The Rush to Real-Time Data: Automation Powers Next-Generation Retail Insights
In today’s digital world, data is worth its proverbial weight in gold. However, it’s not enough for retailers to just collect data to win the retail wars; they need to have a strategy to distill and apply insights from the data.
For example, inventory data is particularly ripe for strategic use. By synthesizing information about what’s on the shelf, retailers can quickly determine which aisles need attention to optimize the customer’s experience and maintain smooth operations. Without these insights, retailers may miss sales opportunities. A recent study by P&G revealed that when consumers can’t find a product they need, 31 percent will purchase it from a competitor, 15 percent will delay their purchase, and another 9 percent won’t purchase the item at all.
However, the move from data collection to data insights, though necessary to stay competitive, is difficult at scale for most retailers. We’ll examine automated methods to collect retail inventory data at scale, how to process it through artificial intelligence (AI) in near real time, and the benefits of applying the resulting insights.
In order to reap the benefits of these data-based insights, the first step is building a solid data foundation. The key is consistent data capture. Traditionally, this was done by associates manually scanning each item on the shelf. This is a tedious, labor-intensive process that often leads to inaccurate results due to human error. It’s not an efficient process, especially at scale.
With advances in automated technology, retailers can now leverage new processes to yield smooth data capture. For example, autonomous robots are able to scan products on the shelf and analyze terabytes worth of data within minutes, giving retailers deep insight into real-time product inventory. Armed with computer vision, which helps the robots “see” what’s on the shelf and determine if anything is misplaced, mispriced or missing, these systems are far more efficient and three times more accurate than traditional methods.
In order to maximize insights from the data collected, consider implementing AI technology. AI is a powerful tool to distill insights from new data sets (or old ones), especially when dealing with a large volume of data. Retailers are already in the early stages of implementing these technologies. In fact, a recent NRF and IBM study found that 40 percent of retail and consumer product companies are using intelligent automation, and that number is expected to double by 2021. In the case of retail inventory, the insights need to be derived in near real time to be effective. Luckily, AI is able to crunch massive amounts of data and share insights about which shelves need attention in as little as 15 minutes.
Let's put the volume of this work into context: some big-box retailers have approximately 1,500 products per aisle and roughly 50 aisles per store. With each robot scanning each aisle three times a day, the technology captures 225,000 products and 2.5 terabytes of data a day. One robot can capture and process up to 500,000 images in a day, giving unprecedented visibility into on-shelf inventory.
The benefits of these means of data collection and processing are unparalleled, bringing to life the fast, seamless shopping experience consumers expect. Per a recent Deloitte report, autonomous robots will empower increased efficiency and productivity as well as reduce the volume of errors and re-work. When leveraged successfully, inventory data insights can tell associates which products need to be restocked, which are mislabeled, even which displays are organized incorrectly — all in near real time. Moreover, associates are empowered to spend their time with high-value tasks like assisting customers, instead of getting tied up in menial tasks like accounting for inventory.
New technologies like automation may seem intimidating to retailers, but ultimately they’re the key to success in today’s retail market. It’s well known that data is critical to stay competitive, but data doesn’t mean anything unless retailers can distill actionable insights from it. Autonomous processes powered by AI bridge this gap and are the future of the retail intelligence revolution.
Martin Hitch is the co-founder and chief business officer at Bossa Nova, a robotics company that provides product inventory data for retail.
Martin Hitch is the co-founder and chief business officer at Bossa Nova, a robotics company that provides product inventory data for retail.
