Audit advanced Works with: Any AI

Monday.com Project Delivery Performance Audit

Table output Has example

• 📅 Monday.com

Measure plan versus actual across completed items.

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Compare plan with actual delivery using this monday.com data: [COMPLETED_ITEMS_WITH_PLANNED_AND_ACTUAL_DATES_AND_HOURS]. Period: [PERIOD].

Explain what you counted as planned and what as actual if the columns are ambiguous, and show one fully worked row so I can check your method. Treat items without actual dates as not finished rather than late. Calculate average slip in days (actual end minus planned end), share finished on time, hours variance as (actual minus estimated) divided by estimated, and variance by item type or owner role. Report medians next to averages, and a table by item type with counts; say which types have too few examples and treat their results as tentative. Describe the shape of the slip: are most items a little late, or a few very late? That changes the advice.

Give three hypotheses for any large variance with a test, separate estimation problems from scope change if the data allows, and do not rank people. Plan next quarter's improvement: record the reason for every slip in a dropdown, review the reasons monthly, and adjust plans by the typical slip only after at least 20 items support it. Recommend two planning changes and how we will check them.

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Invented data for 30 completed items. Planned versus actual end: on time 18 (60 percent); average slip for the 12 late items 5 days (total 60 days); median slip 4 days. Hours: estimated 420, actual 504; variance (504 - 420) / 420 = 20 percent. Design items: estimated 120, actual 132 (+10 percent). Build items: estimated 200, actual 270 (+35 percent).
Reading: build items are under-estimated. Next quarter, add a 30 percent buffer to build estimates for three items and compare. Record the reason for each slip in a dropdown.

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