Ask a retailer to choose between a mobile point-of-sale or queue sensor and the likely answer is mobile. The reason is simple. A mobile device is a tool that speeds and adds convenience to the checkout. A queue management system is passive. It measures, monitors, and predicts queue behaviors.
Amazon Go tries to do it all. It works when the company controls the store, application, and user history (see below). Most retailers cannot control the ecosystem. Only the store. And yet, retailers cannot run a multi-million corporation based on the managers’ acumen. Optimizing service at the checkouts needs a solution for queue management.
Queue Management systems capture behaviors in real-time. They provide data on how many people are standing in the queue per period of time, and for how long. Moreover, the solutions predict how many cashiers should be active to prevent queues.
The streaming data allows the system to defined service. Common models include “One in Front” and “Serve 90% of Customers in Less than 3 Minutes”. In First Touch scenarios, the objective can be “95% of orders done in less than 1 minute”.
The business values are costs and service. The system prevents under-staffing or over-staffing. And the checkout is managed to the Customer Service Model.
Checkless Mobile Payment (Amazon Go)
Amazon created headlines with the introduction of Amazon Go and buying Whole Foods. The two events are connected.
Amazon Go is a checkless payment solution. The solution requires three systems. First, each product must have a wireless tag. This is a supply chain issue on how to identify items. The interesting tech is what Amazon refers to as Sensor Fusion.
Second, purchase history is the secret to the success of Amazon Go. From a customer point of view the challenge is the accuracy of the item. Consumers will have a problem if the solution charges for a large bottle of ketchup, instead of a small one.
Last point is that everything must work in real time. Everything! The security gateways need to know if the solution recognized the user, items, and payment. The purchase history needs to correct. And so on. This solution requires massive expertise, infrastructure, and capital. Other retailers need to solve queues in a different way.
Wait Time as Customer Service Model
Time serve as the ‘measuring stick’ for many retail activities. We monitor how long it takes to unload a track. We check how long it takes to unload a fulfillment cart. Since customers dislike waiting in line, Wait Time is a good metric for the quality of service.
Many retailers use Average Wait Time as a Key Performance Indicator. This is a mistake. More effective is using Customer Service Models.
A good service model achieves two goals. It provides a metric of achievement. And it contains a measurement of success. In Queue Management, we need the metric of Wait Time and percentage of customers.
A core policy, for example, is “serve 90% of customers in less than 3 minutes”. It will also contain “serve 51% of customers in less than 60 seconds”. This means the Average Wait Time is less than 1 minute. We can also set “serve 98% in less than 5 minutes”. This is also how we set the Outliers KPI of “bad service” at 2%.
Frontline Service Management
In Big Box supermarkets, the main bank checkouts continue to dominate. This is the story of Walmart, Target, and Tesco. And it works regardless if the frontline layout is a single main bank, double-deck, or duplex. A bulk checkout area requires more than a sensor above the waiting zone.
Queue Management for frontlines includes sensors and predictive analytics. The sensors count the number of people in line, how long they wait, and their direction of motion. We also need door-sensors to know how many people are in the store, and to calculate the stay time in the store. And predictive analytics says how many cashiers should be active now and soon (i.e. in 15 minutes).
Queue Flow Rate
Queue Management is also important when the shopping starts with waiting in line. The Quick Service Restaurants (QSR) such as Starbucks and McDonald stores has limited resources. Their challenge is the queues are the customer’s First Touch.
In QSR, Post Offices and others, the 3-5 people team mans the counter service, drive-thru, and back office. There no option of opening more checkouts. In such situations, the adaptation to actual demand stems from the Queue Flow.
Queue Flow solutions measure the exit rate from the queue, in seconds. The speed of the queue depends on the Order Time. And it is regardless of how many service counters are open.
The business value is that the service level stays the same regardless of demand. It does not matter how many customers are waiting in line. The quality of customer service is in how fast people move.
Bringing It All Together
The checkout is the highest friction point in shopping. Years ago, Amazon solved the online checkout with 1-Click. And Amazon Go is the solution for the physical store. Their guiding philosophy is
“Always migrate your audience to the path of least resistance”.
Checkouts are not going away. In Big Box Stores, Airports, and QSR, managing queues is a priority. In a high competitive venue of retail, superior service is a must for survival, and success.