In my previous post I talked about robotics and IOT. In this post I will give an example of such a robotized system in retail.

One of the trends in grocery retailers is transforming their stores to strengthen their high quality fresh offer, either for take-away or for consumption on-site. For example sushi and healthy meals presented at a premium spot in the store.

Fresh products have short shelf life and need a climate controlled environment. As a retailer you want a high availability of your product and prevent out of stock which results in unhappy customers. The combination of high availability and short shelf life creates a high probability of shrink, having to throw away products past expiration date. A strategy for preventing this kind of shrink is to have some markdown policy on items that are about to expire.

Besides the availability and price the presentation of these high margin products is critical for the success and experience. Current strategy is continuous monitoring  by the front-line employees to maintain a good shelf condition typically by keeping the shelves fully stocked.

The Internet Of Things connects the physical world to the digital world using the internet. Sensors produce the data and they can be connected to all kinds of things. Here we can think of monitoring the climate controlled environment but also we can monitor the shelf condition using images and vision recognition. Several companies are already developing and using systems: Amazon Go is probably the most advanced, the LoweBot of Lowe’s and  Bossanova tested by Walmart are all good demonstrations of using vision and robotics.

CLICK ON IMAGE TO START VIDEO

CLICK ON IMAGE TO START VIDEO

CLICK ON IMAGE TO START VIDEO

Unfortunately we do not all have such deep pockets to innovate like these big companies. But in today’s open source software world you can relatively easy get a good vision recognition system up and running in a short time. This student at Stanford Robotics demonstrate in a well documented project you can easily monitor some shelves to detect out of stocks using free open source software. Learning from this project it is relatively easy to start using a fixed camera to monitor critical shelves to collect  business intelligence and to create alarms when the shelf condition is no longer what it is supposed to be. The collected data can also be used to implement a better dynamic pricing scheme focused on revenue optimization instead of spillage minimization.

If you ever felt that you would like to know more about what happens to your shelves, you want to increase your business intelligence and improve your operations then act today. The first steps are quite easy and consists out of monitoring more of your operations. If you do not know what to do, then do something and give us a call.