Backlog analysis · no data loaded yet

Backlog Currents

A prioritised backlog promises an order of work. Week by week, items climb, sink, sit still, or skip the queue altogether. This page replays those moves from your weekly exports, then shows what the flow says about how work really gets chosen.

  • New
  • Moved up
  • Moved down
  • Started
  • Removed or left

Drop one export per week (or one file with a date column). “Moved” means re-prioritised by 3 or more places against the items that stayed, so shifts caused by work leaving the top don’t count.

What files do I need?
Azure DevOps
  1. Make a query for your backlog items with State not Done or Closed, sorted by Backlog Priority.
  2. Columns: ID, Title, State, Backlog Priority.
  3. Export to CSV once a week or sprint. Put the date in the file name, e.g. backlog-2026-10-19.csv.
Jira
  1. Filter: project = ABC AND statusCategory != Done ORDER BY Rank.
  2. Export CSV with Issue key, Summary, Status. Row order is used as the rank.
  3. Same routine: one dated file per week or sprint.
One file with history
  1. Columns Date, ID, Title, State, Rank, one row per item per snapshot (e.g. from ADO Analytics). “Copy a sample CSV” gives this format.
  2. Keep just-started items (Active, Committed, In Progress) in the export so the page can tell started work from removed work.

Made by Dr David Michel, The Agile Broadcast. Try it online.

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Drop weekly CSV exports from Azure DevOps or Jira above to replay your own backlog. Or look around first with a made-up team's example.