Why average response time doesn't tell you where you're losing tenants

Friday afternoon, half past three. You call back about a damp report from last Monday and hear on the other end: "Oh, you're the first person who's got in touch." Not angry, not aggrieved, just tired. She hasn't spent those four days watching a stopwatch. She's simply switched off.

Two days later, your weekly report shows that your response time on reports that week was 1.8 days. Under target. Green figure. You act as if it's accurate. And in a sense it is, because you did indeed pick up 80 per cent of your reports within 24 hours. The problem sits in the other 20 per cent. And that other 20 per cent is almost always the same group of people.

The average is a blatant liar

An average response time under two days looks fine on a dashboard. But averages are disastrous to steer tenant communication by, because satisfaction losses concentrate in the tail. You don't lose a tenant because you helped 80 per cent of people quickly. You lose her because, in the one report that went wrong, she heard nothing for four days.

That pattern shows up in the Woonbond reports from the first half of 2025: one in five people who file a report say the landlord doesn't respond to maintenance complaints, and 27 per cent of all reports are about a landlord who simply never comes back. That isn't 20 per cent of randomly scattered cases, it's a fixed group of reports that structurally slips past the system.

The Aedes benchmark 2024 makes the pattern even clearer for repairs. If a report is resolved in one visit, tenants rate the process 8.5 on average. If four or more visits are needed, that score drops to 6.6. A drop of almost two full points on a ten-point scale, carried by a fraction of your reports.

The tail isn't chance, it's a cohort

The second problem with steering by averages is that it makes you think the tail is random. As if a handful of reports each week just happen to take longer. That's almost never the case. If you split your incoming reports, you often see the same profile coming back.

Three cohorts where you're most likely to lose track of the tail:

Non-urgent reports via the wrong channel. A tenant emails on Tuesday about a damp problem that isn't urgent. No automatic confirmation, no ticket number, no status. On Thursday she calls because she's heard nothing. The front desk logs it as new, because they can't find the email. By Friday it exists somewhere, but now in two systems.

Repeat reports on an open ticket. The first report moves fast: the engineer visits, the report is marked "awaiting materials", the ticket is closed in the count. The tenant hears nothing for three weeks and calls again. That second contact often counts as a new report, with a new response-time clock. On paper your service level looks good, in reality she's waited nine weeks.

Reports that depend on third parties. The contractor schedules the first appointment fine, but the second appointment shifts without anyone informing the tenant. Between you and the contractor, things go quiet. The tenant only sees the silence.

In practice, these three cohorts explain a large part of your tail. And they have one thing in common: they arise at the handover points in your process, not at the first response.

What to measure instead

The question isn't "what's my average response time". The question is "how many reports are currently waiting longer than five working days for a first or follow-up response". That's a different measurement, with a different lever to pull.

If you build the figure as a percentile (P95 instead of average), it forces you to look at the tail. The Aedes benchmark 2025 shows that the sector average sits stable around 7.7. Stable, not rising. The gain isn't in adding another tenth of a point to the average, but in the tenants who currently give a 4 or a 5 and drag the whole score down with them.

In practice, that means a daily list of reports older than five days, split by the three cohorts above. Not to hold anyone accountable to a KPI, but to see where the handover stalls. It's often the same handover, week after week.

The conversation that changes this

The hardest part of this switch isn't the measurement, it's the conversation with the organisation. Someone set your average response time to green, and you're the one telling them that the figure they hit isn't what tenants actually experience. That rarely goes down well.

What helps is putting the cohort data alongside it. Not "our average is lying", but "these are the six reports from last week that have been open for more than five days, and in four of them the same step is stuck". Then the conversation stops being about whether the figure is correct, and starts being about where the organisation is stalling. And that's the conversation that actually helps the tenant.