Welcome to Aapya Solutions, your guide to navigating the evolving landscape of convenience store technology, with a special focus on the critical realm of inventory management. In today’s fast-paced retail environment, staying competitive means effectively managing inventory to meet customer demand, and we’re here to explore how cutting-edge solutions like Edge and IoT (Internet of Things) can revolutionize this process.

Retailers are constantly trying to stay relevant in these times of digital disruption and one of the major problems confronting them is having right inventory in stock at the right time. Edge and IoT can help solve that problem and help improve customer experience. Edge solution does this by being the central point of information aggregation from sensors (camera) in the shelf/store, POS, interactive shelves, displays, tablets and mobile devices. The next chapter of retailing is being written as we speak today.

Customer Pain points and associated business loss:

Reduce lost sales from lack of inventory/stock when needed. In one study Harvard Business Review (HBR) found that by using technology a C-store was able to reduce stock-out rate by 22.5% in 8 weeks and in another case a C-store sale increased by upto 2%.

In a Study by HBR globally around C-store stock-out problem, 43% of customers loyal to a brand of product would leave a store and go to another store to buy the product resulting in loss of sales. The study of around 71,000 customers claims customers have little patience for stock-outs.

Over stocking leads to waste if the product expires and this reduces profitability. Whether overstocking or understocking, miscalculating stock levels is an expensive problem for C-stores.

Current POS based Solutions:

Current POS only tells what was sold, they can not only anticipate how demand might fluctuate based on seasons, price changes, promotional campaigns, or store hours but also have no visibility in the shelves/racks in real-time as inventory moves out. This is what the Edge based solution with Computer vision will do for c-stores.

Traditional approaches would involve sales associates to walk around and collect information on stock levels and is laborious and prone to errors. Computer Vision and cost-effective Edge help solve this problem and improve accuracy and can provide information on demand.

Existing traditional solutions and technologies for inventory management in convenience stores face significant challenges due to their inability to provide real-time visibility into shelf activity. These methods often lack the integrated data necessary for informed decision-making and effective responses to Out-of-Stock (OSA) situations.

Manual Audits: Historically, manual audits have been a primary method for inventory management. However, they are expensive, difficult to scale, and prone to human error. Moreover, manual audits often fail to accurately measure sales loss, limiting their effectiveness.

Perpetual Inventory Systems: These systems enable immediate tracking of sales and typically interpret “zero sales” as an indication of an out-of-stock (OOS) situation. However, their on-hand accuracy can be problematic, with studies revealing significant variances ranging from 32 to 45%.

POS Data: Point-of-sale (POS) data analysis relies on historical sales patterns to estimate OOS rates. While this method provides some insight, it may not effectively address slow-selling SKUs. Additionally, POS data is often aggregated, making it challenging for brands to access detailed store-level insights.

RFID Technology: Radio frequency identification (RFID) technology automates product identification using wireless signals transmitted by RFID tags attached to each item. Unlike barcodes, RFID tags do not require line-of-sight scanning, enhancing efficiency. However, RFID has limitations, including a high error rate when identifying multiple products simultaneously. Moreover, RFID labels are expensive and pose challenges for recycling, contributing to higher operational costs and sustainability concerns.

As the retail landscape evolves, businesses are increasingly turning to artificial intelligence (AI) technology to revolutionize inventory management. AI offers the potential to reshape the retail industry by integrating online and offline experiences, addressing existing challenges, and optimizing operational efficiency.