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Backlog age: the histogram that tells you if your backlog is a to-do list or a graveyard

Backlog age buckets every currently-open Jira issue by how long it's been sitting since it was created — 0–7 days, 7–30, 30–90, and 90-plus. There's no date-range filter on this one; it's computed fresh every time, so it always answers the same blunt question: how old is what you haven't touched, right now, today.

deckgauge · Board · Intelligence
0–7d
7–30d
30–90d
90d+

A healthy shape — most mass in the youngest bucket, a thin old tail.

What it measures, and where the data comes from

Every issue this pulls is currently open in Jira — done and closed issues never enter the count. Age is simply "now minus created date," bucketed into four fixed ranges: 0–7 days, 7–30 days, 30–90 days, and 90 days or more. No status filtering beyond open/closed, no priority weighting — just how long each thing has existed without being finished.

The "computed fresh each time" part matters more than it sounds. There's deliberately no window to select, no "last 90 days" toggle to hide behind — the moment you open the chart it's telling you about the backlog as it stands right now, not as it stood at some report-generation time last week.

Age isn't the same as stuckAn old issue waiting on a customer, blocked by an external dependency, or deliberately deprioritized for a good reason still ages the same as one nobody's looked at in months. This chart tells you where to look, not automatically why it's there — check a sample from the 90d+ bucket before you assume neglect.

How to read it

Look at the shape of the mass, left to right, the same way you'd read PR Size Distribution. A healthy backlog looks like the mockup above — tallest bar at 0–7d, a shorter one at 7–30d, and the two older buckets small enough you'd have to squint. That's a team where new work gets triaged and moved quickly, and old work gets cleared rather than accumulated.

Two unhealthy shapes to watch for specifically: a 90d+ bucket that's large or the largest bar in the chart, and a thin 0–7d bucket sitting right next to a fat older tail. The first says grooming has lapsed. The second says something subtler — intake itself is small compared to what's already stuck, so even a quiet week won't fix anything, because the backlog's problem isn't new work, it's old work that never left.

What it tells you over time

Because there's no filter, the only way to see a trend is to check back and compare shapes — this week's histogram against last month's. Watch whether weight is draining out of the old buckets over time or building up in them. A 90d+ bar that keeps growing check after check means whatever process used to close out old issues has quietly stopped running, whether that's a person, a habit, or an automation nobody noticed break.

Example situations

1. The 90d+ bucket is the biggest bar in the chart

deckgauge · Backlog Age
0–7d
7–30d
30–90d
90d+

Old issues now outweigh everything newer.

What you're seeing: the bars climb steadily older, left to right, with 90d+ towering over everything else. This isn't one bad sprint — a bucket this size takes months of low-priority issues quietly accumulating without anyone deciding to deal with them.

How to react: resist the urge to just triage the newest issues faster — that does nothing for a tail that's already this size. The 90d+ bucket needs a dedicated pass, not incremental attention squeezed into normal sprint work.

Managerial playSchedule an actual grooming session — not "as time allows," a calendar slot with the team in the room. Go through the 90d+ bucket issue by issue and force one of three honest outcomes for each: close it if it's stale, revive it with a real owner and date if it still matters, or delete it outright if it never will. The goal isn't to make the bar smaller for the chart's sake — it's to stop carrying issues that everyone already knows, quietly, are never getting done.

2. A thin intake bucket next to a fat old tail

deckgauge · Backlog Age
0–7d
7–30d
30–90d
90d+

Barely anything new — but the old buckets are still full.

What you're seeing: the 0–7d bar is the shortest one in the chart, not the tallest — new intake has genuinely slowed down. But the older buckets haven't shrunk to match; they're still carrying most of the backlog's weight. A quiet week at the front didn't fix anything at the back.

How to react: don't read the thin intake bar as good news on its own — it's easy to mistake "not much new is coming in" for "the backlog is under control," and this shape says otherwise. The team has capacity that isn't going toward the old, stuck work either.

Managerial playUse the light intake week deliberately — this is exactly the moment to redirect capacity at the old tail instead of waiting for it to refill with new requests. Say it plainly in planning: "stop starting, start finishing" for a sprint or two, and measure success by how much the 30–90d and 90d+ bars shrink, not by how much new work got picked up. A quiet front door is an opportunity, not a metric to celebrate by itself.

Frequently asked

What is backlog age?
Backlog age buckets every currently-open Jira issue by how long it has existed since creation: 0-7 days, 7-30, 30-90, and 90-plus. It is computed fresh each time with no date-range filter, so it always answers what your untouched work looks like today.
What does a large 90-day-plus bucket mean?
It means the backlog is functioning as a graveyard rather than a to-do list. Work that has sat for over 90 days is very unlikely to be picked up as-is, and keeping it open inflates every other backlog figure you report.
Why is there no date filter on this widget?
Because backlog age is a snapshot question, not a historical one. Filtering it by date would answer how old issues were at some past moment, which is not the decision this chart supports.

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