Operating retail stores have always had a myriad of challenges, which required employees to be extremely good at multitasking (e.g., when taking care of both operations and sales activities). Nowadays, with the emergence of new retail channels, which use the store as a hub (e.g., ship-from-store and click-and-collect), the number of intertwined processes that stores have to properly manage has soared. To be able to cope with all this complexity, retailers need to put technology and data at the core of managing the traditional store.
Let us deep-dive into three key processes that can be improved with a such blend of approaches: checkout design, inventory management, and workforce planning.
The main pain point of offline customers in the store is the waiting lines, which may push them away from the retailer. This emphasizes the importance of proper checkout design. The ideal number of checkouts balances the right mix between the benefit of increasing maximum sales on peak periods and the cost of operating them, by reducing the available area for exhibiting products.
Not only dimensioning is crucial, but also questioning the checkout model. The conventional checkout can benefit from a single-line approach, instead of a multi-line one, but disrupting models are being placed in stores and this will prevail in the future.
Self-checkout is the main one, removing the workforce cost at the front line of the store, by letting the customer check their own shopping. Contactless checkouts will also prevail, removing all the need of stopping the customer at the end of the shopping experience and, again, promoting convenience and creating totally different store experiences.
Digital twins can be a great data and analytics tool to perform different simulations and achieve the best trade-off.
Such digital twins can also incorporate personal shoppers that are using the store to fulfill online customers.
Technology may also help the replenishment processes that happen inside the store. Real-time continuous monitoring of stock on the shelf allows for triggering the quantities that need to be replenished and alerting for stockout situations. To feed this decision process a mix of tech and data can be deployed. Cameras that monitor the depletion of a shelf and/or algorithms that run in the background to detect real-time anomalies in sales are great tools to support this process.
Store warehouse operations can also be automatized, sorting the products that need replacement, and tagging them per section of the store, for a faster operation with lower errors. Great tech startups are emerging in this field (see, for example, Fabric).
Labeling prices and promotions, a heavy effort task can also be done with small electronic devices near the shelf, as well as in-store interactive catalogs and maps, that help the customer through his shopping journey, removing the time-consuming tasks of guiding the customer through the shop. Walmart has been a leader in these endeavors.
As labor costs tend to increase, store profitability benefits from an analytical approach to workforce management. This technique, belonging to the field of people analytics, uses data to leverage workforce dimensioning, staffing, and retention.
The correct dimensioning of people at stores balances the service level with the operational costs and includes store-specific characteristics, such as demographics and worker preferences, to predict the future needs of labor per each sector of the store, identifying specific needs for recruitment training in the short and long term.
After dimensioning the team, the store labor scheduling is a crucial step to ensure that a well-designed chronogram is delivered every day to assure all the tasks that are needed, according to the current workforce and set of skills, while respecting legal obligations and consumers’ demand.
By: Pedro Amorim
