TASK UNWIND — WEEKLY REPORTING PORTFOLIO

START HERE
Open Task_Unwind_Reporting_Portfolio.xlsx in Excel. Begin on Report, then
inspect Prepared, Source and Guide. Or open sample_output/report.html in a
browser for the finished report, with no installation required.

THE PROBLEM
A fictional service team receives an inconsistent weekly export. Duplicates,
missing fields and invalid values would distort its workload and SLA metrics.

THE SOLUTION
The workflow preserves raw inputs, normalizes ticket IDs and team names,
quarantines questionable records and produces a traceable weekly summary.
Both copies of duplicate IDs are excluded until a reviewer resolves them.

BASELINE RESULTS — FICTIONAL DEMONSTRATION
97 source records; 87 included; 10 needing review.
129.0 effort hours; 83.9% within SLA; 21.7 average resolution hours.
The review set contains both copies of a duplicate ticket, a missing ID,
an unknown team, missing/negative effort, an invalid date, negative and
non-numeric resolution values, and an invalid SLA target.

EXCEL REFRESH
Set Report C5 to a Monday. F5 and the four weekly dates update automatically.
Clear Source A2:F207, then paste a replacement batch in the six-column layout.
Dates must be actual Excel dates and hours must be numeric. Capacity is 206
records. Do not paste over Prepared formulas. Filter its Disposition column
to Review, correct the original Source values, and review the updated totals.
Do not insert or sort Source rows independently of Prepared. Sort/filter the
Prepared table when inspecting results. The workflow holds cell references,
not persistent source-system identifiers for its row numbers.

PYTHON REFRESH (OPTIONAL)
Python 3 is required. No extra packages, accounts or API keys are needed.
From this extracted folder, run:
  python3 automate_report.py
For another CSV and reporting window:
  python3 automate_report.py --input your_export.csv --output your_report --start 2026-09-28 --end 2026-10-25
CSV dates must be YYYY-MM-DD. Use the six exact sample headers in order.
The script produces accepted_records.csv, exceptions.csv, summary.json and
report.html. It does not modify the workbook. Existing output filenames in
the selected output folder are replaced when you run it again.

VALIDATION AND LIMITS
Workbook metrics were checked against an independent calculation and the
Python results. Excel input-change tests covered an added record, zero effort,
exact SLA equality, end-date inclusion, out-of-period exclusion and a changed
reporting window. Python boundary tests also covered blanks, duplicates,
unknown teams, invalid targets, non-finite numbers and an empty batch.
The workbook was rendered and inspected. It has not been opened or tested in
desktop Microsoft Excel. No macros, external connections, scheduling, source
fetching, email delivery or production integrations are included.

PORTFOLIO DESCRIPTION
Repeatable weekly reporting workflow using Excel and Python. Standardizes
inconsistent service data, isolates duplicates and incomplete records, and
produces workload and SLA summaries with an auditable exception list.

All data is synthetic. This sample was built with AI assistance for Task
Unwind. It is not a client engagement and does not establish measured time
savings. Review and practice the workflow before presenting it as a sample
you can independently explain and support.

Task Unwind
https://taskunwind.com
hello@taskunwind.com
