Hussein Kamel, Senior WFM Consultant at Teleopti, looks at the best ways to work with Average Handling Time. Shorter contact durations cannot be demanded from agents, but instead the AHT must be properly examined, processes adjusted and agents assisted.
When creating forecasts, you are predicting volumes based on historical patterns, seasonality, special events, etc. However, there is also the other elephant in the room: Average Handling Time (AHT). Yet, though AHT merits attention, it rarely seems to get its equal share of the focus in a contact center’s operations. Interestingly, a reduction of 20% in AHT is equivalent to an equal reduction in volume on your overall staffing needs.
Most organizations are looking toward reducing their call volumes through better self-service solutions, social media, and pushing out information to customers. Yet, reducing AHT is also a strategy that centers use, and should be using even more, to reduce costs and increase efficiency. It is worth noting that we see a lot of approaches to AHT which offers plenty of opportunities to streamline contact durations. The following key points are general ideas about how to approach managing AHT reduction plans.
Yes, it is necessary for agents to see their AHT so they’re aware of how it is trending, but if you ask your agents to drop from a four-minute call to a target of a three-minute one, they will most probably do so, but at the expense of customer experience. Of course, this does not mean that higher AHT makes happier customers (that tends to be another center legend). However, it means that if agents are thinking they must cut down their call time, they will talk faster, make mistakes, brush off customers, and overall be stressed about how fast they need to hang up and get on to the next call. They won’t be focused on customer resolution or satisfaction. So, how do you approach reducing AHT?
A first step is to create a bell curve analysis of AHT. A bell curve is a tool to measure how much variation there is from the average. AHT will always follow a bell curve pattern with differing degrees of variation. Follow this link for more on bell curves.
For example, let’s assume you have a target of three minutes, and your center is achieving an average of four minutes. You are above the target by a minute. Not good. Once you look at the variation of the data using a bell curve analysis, what do you find? Are most of your agents 30 seconds above or below the four-minute average, with the same percentage of variation from the average? Does the bell shape look tight and uniform? In this case, you see low variation in the data.
Or, are some agents hovering around three minutes, whilst others are up around the five, six or seven-minute mark, thus skewing the data for everyone else to have an average of four? Does the bell shape look loose and spread out? You then have high variation in the data.
If the data shows you have low variation for the call durations (everyone more or less obtaining the same AHT – say, 30 seconds up or down from the target), and at the same time you are off target, it means the problem is not an issue with the agents, it is rather something at the process level. Granted there will be a few agents at the far end of the curve, but just a few doesn’t matter.
So, how do you move from four to three minutes? It is by understanding which main types of calls have the highest impact on overall AHT, and trying to re-engineer the processes of those calls to make them shorter. Are the systems slow in pulling the data for the call, does the agent need to use “hold” to do something away from the desk, ask permission, find certain information or get approval from their supervisor? Do they have to follow troubleshooting steps that could be made easier? You need to unload baggage from the process itself to make the call simpler, and once you decide on what to change, you train your agents and coach them on the new changes. Once this starts being implemented, everyone begins moving together toward the target the center is required to meet.
The other scenario is that you have variation in the AHT data with some agents at three minutes, and others at five, six, seven, etc… Why? For many reasons.
A good question now would be, what if, for these agents with high AHT variation, you reengineer and improve processes for calls, just as you would for a center that has low AHT variation? Would that work? Mostly no, since the “process” is already out of control. You need to get agents back in control, and then improve the process.
If, as a metaphor, your agents are soldiers, and supervisors are officers, you cannot ask the soldiers to march from point A to point B, unless they learnt to march together, turn, and follow instructions at the request of their officers! Otherwise, it’s going be a long slow march. In real-world terms, supervisors need to be working closely with agents to see where there are problems and figure out how to get them all up to the same level, whether that is stress management or competency development.
To repeat for emphasis, if you tell an agent to get their AHT down from four to three minutes by next week, most probably she/he will do it, but you are not sure how, and thus you expose your customers to the law of unintended outcomes. This is like asking a chef to make an omelet for 5 people with 2 eggs. You might get one, but you have no idea what else is in there, and it probably won’t taste very good.
Remember, you want to make customers happy as much as you want to be profitable. Happy customers, along with low AHTs, come through a refined contact process and well-managed, well-trained agents.