Metric Sweet Spots – Correlating Metrics for Optimum Productivity Against Goals
In Blinded by Averages we looked at getting beyond averages to individual performance, as a sure way to increase productivity. We showed how teams that collectively hit targets may be getting there on the shoulders of relatively few agents (typically, one third), while just as many drag the results down, their performance hidden by the focus on averages.
Once a company realizes this and begins using systems that uncover and improve individual metrics, they also discover another component of running at optimal levels: key metrics a!ect each other, and finding the most productive combination of targets can yield tremendous results. By examining how KPIs interrelate, rather than viewing them as separate goals, organizations can better set targets for each. We call this the ‘sweet spot’ – and those spots are often not where you’d expect them to be.
The Tightrope of Corporate Goals
Organizations typically have goals that require their contact centres to maintain a balancing act. Perhaps productivity goals require that Average Handle Time (AHT) be kept low, but an additional product sales goal has been added. Maybe Quality goals need to be met without spending either too long on a call or, conversely, rushing the customer. How can an organization know where the optimal balance lies?
Only by understanding how these metrics work with each other, and how the most successful agents balance them, can all agents be made more effective. This kind of analysis is only possible when feedback platforms such as Orbit’s Compas™ provide the detailed data needed to see the full scope of the situation. To examine this concept in action, let’s consider how AHT affects other parameters, by looking at some concrete examples.
How long does it take to make a customer happy?
This example, from a North American insurance company contact centre, illustrates how the top-performing 8-tiles have AHT averages within them of 166 and 141 seconds. As shown by the boxes highlighted in red, longer handle times do not result in improved call quality. The longest handle times are, in fact, associated with some of the worst results.
Based on these results, the organization can explore, through coaching conversations, why these results are as they are. What are the best agents doing to get those AHT results while maintaining customer satisfaction? In particular, what are the agents in the second 8-tile doing to get off the phone so quickly and leave their customers almost as happy as those agents who took up to 20% longer to complete their calls?
This example, also from a North American insurance company, illustrates the improvements that can result from cross-referencing metrics and training agents to meet new ‘sweet spot’ goals. The ‘before’ data on the left shows almost no correlation between AHT and quality. Longer handle times seemed, in fact, to increase dissatisfaction. The Quality goal of 90% was only being met by half the team, with three of the 8-tiles failing to make the required minimum grade. And the AHT goal of 300 seconds was not being met nearly enough.
The ‘after’ data from just three months later shows how focus and training improve goal alignment. By focusing on the most critical Quality components for their business, making those clear to agents, and setting tighter protocols for attaining the AHT goal of 300 seconds (which pleased customers, too), the organization was able to align Quality and AHT efficiently and effectively to meet their organizational goals.
Keeping Customers on the line doesn’t always close the sale
It’s frequently believed that sales increase when agents spend a little more time on the call. Orbit’s analyses, however, clearly demonstrate that it’s often not true. In fact, the most effective agents make their sale and get off the call faster than their peers.
This example from a telecommunications company shows how the top performers outsell the next most successful group 2 to 1, while averaging 8% lower AHT. These agents have found the sweet spot between time and conversion in order to perform better on both metrics. Most tellingly, this data illustrates an inverse relationship: the longer agents spend on their calls, the fewer sales conversions they’re achieving.
In another telecommunications example, we find a similar situation. The highest sales per hour results are being achieved at the lowest average handle times. Not only do these results demonstrate what agents should be able to achieve, they also identify which groups of agents aren’t performing to either metric; critical information for targeting improvement efforts to individuals.
These results show exactly what is possible in terms of performance, allowing the organization to use the winning methods of the top tiers to coach the bottom tiers towards better performance.
What the Sweet Spot Means For You
Without cross-referencing metrics in this way, organizations are left to guess at what will influence their most important goals – and if popular wisdom is guiding them, they will often guess incorrectly. When analyzed to correlate results, organizations can precisely determine where their targets need to be for each metric to yield the optimum performance against their overall goals.
Customers are happier, efficiencies are increased, agents are more focused, and the bottom line improves. Want that for your organization?
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