Two years ago, I wrote an article titled “Security’s Watershed Moment.” In that article, I said:
“We have now reached a physical security industry watershed moment, in which we are making a complete break in security technology capabilities from the products and deployments of the past. It has been hard to see, but now the evidence is appearing. The next 10 years of physical security will be a radical transformation from the previous 50 years.”
The term “watershed moment” is often used to describe a pivotal event that changes the course of history. As ProWritingAid explains, it marks “an important event that changes the direction of history.” Similarly, Grammarist defines it as “a turning point, the exact moment that changes the direction of an activity or situation…a dividing point, from which things will never be the same.” It’s momentous — but often only fully recognized in hindsight — which is where we are now.
HELIAUS is another piece of evidence highlighting the revolutionary shift in post-watershed-moment technologies emerging in our industry. As Allied Universal put it in their initial product announcement:
“The main significance of HELIAUS is to bring together rich data, artificial intelligence, location-aware workflow automation, and seamless user experience design for security professionals.”
Take a close look at Figure 1 below. It outlines the before and after states of the physical security industry’s watershed moment. Notice how each value point in Allied’s press release aligns perfectly with the defining characteristics of post-watershed-moment technology. Dig deeper into the HELIAUS product information on the company’s website. You’ll find even more evidence of how this platform exemplifies the advancing technological transformation we’ve been waiting for.
Data-Driven Security Operations
Many organizations using these products don’t necessarily think of them as tools for “data-driven security operations.” And let’s face it, most security personnel are already stretched thin. They rarely have the time to step back and fully consider the potential of the data being collected. Yet that potential is becoming increasingly significant as AI-enabled physical security applications continue to emerge.
Data-Driven Security Operations refers to data collection, analysis and insights to optimize all aspects of a physical security program. This includes:
· Risk identification and assessment (scenario-based and history-aware)
· Incident detection, response and resolution (both preemptive and immediate)
· Resource allocation (personnel, technology and procedures)
· Continuous improvement and accountability (e.g., performance tracking, documentation)
A platform like HELIAUS directly contributes to security operations improvements in all four categories listed above.
Making the Most of Advanced Technology
By combining AI tools, data science and human expertise, data-driven operations enable security teams to act faster, make smarter decisions, and take a more proactive approach to preventing and responding to security risk situations.
Most large enterprises already have data transformation initiatives in place, supported by teams of data science engineers. These initiatives aim to uncover all an organization's data, assess its potential value across the enterprise, and facilitate its optimal use. Interestingly, data scientists are sometimes found within HR departments, where they apply their expertise to workforce analytics and related initiatives. This is an often overlooked resource for physical security teams seeking collaboration.
Physical security functions can greatly benefit from partnering with data transformation teams—or even with HR data scientists—to identify the risk-related and performance-related data elements within various physical security applications. Such collaborations unlock the full potential of these tools and maximize ROI.
Transformative Results
As I’ve said before — and will keep saying — the only limitation on physical security technology deployments and their contribution to high-performing security operations is our own thinking. The challenge is that some of the thinking we need, especially regarding data-driven operations, lies beyond the realm of our experience. Fortunately, the expertise we require almost always exists within our organizations. We can overcome these limitations through cross-functional collaboration with data-savvy colleagues and achieve truly transformative results.
