From Challenges to Benefits: Generative AI in Retail Businesses in...Read More
Dark stores began to appear before Covid-19 and accelerated their development during the pandemic to become an important new link in urban logistics. Conceived to deliver daily shopping in less than 15 minutes, stores that are not open to customers offer a new solution to the agility challenges of e-commerce for consumer products.
What's a Dark store ?
They have the functionality of a warehouse, but the organization of a store.They are located in urban areas near 100,000 users. Dark stores are stores not open to the public but only to delivery people. They have stocks of food distributed on the racks. Nevertheless, these structures have fewer articles than the supermarkets.
Principle of operating
The major advantage of a Dark store is its speed in the logistics of order preparation and delivery. It takes an average of 15 minutes for your order to arrive on your doorstep. All this is made possible thanks to a smooth process. As soon as your order is entered by an application, an operator in the Warehouse receives your shopping list on his work app or laptop. An algorithm then defines the employee’s route in order to avoid round trips to the shelves. Once the bag is ready, it is passed on to a delivery person on a bike or motorcycle, who in turn has previously recorded the route from the warehouse to your home.
1-Finding the ideal Dark store location
papAI solution can help retail companies to predict the best locations to open a new Dark store with a real-time maps, vector maps, geo data, and population movement, in their case, the companies is looking to settle in densely populated areas with a high standard of living.
From historical data, orders and current inventory, the papAI platform can predict the needs of the overall dark store network but also predict the individual needs of each dark store and suggest optimized decisions (purchase, transfer, etc.),after the creation of the machine learning model to be used according to the results of the backtest phase, the model will start giving predictive results.. It will identify which products are selling the fastest or slowest and model a more accurate inventory accordingly. This makes it possible to adjust stocks to avoid shortages and limit excess merchandise.
The papAI platform can anticipate breakdowns and schedule preventive maintenance of freight and logistics machines, Models can be trained by combining data from the Io’s advanced sensors, thereby improving asset utilization, increasing availability and reducing operating costs.