Flow and pull

WIP aging report

WIP aging report is licensed CC BY 4.0. Attribution: Katafacts (katafacts.com).

1 · What it is

What it is

A WIP aging report answers one question a point-in-time snapshot can't: not how much work is open, but which specific pieces of it have been sitting the longest relative to their peers. Every item gets one thing measured — how many days it's been in its current stage — and from that, each stage's average age and which items are aging at least twice their stage's average get computed. Those items are stalled, not just old; a queue where everything is uniformly slow has a different problem than a queue where one item has quietly sat for months while everything else moves normally.

2 · When to use it

When to use it — and when not to

Use it when

You have a queue, pipeline, or workflow with items currently open — not yet complete — and a record of when each entered its current stage.
You want to know which specific items need attention now, not just an overall count of what's open.
You suspect a small number of items are stalled and skewing the queue's overall feel, but can't point to which ones without a proper count.

Not when

Everything in scope has already finished — that's a cycle-time or lead-time analysis on completed work, not this.
You only have a total count of open items with no per-item entry date — there's nothing to compute an age from.
The queue has fewer than a handful of items in most stages — the stage-average comparison this tool relies on needs more than one item per stage to mean anything.

3 · How to fill it in

How to fill it in

Scope: Which pipeline, workflow, or queue, as of what date? A snapshot with no stated boundary blends queues that don't belong together into a report that describes neither.
Open items: List every currently-open item with its current stage and the date it entered that stage. Pull real dates from a system of record — a guessed entry date defeats the point of measuring age at all.
Stage averages: Each stage's average age among its currently-open items — computed for you, nothing to enter here.
Overall summary · Stalled items: The overall average age, the single oldest item, and which items are flagged as stalled (aging at least twice their stage's average) — all computed for you.
Narrative: Drafted from the stall flags and your observation notes — what you've seen or heard about why a specific item is actually stuck.
Countermeasures: What will you do about the stalled items, ranked by impact and effort, owned and dated? A countermeasure not tied to a named stalled item is a coaching failure mode, not a real action.

4 · What good looks like

What good looks like

The example below is an IT service request queue's WIP aging: real entry dates per item, stage averages with the arithmetic shown, one item correctly flagged as stalled at more than 2x its stage's average, and a countermeasure that traces directly to that specific item rather than a generic 'work faster' push.

Same example, as a downloadable xlsx workbook.

Download .xlsx

WIP aging report · as of 2026-03-01

IT service request queue — WIP aging

Sam Torres, Service Desk Lead · 2026-03-01

Team: Nina Petrov, Support · Sponsor: Alex Romero, IT Director

Scope

Scope covers every open service request as of 2026-03-01, across triage, in-progress, and review — excludes closed requests, which are a separate reporting view.

Open items

Item	Stage	Entered	Age (days)
REQ-101	Triage	2026-02-27	2
REQ-102	Triage	2026-02-26	3
REQ-103Stalled	Triage	2026-01-15	45
REQ-104	In progress	2026-02-20	9
REQ-105	In progress	2026-02-15	14
REQ-106	Review	2026-02-28	1

Stage averages

Stage	Items	Average age (days)
Triage	3	16.7
In progress	2	11.5
Review	1	1

Overall summary · Stalled items

Average age

12.3 days

Open items

(2 + 3 + 45 + 9 + 14 + 1) / 6 = 12.3 days

Oldest item

REQ-103 (Triage)

45 days

Stalled items

REQ-103 — 45 days is at least 2x this stage's average of 16.7 days — this item is stalled relative to its peers.

Narrative

REQ-103 is the one stalled item, sitting in triage for 45 days against that stage's 16.7-day average — more than double, and the oldest item in the whole queue. The observation notes point to an unanswered vendor follow-up as the specific blocker, not a triage-process problem generally, since the other two triage items are both under a week old. Overall queue average age is 12.3 days across 6 open items.

Countermeasures

Escalate the outstanding vendor follow-up on REQ-103 directly rather than waiting on the vendor's own SLA, since the ticket has already sat unanswered for 45 days.
Linked finding: REQ-103 — stalled at 45 days, 2.7x the triage stage average
Impact: high · Effort: low · Owner: Sam Torres · Due: 2026-03-08
Add a standing follow-up reminder for any triage ticket blocked on a third party for more than 10 days, so a REQ-103 situation surfaces automatically instead of relying on someone noticing.
Linked finding: REQ-103 — 45 days with no follow-up recorded since the initial ticket
Impact: medium · Effort: low · Owner: Nina Petrov · Due: 2026-03-15

5 · Common mistakes

Common mistakes

Treating every item with a nonzero age as worth flagging.
Same vital-few discipline as every other artifact in this catalogue (master-plan §1.3) — one item genuinely stalled relative to its peers beats a list of every item that isn't brand new.
Comparing an item's age against the overall average instead of its own stage's average.
A stage that's naturally slower than others (a review step vs. a quick triage step, say) will always look 'stalled' against the overall average even when every item in it is moving normally — the comparison has to be within the stage, not across the whole queue.
Running this on a stage with only one or two items and treating the result as meaningful.
There's no real 'average' to compare against with that little data — a single item can't be 2x its own average, which is exactly why this tool never flags a single-item stage.

6 · What it connects to

What it connects to

upstream

Kanban sizing calculator
A WIP limit sized too high is exactly what produces a queue with room for items to quietly stall — this report is where that shows up after the fact.

downstream

A3 problem solving
Once a stalled item is named, an A3 is where you'd run root cause analysis in depth if the blocker isn't already obvious from the observation notes.

7 · Where AI helps

Where AI helps

Judgement — stays yours

Deciding whether a stalled item needs immediate escalation or can wait for the next regular check-in
Committing to which countermeasure to act on first

Analysis — AI helps

Drafting the narrative from observation notes and the stall-flag findings
Pressure-testing whether a proposed countermeasure actually addresses the named stalled item

Drudgery — automated

Computing every item's age, each stage's average, and which items are stalled, with the arithmetic shown
Identifying the single oldest item in the whole queue
Exporting to xlsx in the house format

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