Report Usage Analytics and Decommission Flagging
BI environments accumulate dashboards the way email accumulates unread newsletters — someone builds one for a specific project or a one-time request, it gets left running on a scheduled refresh forever, and within a year or two nobody remembers whether anyone actually still looks at it. Each unused dashboard still consumes refresh compute, still clutters search results when someone's trying to find the one they actually need, and still shows up as a maintenance burden whenever the underlying data source changes and every downstream dashboard needs updating, whether or not a single person has opened it in the last six months.
STARTING PRICE
From €299
Standard tier · Multi-step workflow with AI extraction/decisioning and 2-3 integrations.
Get a quote →Saves roughly 4-6 hrs/month of manual dashboard audits plus reduced refresh compute costs from decommissioning genuinely unused reports.
How the automation works
We pull view logs directly from your BI platforms and build a usage profile per dashboard — last viewed date, distinct viewers over a rolling window, and whether it's on a scheduled refresh that keeps consuming compute regardless of whether anyone's watching. Dashboards crossing a configurable low-usage threshold get flagged for review with their owner, along with the specific evidence (zero views in ninety days, one viewer who hasn't logged in for six months) rather than a blanket 'this looks unused' guess, and owners confirm decommissioning, archive-but-keep, or flag as intentionally low-frequency (a quarterly board report that's genuinely only opened four times a year and shouldn't be flagged the same way as an abandoned one).
Process flow
- 01
Collect view logs from BI platforms integration
Dashboard and report view logs are pulled directly from Tableau, Looker, and Power BI, capturing who viewed what and when.
- 02
Build a usage profile per dashboard ai
Each dashboard gets a usage profile: last viewed date, distinct viewer count over a rolling window, and refresh schedule and compute cost where available.
- 03
Flag low-usage dashboards with evidence ai
Dashboards crossing a configurable low-usage threshold are flagged with the specific supporting evidence, not a generic unused label.
- 04
Exclude known intentionally low-frequency reports ai
Dashboards explicitly tagged as intentionally infrequent, such as a quarterly board report, are excluded from standard low-usage flagging logic.
- 05
Route to owner for a decision output
Flagged dashboards route to their listed owner to confirm decommissioning, archiving, or explicit low-frequency exemption.
Inputs
- BI platform view/access logs
- Dashboard refresh schedule and compute cost data
- Dashboard ownership records
- Intentional low-frequency dashboard tags
Outputs
- Low-usage dashboard flag list with evidence
- Owner decision queue (decommission/archive/exempt)
- Refresh compute savings estimate from decommissioning
- Usage trend report across the BI environment
Works with
Prefer a fully custom build instead of an off-the-shelf integration? We scope both options during your free consultation — most jobs like this one work fine on standard connectors, but higher-volume or non-standard systems sometimes need bespoke API work, reflected in the complex tier.
Where this goes wrong if you get it wrong
- View count alone misses dashboards embedded elsewhere — a dashboard feeding a scheduled email digest or embedded in another application might show near-zero direct 'opens' in the BI platform while still being actively consumed through a channel the view logs don't capture, so usage tracking needs to account for embedded and distribution-based consumption, not just direct login views.
- A dashboard with low view count isn't automatically safe to decommission if it's the source data or the underlying model that other dashboards or downstream processes depend on — decommissioning needs a downstream dependency check, not just a usage number, or removing it breaks something invisible to the usage report alone.
- Executives and senior leaders often view dashboards infrequently but with high stakes attached to each view — a CFO checking a specific report once a quarter right before a board meeting looks identical, in raw usage terms, to an abandoned dashboard nobody needs, and the flagging logic needs role-aware context, not a flat usage threshold applied to everyone equally.
- Flagging every low-usage dashboard for decommissioning without asking why usage is low can miss the real problem — sometimes a dashboard is unused because it's genuinely obsolete, and sometimes it's unused because nobody knows it exists or it's hard to find, which is a discoverability problem with a different fix than deletion.
Frequently asked questions
Does this delete unused dashboards automatically?
No, it flags them with supporting usage evidence and routes to the owner for a decision — decommissioning, archiving, or marking as intentionally low-frequency is always a human confirmation, not an automatic deletion.
How does it handle reports that are genuinely only needed a few times a year?
Dashboards can be explicitly tagged as intentionally low-frequency, such as a quarterly board report, which excludes them from the standard low-usage flagging that would otherwise misclassify them as abandoned.
What about dashboards embedded in other tools or distributed by email, not viewed directly?
Usage tracking is extended to account for embedded views and scheduled distribution where the BI platform exposes that data, since direct login-based view counts alone would understate real usage for those dashboards.
Is it safe to decommission a flagged dashboard right away?
A downstream dependency check is recommended before removal, since a low-usage dashboard might still be a data source or model that other, more actively used dashboards depend on.