In our last blog, we underscored the significance of On-Shelf Availability (OSA) in the retail industry's landscape. This time, we dive deeper into the OSA tracking methodologies, the technology that powers them, and how to identify the right solution tailored to your business requirements.
Several OSA tracking strategies are presently in use, ranging from traditional manual inspections to more sophisticated, automated systems. These methodologies can broadly be categorized into manual (involving human-operated processes) and automatic (utilizing advanced processes with minimal human intervention).
While we lack exact data on the distribution of these OSA tracking methods, we can infer broad trends from industry reports and studies.
MarketsandMarkets research suggests that barcode scanning, with its low cost and ease of implementation, was the dominant OSA tracking technology in 2020. However, IoT sensors are gaining popularity due to their real-time inventory data provision and potential labor cost reduction.
Advanced OSA tracking technologies like RFID tagging, static camera-based computer vision, and mobile robot patrols are generally favored by larger retailers managing intricate supply chains.
Geographically, North America and Europe lead in adopting these OSA tracking techniques, thanks to better access to technology and resources. However, emerging markets like Asia-Pacific and Latin America show an increasing trend of investing in advanced OSA tracking technologies, underlining a global recognition of OSA's importance in enhancing efficiency and customer satisfaction.
As retailers continue to prioritize OSA tracking, the fusion of static cameras and computer vision is emerging as a game-changer. This technology not only automates the process of OSA tracking but also offers several advantages that put it ahead of the curve.
Primarily, static cameras combined with computer vision offer real-time and continuous data. This feature distinguishes them from manual methods, which necessitate human operators for data collection and action. Contrasted with other automatic solutions such as RFID and IoT sensors, static cameras don't require additional labor for applying RFID tags on all products or installing a network of sensors on shelves. While mobile robots sidestep this constraint, they could struggle with maneuvering during periods of high store traffic, require maintenance and charging, and may find navigating crowded or complex store layouts challenging.
Moreover, cameras installed for OSA tracking can serve multiple purposes. They can monitor compliance with planograms, assist online order systems if the stores double as distribution centers, and be repurposed for security applications. Their continuous feed can be utilized by other innovative applications to detect theft and other security concerns, maximizing the return on investment.
As technology advances, the cost of cameras continues to decrease, making it more affordable for retailers to adopt computer vision technology for OSA tracking. Concurrently, breakthroughs in AI and computer vision technologies are reducing the cost of running these models. These can be hosted on cloud platforms, allowing retailers to pay only for what they use.
With an acute understanding of the rising need for real-time and precise OSA data, enRetail has designed an efficient solution to streamline this process. Our platform integrates seamlessly with existing security cameras to provide comprehensive, real-time OSA data. By automating shelf management with enRetail, retailers can gain valuable insights, increase operational efficiency, and ultimately elevate the customer experience. As we continually refine our technology and services, enRetail remains committed to empowering retailers on their journey towards an optimized retail ecosystem.