It is common knowledge that technical service and support is a high turnover industry. In fact, global benchmarking data from 2020 shows that annual agent turnover was about 40% for enterprise agents and a staggering 97% for managed service providers! This is problematic for numerous reasons, including the high cost of turnover and the loss of knowledge and expertise that accompanies agent turnover.
But the drivers of agent turnover are well known and controllable. By adopting industry best practices that reduce and minimize turnover, IT service providers can take control of turnover, thereby reducing turnover related costs and loss of expertise. Additionally, the recent introduction of AI tools powered by machine learning has proven to be a powerful antidote to the decades-old problem of high agent turnover.
Annual Agent Turnover is the percentage of all agents that leave a support organization over the course of a year. Let’s say, for example, that the average agent headcount for your service desk is 45, and that 15 agents leave and must be replaced during the year. The annual agent turnover would therefore be 15 ÷ 45 = 33.3%.
Some organizations make a distinction between good turnover and bad turnover. Bad turnover is when an agent leaves an enterprise or MSP altogether because of performance issues or to pursue other job opportunities. So-called good turnover, by contrast, is when an agent who is otherwise performing well is moved or promoted to a non-customer facing position in the service desk or accepts another position in the company that is outside of the service desk. Both types of turnover are included in the calculation of annual agent turnover because both types of turnover create a vacancy that must be filled.
Agent turnover can be detrimental to a service desk because it typically results in a seasoned agent being replaced by a less experienced agent. When there is turnover, the knowledge and experience of the agent leaving the service desk walks out the door with them. For those who have worked in a service desk, you know how painful this can be! Industry estimates place the cost of replacing an agent at more than $12,000 in North America. This includes the cost of identifying, screening, recruiting, and training a new agent, as well as the indirect cost of lower productivity that results when a new agent encounters the learning curve of a new job.
One of the primary cause-and-effect relationships in the service desk is between agent job satisfaction and agent turnover: high job satisfaction is strongly correlated with low agent turnover rates and vice versa. The reasons for this are fairly obvious. When agents are satisfied with their work life, they tend to stay put. When they are unhappy at work, they are more likely to leave. It is important to note, however, that turnover can be controlled by proactively managing agent job satisfaction.
The cause-and-effect diagram below shows that the key drivers of job satisfaction are training, coaching, and career pathing. By optimizing these metrics, we can ensure high job satisfaction, and hence low turnover.
Using benchmarking data, we can examine the relationship between Job Satisfaction and Agent Turnover below. The correlation in this chart is clear to see. As agent job satisfaction increases, agent turnover decreases!
Now, let’s examine how training and career pathing impact agent job satisfaction. Once again, using benchmarking data we can see in the correlation charts below just how powerful the impact of training and career pathing is on agent job satisfaction. As annual training hours increase agent job satisfaction also increases. And having a formal career path increases agent job satisfaction from an average 72.4% to 80.7%! Remember that increasing agent job satisfaction has the effect of reducing agent turnover.
The outsourcing market for IT service and support is crowded with hundreds of competitors. With so many vying for a limited share of market the industry is extremely competitive. Normally, this would be a good thing for customers as MSPs compete for their business. However, many in the outsourcing space will underbid contracts in an effort to win market share. The all-too-common result is that outsourcing contracts operate at a loss.
In an effort to break even, or earn a small profit, some service providers will do everything possible to reduce their costs. This includes but is not limited to paying low wages, not investing in training, and offering few if any career path opportunities for front line agents. These factors have a devastating effect on agent turnover, which as mentioned earlier, is more than double that of agents who work in the enterprise world.
Fortunately, there’s a solution to the decades-old problem of high turnover for both enterprises and MSPs. That solution is the smart application of AI – artificial intelligence.
The beauty of AI powered by machine learning is that it will take us places we never dreamed possible. Nevertheless, we can look at the repeatable success stories in the ITSM industry and make some reasonable predictions about where AI is going. These demonstrated successes include:
AI has, and will continue to be a disruptor in the industry. Initially it will eliminate the need for agent-based commodity support – think Microsoft Office, Windows, password resets, and other easily resolved problems. But as machine learning makes each deployment of AI progressively more intelligent, even the most complex support provided by today’s customer facing agents will be replaced by more intelligent bots. Yet the vast majority of agents see AI as a good thing because it will transform careers for the better.
Much like today’s auto industry assembly line workers are engineers monitoring computer screens while robots actually build the cars, the support technician of the future will become a support engineer who monitors, coordinates, and directs the efforts of the AI bots. Needless to say, these support technicians will be highly trained, well-compensated, and have plenty of career opportunities. This, in turn, will solve the problem of high agent turnover once and for all.