Magazine Features

Loss prevention professionals face unique mental health challenges due to high-stress, high-risk job environments, and accessible therapy options can help them build resilience and sustain long-term well-being.

Strategic cargo theft is a growing, global threat exploiting supply chain vulnerabilities, demanding stronger collaboration and updated protections.

The adaptive, predictive, and networked behavior of dragonflies offers a striking parallel to how organized retail crime groups assess risk, communicate, and evolve—especially through tools like social media—to exploit weaknesses in retail systems.

Despite official crime stats suggesting retail theft is down, new research shows it's actually rising—underreporting, shifting policies, and strained police resources are masking the true scale of the problem and fueling a misleading public narrative.

Retailers face rising teen-driven disruptions fueled by social media, prompting calls for stronger security, community partnerships, and balanced policies.

Celebrating its 25th year, the Loss Prevention Research Council (LPRC) continues its mission to advance evidence-based retail crime prevention through collaboration, innovation, and rigorous research—growing from a bold idea in 2000 into a global leader in loss prevention strategy.

Research is a systematic, evidence-based approach to understanding the world that helps us overcome personal biases, adapt to change, broaden our perspectives, support arguments with credible data, and determine what works and why—especially in fields like loss prevention.

Amid high rates of property crime, police staffing challenges, a fentanyl crisis, and widespread social instability, Albuquerque has emerged as an unexpected hotspot for retail theft, prompting retailers and law enforcement to push for reforms, partnerships, and tougher enforcement to turn the tide.

Talented people make all the difference. Finding the right balance of talented individuals at every level of the department builds the foundation, sets the tone, and executes the message.

Vision-Language Models (VLMs) combine computer vision and natural language processing to enhance retail loss prevention by not only detecting suspicious behaviors in real-time but also providing contextual understanding and actionable insights.