In an increasingly omni-channel world, where customers want to be able to engage companies whenever and wherever they please, a more intelligent approach is needed to manage the skilled labor necessary to address this rising consumer demand. And not only in the voice channel, but in all of the communication channels as well. The contact center industry has spent decades refining the intricacies of forecasting, scheduling and intra-day tracking of adherence for inbound and outbound voice calls. The next frontier is wrestling with the management of the workforce across all of these channels. Unfortunately, these other channels don’t have the same dynamics as the voice channel, and you can’t use the same planning and forecasting techniques to manage the workforce efficiently in these non-voice channels.
Chat is a perfect example. Forrester notes that chat is the third most heavily used form of interactive customer communication after voice and email, but it is by far the fastest growing at about 8% per year. Aspect’s own research shows chat is actually even ahead of email. Unique to customer contact via the chat channel is the practice of assigning multiple, simultaneous chats to one agent. Assigning one chat contact to an agent is generally considered underutilization of resources due to gaps in time spent waiting for customer message composition after the agent composed and sent his or her reply. Without any other guidance, most workforce optimization managers would use some simple rules of thumb to estimate staffing levels required to meet service level targets. Their estimates are likely rooted in their experience with voice, but chat is a completely different world with different rules of conversational engagement, different timing, and different physical processes involved in working with multiple customers simultaneously.
Here’s an example to think about.
A team of chat agents has been assigned to provide customer service, with a maximum of three concurrent chats per agent. Using the pattern of historical chat volume, the Workforce Management (WFM) manager observes the average handle time of an employee handling one chat at a time and divides that by 3 (since each agent is handling up to a max of 3 sessions) then uses standard single skill voice channel erlang-based methods to arrive at a required number of agents for each time period to meet a 70% in 30 seconds Service Level Goal. Using this method, the staffing looks like the Current Industry Practice line below.
However, when an agent’s workload goes from one chat session to two and then to three, new dynamics come into play. Here are some of the more obvious ones:
- The agent is getting routed more chats from the queue
- From the perspective of a customer, that agent is now responding more slowly because they are working on replies to multiple other customers interleaved with their responses to a single customer.
- The agent is now switching mental and business contexts as their attention moves from one customer to another and some time is spent getting back up to speed on the contents of that conversation before composing a reply.
- Unproductive time can impact multiple customer chats.
The actual number of chat staff required to meet required service levels computed taking all of the dynamics of chat is shown in the Actual Staff Required line.
You can see that it’s much higher than what would be estimated using current industry practice.
Another way to look at this is from the perspective of service levels. In the chart below, the Current Industry Practice line shows that the contact center would be well short of their required service level if they were to schedule based on required staff computed by estimating handle time and using voice channel methods. Using the Aspect Multi-Chat Calculator, taking all of the particular dynamics of chat, multiple simultaneous chats, and multiskill staff into account, the actual service level would be very close to being met throughout the day if we staffed using the Aspect Model.
As we noted above, the industry has had years to think about how to forecast, schedule and track the voice workforce. Not so for other customer communication channels. When you start to peel back the onion, you will find a whole new set of metrics that we need to incorporate in our forecasting models such as: chat concurrency (how many simultaneous chats is the agent handling), agent composition time, customer composition time, agent wait time, customer wait time and number of messages exchanged in a session. For WFO professionals, it’s a radically different way of having to think about customer engagement.
Fortunately, Aspect is leading the charge in this brave new world of omni-channel customer interaction. For more information about the Multi-Chat Calculator and other features of Aspect’s Workforce Management solution, visit our web page or feel free to contact me directly at firstname.lastname@example.org