In 2018, Forrester Research conducted a study of thousands of American retail grocery shoppers to understand how they decide where to shop.1 Not shockingly, shoppers noted that location and price were their two top priorities; however, they also ranked length of checkout as their third highest factor in deciding whether or not to go elsewhere. “Retailers that prioritize checkout efficiency aren’t only positioned to satisfy customers, but also attract new shoppers who aren’t willing to wait in long lines.”1
For this reason, the study of waiting in line will continue to be an important topic to retail leaders in 2019 and beyond. In the retail industry, we call line optimization queue management. It refers to determining how to reduce wait time and improve service levels at checkout to win customer loyalty. Today’s blog post will dive into multiple facets of queue management. First, our discussion gives an overview of the anatomy of a queue. Then, we outline intricacies between different types of queuing within retail stores. Finally, we cover how retailers can use this information to manage queues well.
The structure of the queue: a brief introduction
Let us begin by defining the internal skeleton of the queue. Its structure stretches from the waiting line to the end of cashier checkout in the front end; this anatomy is slightly different at service counters. Queues can be finite, or inclusive of an unchanging number of customers, or infinite, allowing shoppers to continually enter over time. There is also a queue’s layout to consider, from combined queues, or one line that feeds multiple registers, and single queues, which use one line per register. From an equity standpoint, combined queues are often perceived as fairer than single queues, although situations can vary as to which is faster.
Regarding the flow of the front end system, there are five phases in queuing: arrival, unloading, scanning, transaction and bagging. Some of these elements are non-existent in particular retail environments (i.e., deli counter queues.) Front end wait time is most highly dependent on a customer’s basket size, the physical structure of the checkout space, cashier efficiency, the customer’s readiness, the chosen tender type, internal movements (i.e., an employee doing two tasks simultaneously), best methods and more.
Queueing profiles and their attributes
The main focus of traditional queue management is optimizing the tipping point between servicing customers with the resources at hand versus adding a new register that will increase labor costs. However, queue management now considers additional factors, especially with the onset of self-checkout, express lanes, mobile checkout and even RFID checkout like in Amazon Go stores.
Self-checkout often gives the perception of less wait time because individuals are scanning and bagging their own items. From a labor standpoint, it reduces the number of employees per register, since one employee can oversee five or six registers at a time. Notably, recent studies2 showcased that mobile technology for self-service and manned queues helps provide a faster shopping experience and are desired by consumers.
Express lanes are meant to validate customer perceptions within the total queueing experience. Shoppers with few items (i.e., the grab-and-go type) choose a longer express line than the shorter traditional queue because they believe the express line will move faster. In return, this keeps traditional queues from building up for the clientele with full shopping carts. Thus, express lines are less about balancing workload and more about meeting customer service expectations.
Best practice and queuing technology
So how do retail leaders best utilize this queue management information? First, leaders know that queue management is about optimizing a store’s checkout technology and associate knowledge to meet customer expectations, even at different times of the day under different circumstances. For instance, early morning shoppers who are most likely rushing to work will be much less likely to wait than the midday crowd. Retailers must know their customers and customer expectations well. Second, retail leaders plan for those expectations using labor and queue standard-based staffing and scheduling. In other words, optimal technology solutions anticipate labor requirements as well as service needs so standards are not violated.
Once the plan is in place, operators can expect the unexpected. For this, retailers create tolerance standards and safety valves for their queues. Tolerance standards refer to the number of customers that can acceptably wait in line based on a company’s go-to-market strategy at different times under different circumstances. For instance, a “1 + 2” tolerance means a retailer allows three people in line (one shopper checks out while two wait) before calling in reinforcements. This tolerance may exist for a specific time of day, or day of week. Every retailer sets these differently. Remember that customer expectations and queue standards are equally important for service department lines like the deli versus the front end; effective queuing logic must take service department staffing requirements into account, too.
Safety valves are protocols used to divert traffic to additional registers or checkout mechanisms when tolerances are breached. This is where associate knowledge comes into play. Associates must be trained to notice when tolerance standards are not met, thus enacting the safety valves to keep customer perception and throughput at an acceptable level. Technology can help here. Not only is it useful in the training piece of associate awareness, but mobile technology also makes the execution of the safety valve much quicker. The more queues are measured, and the more variables that can be taken into account ahead of time, the easier they will be to manage.
Unfortunately, many retailers still plan for and react to queues in antiquated ways. Retailers looking to optimize their queue will find a technology partner than can consult on forecasted customers per hour to understand how customer flow will affect tolerance levels all throughout the day, even down to fifteen-minute increments. Also, technology vendors using best practices in queue management will offer valuable insight around optimal tolerances, as well as provide state-of-the-art tools like mobile technology to make transitions to safety valves easier.
In ending, the queue is a complex mechanism, one that business leaders to academic professors spend considerable time studying. In retail, optimizing the queue requires many facets. First, understanding its elements and types is key. Next, retailers can determine what is acceptable to their leaders and customers with the ultimate plan of winning over shoppers. Finally, utilizing world-class technology to plan for and react to queuing best-practice may offer significant benefits for retailers in their pursuit of excellence.
- Browne, M. (2018, August 23). For customers, the waiting is the hardest part: Shoppers willing to switch stores for faster checkout, study shows. Supermarket News. Retrieved from https://www.supermarketnews.com/retail-financial/customers-waiting-hardest-part
- O’Shea, D. (2019, January 15). Study: 73% of consumers want self-service technology. Retail Dive. Retrieved from https://www.retaildive.com/news/study-73-of-consumers-want-self-service-technology/546044/