AgentBalance, as a solution that reveals hidden psychological parameters of contact center agents, can work well as a standalone solution in such environments where Quality Management processes are either missing or deployed in a simple way.
However, where AgentBalance becomes a real deal breaker is a situation when team leaders combine their QM data such as Average Handling Time and First Call Resolution with data obtained through AgentBalance. Why and how?
- First Call Resolution combined with Level of Energy invested into executing job tasks – AgentBalance reveals the portion of agents’ mental energy that is spent on the job the agent is basically paid for. Any distractions causing agents’ focus to move from the conversation with the customer means that the energy spent on the job will decline. This is what the team leader can build their observation on. Maybe the agent was distracted by other team members, working environment or even unsatisfactory relationship with the team leader. Even worse, the agent could have mentally resigned from the job and it is only a matter of time when this will project into their decision to leave the contact center for good. Of course in all these cases it only makes sense that the First Call Resolution would start dropping.
- Average Handling Time with Level of Energy – Being effective in handling customers’ requests in optimal time requires the agent to have sharp focus and clear mind. A general requisite for this state of mind is that the agent is well rested. Being tired or near burnout simply doesn’t allow the agent to stay focused so the time needed for handling a single request goes up. There may well be other reasons for this situation but checking agents’ level of energy in such scenarios is what I consider the single most important step.
- Customer Satisfaction with Attrition Index – An agent who is already thinking about leaving the contact center job can hardly maintain high level of customer satisfaction as this agent’s level of overall motivation must have already dropped below critical value. Agents presenting high risk of leaving the job should be monitored much more often using any means available – listening to calls, speech analytics and customer feedback. It is wise to spend extra time with these “endangered” agents and decide, based on their performance, to either keep them in-house, or make the departure as smooth as possible.
- Sales or Collections with Job Fulfillment – The Job Fulfillment parameter provided by AgentBalance shows how the agents enjoy their current assignment. If this parameter starts declining it may be a clear sign that the agent might not be the right person to be assigned to this difficult and often exhausting task. Consider relocating otherwise well performing agent to a different task because otherwise you risk the possibility of demotivating the agent completely which would mean losing the agent in matter of weeks.
Of course these correlations represent only an example of how AgentBalance data relate to real life Quality Management data available in most contact centers. Skilled team leaders will come up with their own observations that will help them not only decrease agent attrition, but also improve their teams’ overall performance.
– Václav Martin, Managing Partner Trade Design