MJR INTELLIGENCE GROUP
Fractional Analytics

The audit that checked 132 dashboards so people didn't have to

A case study from the founder's work inside a Fortune 100 analytics organization. The client is anonymized; no client name, data, or screenshots are used.

The problem

Years of dashboard building had left 132 Tableau workbooks in production with no reliable inventory of which ones were still correct. Fiscal-year logic had changed, and every workbook that handled it wrong was a decision waiting to be made on bad numbers. A manual audit — open each workbook, trace its calculations, check five categories of fiscal-year problems — would have taken weeks of analyst time nobody had.

What was built

An automated audit tool that read every workbook by itself, checked each one against the five problem categories, and produced a findings report with a specific fix instruction for every issue — so workbook owners could repair their own work instead of waiting on the audit team.

The results

132
workbooks audited end-to-end
84
flagged with at least one problem
4,062
individual findings, each with a fix path
Zero
findings against the work in the company's own security audit of the project

And it finished ahead of the fiscal deadline.

Why this is the founding audit, productized

This is exactly the $950 Reporting Health Check MJR sells first: connect, scan everything, hand the owner a plain-English report of what's broken, what's stale, and what it will cost to fix — before anyone commits to a build or a retainer. The founder isn't selling a method he read about. He has already run this audit, at scale, under a real deadline.

And this is what the ongoing work looks like

After the build, clients don't get raw exports — they get instruments a busy owner can read in two minutes. Samples below use illustrative data.

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