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Put Lean Forward Agent Training Into Action

Training for new customer service agents works best when conducted in a safe environment that allows them to learn by doing, make mistakes, ask questions and figure out how to solve problems or complete tasks independently. Recently we shared an article that made the case for lean-forward learning  for agent training. In this article, you’ll learn what it looks like in action and why active learning creates more competent, highly performing agents.

We have found that new agents that trained with an active learning approach are adapting to the live environment quicker and tend to stay in the job longer because their expectations have been set during their experience with the training environment.

Traditional vs. Lean-Forward Learning

Traditional training is instructor-led training supported by power points and provided at the trainer’s pace, rather than the learner’s. Traditional training is classroom based with an instructor, conducted on site, is a passive experience for learners and ends when the curriculum has been presented. Traditional training is also difficult to scale and expensive to fund. Quality metrics are usually introduced at the end which disconnects them from the processes and tasks new agents are learning. This results in expectations not being set appropriately during training.

One of the biggest limitations is that traditional training is based on the idea that content is training. However reading or hearing about something doesn’t bring it to life the same way experiencing it does. Active learning takes the content and turns it into activities that agents can interact with to learn by doing, rather than by listening. Energy and excitement in the room is much higher when people get to participate.

Traditional training based on content rather than activities also includes a lot of information that agents could access on their own as it’s not interactive or related to activities that agents will perform on the job, such as company history. There is a lot of excess information included in classroom training that isn’t really useful for on the job performance.

Active learning is learner-driven and can be conducted in the classroom or online. Learners lean forward, engaging with interactive “How to” content and learn by reviewing media cases, participating in systems training and watching expert interviews as they work “hands on” to solve a problem or complete a task assigned to them.

Quality metrics are introduced from the start to set expectations by enabling the agents to rate call simulations, be the customer to experience the other side of the call and score calls using quality surveys. Incorporating your company’s culture into the training is also critical in creating truly engaged agents who have a sound understanding of your customers and the experience they expect to have with your company. By incorporating culture into the learning process, agents will be better prepared to provide a level of service that results in meeting or exceeding quality metrics.

Collaboration is a key component of active learning, allowing the agents to share screens to teach each other what they’ve learned, compete in games using training material, and participate in role plays. The dynamic learning environment establishes community among the agents and promotes peer-to-peer knowledge sharing. And, because the environment is online, learning can become constant and continuous as agents sharpen their skills over time.

Simulators Provide Proof of Concept

While overhauling your entire training curriculum can look like a Herculean task, making iterative adjustments can provide proof of concept through real-world performance impact. Simulators provide one such opportunity.

Simulators are used to create as close to a real working scenario as possible to allow the agent to experience the task just as they would when in a production environment. Simulators reduce the learning curve and increase confidence levels, as learners’ transition to workers. Simulators are made available online, reducing setup time for classroom deployment which increases the number of trainees and classes, speeding up the implementation timeline. New agent confidence also grows more quickly.

A simulator can be used to replicate the most common transactions that a new agent will be required to perform. While it’s not a “real” system, the simulator will achieve an 80% resemblance to the real system and scenario in action by using fake account data. The use of fake data also speeds the deployment of new classes because the content is reusable and rooms don’t need to be reset.

Because simulators provide hands-on practice that helps them become more proficient at handling dispute cases, agents are more prepared for their transition to On the Job Training (OJT). Trainees are also better able to relate processes to the system because of the increased amount of practice they get through learning by doing.

It is important to note that simulators are not gamification applied to training. Gamification can often be associated with helping agents learn information. Simulators are about helping agents learn processes and how to handle scenarios they’ll encounter on the job most effectively by replicating the real-world environment. Gamification can be great to help agents learn about a company’s products or to improve a specific skill, but for real-world training based on content, activities, and reflection; simulators will have a better impact on proficiency and performance as agents move to nesting and transition to production.

From Simulations to Real-World Results

In real-world contact center training scenarios, a client to Sykes found that new agents with a lack of system experience were creating average hold times (AHT) of up to 1,232 seconds and 516 seconds in A-Hold time. None of the agents were meeting the forecasted AHT during nesting on their way to production.

Simulators were created to improve the agents’ system proficiency. After simulator deployment, 70% of the agents met the forecasted AHT during nesting. Contact center operations was able to show a reduction of 42% in AHT—exceeding forecast—and customer hold times were reduced by 58%.