The industry standard of using AHT to measure the efficiency of contact centers and CX teams is helpful for top-line performance trends but lacks any actionable insights for how and what to improve.
CX and Operations leaders are constantly trying to decrease their Average Handle Times to drive productivity but often struggle to effectively do so. The truth is, every front line team has measures they can take to deliver solutions faster but identifying those measures and understanding how to solve them has repeatedly proven to be a challenge.
The industry standard of using AHT to measure the efficiency of contact centers and CX teams is helpful for top-line performance trends but lacks any actionable insights for how and what to improve. Rather than relying on lagging outcome metrics, Fin’s data set is able to calculate ‘true handle time’ per ticket and by task type across all tools and applications for a more granular view into where your team’s time is going and what your largest opportunities are to drive efficiency and decrease costs in your operations.
Segmenting AHT enables you to prioritize problematic, high-volume case types and then size each incremental opportunity based on what your top performing agents are already able to achieve. This helps teams set realistic performance goals and prioritize the right initiatives.
Once you know where to focus, the next step is identifying the root cause of performance issues. To do this, it is critical to understand the exact processes agents follow when solving a case to uncover actionable opportunities to drive efficiency like:
- Outlier performance / agent variance
- Inefficient tool or knowledge base usage
- Unnecessary context switching or process steps
- Candidates for automation and RPA
Here’s How Fin’s Data Structure Allows Teams to Calculate and Segment ‘True Handle Time’:
Fin’s Active Page Events give you the ability to track every process step across tools and understand the total number of unique work sessions needed to complete a case. This structure makes it easy to understand the efficiency of workflows and different agent processes on a much deeper level than AHT. It also allows for targeted intervention and review when patterns diverge from the norm.
Active Page Events
Going one level deeper, our custom events allow you to look inside a web-page for more specific actions taken during a case like understanding specific buttons being clicked, keystroke behavior in tools, time spent searching for knowledge base articles, work done in text boxes, etc.
The intersection of these two data sets gives organizations deep coverage across all of their tools to understand how work is being completed on each case. With a detailed breakdown of where your team’s time is going and what processes look like, you can systematically optimize AHT and address any productivity, process, and product issues holding agents back.