Dashboard Truths
Your average handle time is probably lying to you.
Most contact centre dashboards lead with averages. They are easy to calculate, easy to explain, and often wrong about what is actually happening on the floor. Part 1 of Dashboard Truths is a short, free guide to the handful of statistics that decide whether a wallboard tells the truth.
The answer is not one better number
Swap the average for the median and the ten calls above look calmer: a typical call of 6 minutes. But the 48-minute call is probably the most important one on the list. Somewhere inside it is a confused customer, a broken process or a system that failed. The median hides it completely.
The same thing happens at scale. In the synthetic month used throughout the guide, a system slowdown stretched a block of calls for three hours on one day. The median barely moved. The average rose, mixed in with every other cause. Only the 90th percentile showed the incident clearly.
Flatten for the typical view, but never hide the tail. Every tidy figure on a dashboard should sit beside one that shows what was tidied away.
What Part 1 covers
Ten short chapters, one worked month of data.
Mean, median, minimum and maximum
What each one measures, why contact centre time data leans to the right, and why the shortest and longest calls usually belong on a data quality report rather than a performance one.
Percentiles in plain language
“Nine in ten calls finished within 12 minutes” means something to an agent, a team leader and a board. Why P90 and P95 show the calls where customer experience breaks.
Same data, different answers
Spreadsheets, databases and BI platforms do not all calculate percentiles the same way. On ten calls, three common methods give answers from 9 to 44 minutes.
Trimming and winsorising
Two ways to flatten the extremes, how they differ, and the trap in both: they turn down the part of the data where problems show up first.
Small numbers, big swings
Why a new starter with eight calls can look like the fastest or slowest agent in the building, and what minimum volume to set before anyone is ranked.
Honest tiles and a checklist
A before-and-after dashboard built from the same data, labelling rules, and ten questions to ask of your own reporting.
Every chart and figure uses synthetic data: one invented month for a generic inbound contact centre, 12,906 calls across 40 agents, generated to have the shape real contact centre data has. No customer or organisational data has been used. The patterns are real; the numbers are not.
Where it fits
A misleading dashboard is a foundation problem.
A four-hour call that was really a stuck session. A hundred one-second records that were never conversations. A bad day that only shows up if you know where to look. Those are not reporting quirks. They are data integrity findings, and data integrity is one of the three foundations in Foundation First.
If an organisation cannot trust its own handle time figures, it is not ready to measure whether a new platform or an AI deployment has made anything better.
Free guide
Dashboard Truths, Part 1, as a PDF.
Thirteen A4 pages, written for the people who run contact centres and the people who build their reports. No formulas to learn and no platform to buy. Tell us where to send it and it’s with you in a minute.
Coming next in the series
Three more parts, the same month of data.
Part 2: Voice and sentiment metrics that mean something
Sentiment trajectory, talk-to-listen ratio, silence and overtalk, audio quality, and why poor audio can quietly corrupt sentiment scores.
Part 3: Choosing the right chart
Which charts work for operational data, and which ones mislead.
Part 4: Analysing with AI
What AI analysis gets right and wrong, tested against a dataset with known answers.