9 Queuing Metrics You Should Have at Your Fingertips

June 28, 2013Perry Kuklin

The ebbs and flows of a waiting line don’t have to be mysterious. In fact, queues can be quite predictable if not extremely manageable with real-time queue monitoring and analytics. Today’s technology gives managers more than historical averages, offering actionable intelligence to balance the needs of customers and the operational demands of business. Below we list nine key queuing metrics you should have access to at any given moment, and over time, to maximize the efficiency of a waiting line and the satisfaction of customers. These metrics are important individually and, as you will see, are influential to the whole, forming a big picture of queue management and its impact on customer happiness.

queue-length

1. Queue length

What it is: How long the line is in terms of number of people waiting. Why it’s important: This most basic measure is where queue management starts and ends. How many people are waiting? When you can access this number at a glance for each individual queue under your watch, you have the basis for all to follow.What it is: How long the line is in terms of number of people waiting.  

wait-time

2. Wait times

What it is: How long, on average, people are kept waiting in line before reaching a service agent or cashier. Why it’s important: Customers will only wait so long. Perhaps for your customers, that acceptable wait time is 2 minutes. Maybe it’s 5. By tracking how long the wait is right now, you’ll know if your staffing levels need to be increased or if your wait times are within acceptable limits.

queue-abandonment

3. Queue abandonment rates

What is it: The rate at which people leave the line before completing their transactions. Why it’s important: While many factors affect queue abandonment, the fact that people are leaving should concern any manager. Be alert to this metric and watch for sudden increases or higher than normal queue abandonment rates so you can immediately troubleshoot the source of the issue and resolve it. You can also take steps to reduce average abandonment rates by implementing best practices of a better customer experience  (keeping customers entertained and occupied, for example).  

predicted-wait-times

4. Predicted wait times

What is it: Based on the above, this metric identifies how long people are likely to wait in line for service. Why it’s important: This information can also be used to inform customers of their expected wait time, which can appease even the most impatient in the bunch. Predicted wait times also allow you to anticipate soon-to-be-exceeded acceptable limits and respond with additional service staff. Likewise, you can anticipate over-staffing issues and work swiftly to cut down on unneeded staff, analyze how well a queue is organized and if there are measures that need to be taken to expedite the wait.

  service-times

5. Service times

What is it: How long it takes customers, after waiting in line, to conduct their transactions or complete the services they’ve waited for. Why it’s important: Total wait time can be broken down into the time spent waiting in line and the time to complete the actual transaction. Being able to break down wait time in this way helps you determine the source of longer-than-desired total wait times by determining the source of the long wait. Are service agents causing a line to drag, or is it primarily the sheer length of the queue?  

peak-service-times

6. Peak service times

What it is: The hours, days, weeks, months, etc. when queues are busiest. Why it’s important: When you are prepared to expect crowds first thing in the morning, at lunchtime, in the evening, or on weekends, lines can be staffed accordingly and more service stations can be opened to accommodate larger numbers of people. Being able to predict this metric also means that you can inform customers of peak and off-peak hours, allowing them to decide on their own if that is a time when they wish to frequent your business.  

service-agent-efficiency

7. Service agent efficiency

What it is: The number of customers served by agents in a given timeframe. Why it’s important: Perhaps there’s nothing wrong with the physical design of a queue, but rather the problem lies with how efficiently customers are being served. With access to this metric you’ll shine a light on your service agents and their ability to serve customers in a timely fashion.

  service-point-utilization

8. Service point utilization

What it is: The number of service points open and in use over a given timeframe. Why it’s important: Are busy times being properly staffed? Is there an overstaffing during slow times? The efficiency of your queue and your service staff depends heavily on this queue metric.

  predicted-service-times-and-allocations

9. Predicted service times and allocation

What it is: This metric takes into account agent efficiency, average service times, and service point utilization over a given timeframe to predict service time and how services will be allocated across agents. Why it’s important: This metric combines other metrics to help you reach that ideal configuration of available service stations and the most acceptable service time for customers.   The ability to measure changing variables of a checkout line in real time eliminates the guesswork that can sometimes accompany queue management. Instead of being reactive, managers can be proactive, as they are far more informed about their customers’ habits and the performance of their service staff. Shorter wait times, consistency, and a happier checkout experience for customers are the goals – the metrics gleaned from queue management technology make it possible to check off all of these goals. Talk to a Lavi expert for a demonstration of our queue analytics and monitoring technology.

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