Impact Chart

What it's for

Most contact center metrics are averages, and averages hide their own composition. When AHT moves, the number alone won't tell you whether performance actually changed or the mix of work changed - and those two causes need completely different responses.

The Impact Chart separates them. It shows which groups drag the average higher and which pull it lower, so you can see where effort actually pays off. Impact is a function of both how far a group sits from the average and how much volume it carries - which means the biggest driver is rarely the most extreme performer. 

Improving a high-impact group by even a small amount produces an outsized flow-on effect to the overall number.

The easiest way to read it is as the question: "What would the average be if this group weren't here?" For example:

• "What would our average handle time be if we removed this enquiry entirely?"
• "If this high-performing agent left the contact centre, what impact would it have on our average predicted satisfaction?"

How to use it

• Find it in the Charts widget at the bottom of the screen.
• Only available on average-based metrics - handle time, Predicted Resolution, Predicted Satisfaction, survey scores, and so on. Not applicable to sum-based metrics like interaction volume or total cost.
• Hover over a bar to see the group's value, the overall average, and the calculated impact - for example, "Alissa adds 7.16 seconds to the overall handle time"
• Sort by impact ascending or descending, so the biggest drivers surface immediately.
• Shows the full set of dimensions rather than just the top or bottom 5.

Use cases

Plan an automation or deflection project without a surprise

Say you're about to deflect password resets to self-service. They're high volume and quick to handle, and the Impact Chart shows that enquiry type is currently pulling your overall handle time down by 45 seconds. Remove it, and your overall handle time goes up - even though nothing actually got worse and the project was a success. Knowing this in advance means you can set the right expectation with stakeholders, rather than explaining an apparent negative impact after the fact.

Prioritise coaching by leverage, not by ranking

Sorting agents by handle time surfaces the slowest. Sorting by impact surfaces the ones actually moving the number. An agent 20 seconds above average across 3,000 interactions has far more impact on the overall metric than one 3 minutes above average across 40 - and is a far better use of a team leader's coaching time.

Find where customer experience is quietly lagging

Switch the metric to Predicted Satisfaction or Predicted Resolution, and the dimension to enquiry type. The chart ranks every enquiry type by how far it drags the score down, accounting for how often it happens. A rare enquiry type with poor satisfaction is a coaching note; a common one sitting slightly below average is a process problem worth a project. Because the chart shows the full list rather than just the bottom 5, mid-table drivers carrying real volume don't disappear from view.

Want to see more?

See the Insights #7 OI University module.